Journal articles on the topic 'Vehicle range'
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Lee, Kwan Hyeong. "Improvement in Target Range Estimation and the Range Resolution Using Drone." Electronics 9, no. 7 (July 13, 2020): 1136. http://dx.doi.org/10.3390/electronics9071136.
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This study measured the speed of a moving vehicle in multiple lanes using a drone. The existing methods for measuring a vehicle’s speed while driving on the road measure the speed of moving automobiles by means of a sensor that is mounted on a structure. In another method, a person measures the speed of a vehicle at the edge of a road using a speed-measuring tool. The existing method for measuring a vehicle’s speed requires the installation of a gentry-structure; however, this produces a high risk for traffic accidents, which makes it impossible to measure a vehicle’s speed in multiple lanes at once. In this paper, a method that used a drone to measure the speed of moving vehicles in multiple lanes was proposed. The suggested method consisted of two LiDAR sets mounted on the drone, with each LiDAR sensor set measuring the speed of vehicles moving in one lane; that is, estimating the speed of moving vehicles in multiple lanes was possible by moving the drone over the road. The proposed method’s performance was compared with that of existing equipment in order to measure the speed of moving vehicles using the manufactured drone. The results of the experiment, in which the speed of moving vehicles was measured, showed that the Root Mean Square Error (RMSE) of the first lane and the second lane was 3.30 km/h and 2.27 km/h, respectively. The vehicle detection rate was 100% in the first lane. In the second lane, the vehicle detection rate was 94.12%, but the vehicle was not detected twice in the experiment. The average vehicle detection rate is 97.06%. Compared with the existing measurement system, the multi-lane moving vehicle speed measurement method that used the drone developed in this study reduced the risk of accidents, increased the convenience of movement, and measured the speed of vehicles moving in multiple lanes using a drone. In addition, it was more efficient than current measurement systems because it allowed an accurate measurement of speed in bad environmental conditions.
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Szumska, Emilia M., and Rafał S. Jurecki. "Parameters Influencing on Electric Vehicle Range." Energies 14, no. 16 (August 7, 2021): 4821. http://dx.doi.org/10.3390/en14164821.
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There is a range of anxiety-related phenomena among users and potential buyers of electric vehicles. Chief among them is the fear of the vehicle stopping and its users getting “stuck” before reaching their designated destination. The limited range of an electric vehicle makes EV users worry that the battery will drain while driving and the vehicle will stall on the road. It is therefore important to know the factors that could further reduce the range during daily vehicle operation. The purpose of this study was to determine the effect of selected parameters on a battery’s depth of discharge (DOD). In a simulation study of an electric vehicle, the effects of the driving cycle, ambient temperature, load, and initial state of charge of the accumulator on the energy consumption pattern and a battery’s depth of discharge (DOD) were analyzed. The simulation results confirmed that the route taken has the highest impact on energy consumption. The presented results show how significantly the operating conditions of an electric vehicle affect the energy life. This translates into an electric vehicle’s range.
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Dimitrova, Zlatina. "Optimal designs of electric vehicles for long-range mobility." MATEC Web of Conferences 234 (2018): 02001. http://dx.doi.org/10.1051/matecconf/201823402001.
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This paper introduces the major priorities of the automotive industry of reducing energy consumption and emissions of the passenger cars of the future and of delivering an efficient mobility service for customers. The number of electric vehicles and hybrid electric vehicles is increasing in the mobility market. The problems of the range and the energy storage of the vehicle on board are important. This paper studies the energy system of electric vehicles for different ranges and mobility usages. A multi-objective optimization method is applied to estimate the optimal vehicle energy system designs for urban mobility and for long way electric mobility (> 500 km). Optimal designs considering technical, economic and environmental criteria are presented. The relations between the vehicle ranges and the energy densities of high voltage batteries are illustrated. The boundary of the system is extended to the vehicles and the grid system, including the charging infrastructure. The vehicle energy systems and recharging needs are analysed for a range of 500 km on electric drive.
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Musabini, Antonyo, Kevin Nguyen, Romain Rouyer, and Yannis Lilis. "Influence of Adaptive Human–Machine Interface on Electric-Vehicle Range-Anxiety Mitigation." Multimodal Technologies and Interaction 4, no. 1 (February 14, 2020): 4. http://dx.doi.org/10.3390/mti4010004.
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The electrification of vehicles is without a doubt one of the milestones of today’s automotive technology. Even though industry actors perceive it as a future standard, acceptance, and adoption of this kind of vehicles by the end user remain a huge challenge. One of the main issues is the range anxiety related to the electric vehicle’s remaining battery level. In the scope of the H2020 ADAS&ME project, we designed and developed an intelligent Human Machine Interface (HMI) to ease acceptance of Electric Vehicle (EV) technology. This HMI is mounted on a fake autonomous vehicle piloted by a hidden joystick (called Wizard of Oz (WoZ) driving). We examined 22 inexperienced EV drivers during a one-hour driving task tailored to generate range anxiety. According to our protocol, once the remaining battery level started to become critical after manual driving, the HMI proposed accurate coping techniques to inform the drivers how to reduce the power consumption of the vehicle. In the following steps of the protocol, the vehicle was totally out of battery, and the drivers had to experience an emergency stop. The first result of this paper was that an intelligent HMI could reduce the range anxiety of the driver by proposing adapted coping strategies (i.e., transmitting how to save energy when the vehicle approaches a traffic light). The second result was that such an HMI and automated driving to a safe spot could reduce the stress of the driver when an emergency stop is necessary.
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Evelyn, Evelyn, Abd Rashid Abd Aziz, and Poetro Lebdo Sambegoro. "A Review of Range Extender Technologies in Electric Vehicles." International Journal of Sustainable Transportation Technology 3, no. 1 (April 30, 2020): 7–11. http://dx.doi.org/10.31427/ijstt.2020.3.1.2.
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With the increasing global concern on negative environmental effect from the transportation sector, conventional automobile technologies will not be viable for much longer. Countries like the EU and China have introduced emission related regulations which are stricter than ever. This has compelled automotive manufacturer to turn to Electric Vehicles (EV) as the most effective solution to this issue. There are mainly two types of EV, namely Battery Electric Vehicle (BEV) and Hybrid Electric Vehicle (HEV). Both has its own strength and shortcomings, BEV with zero emission but limited range while HEV has better range at the expense of higher emission. Extended Range Electric Vehicle (EREV) provides a midpoint between these options. This option provides the best of both worlds by allowing users to switch between both systems depending on the vehicle’s operating condition. This paper aims to presents a variety of Range Extender (RE) configurations based on its working principle and type of fuel used. Internal combustion engine, fuel cell, and microturbine are what RE is commonly powered by. The advantages and disadvantages are evaluated and compared to determine the optimal option. It was concluded that depending on fuel availability, space, and efficiency requirement, each configuration has its own merit.
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Kim, Seiho, Jaesik Lee, and Chulung Lee. "Does Driving Range of Electric Vehicles Influence Electric Vehicle Adoption?" Sustainability 9, no. 10 (October 1, 2017): 1783. http://dx.doi.org/10.3390/su9101783.
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Ramasamy, Latha, Ashok Kumar Loganathan, and Rajalakshmi Chinnasamy. "Mathematical modelling of vehicle drivetrain to predict energy consumption." Indonesian Journal of Electrical Engineering and Computer Science 27, no. 2 (August 1, 2022): 638. http://dx.doi.org/10.11591/ijeecs.v27.i2.pp638-646.
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Nowadays, <span>many firms have started producing electric vehicles (EVs). One of the biggest challenges to broad acceptance of electric vehicles is their limited range EVs. Forecasting future energy usage is one of the way to calculate the driving range. In this paper, a simulation model of the drivetrain has been developed to evaluate the energy flow of a vehicle for the given torque and speed conditions. The energy consumption of an electric vehicle is determined by the vehicle's attributes. Road torque, road speed, motor model, motor controller model, battery model, and PI controller are the primary components of the model. The overall resistive force offered by the vehicle, as well as energy consumption owing to resistive force during motoring and regeneration has been validated through the simulation results. Here, the vehicle model, Mercedes Benz Class C Saloon has been considered</span>.
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Joseph, Binsy, and Deepak Vishnu Bhoir. "Design and Assessment of Electric Vehicle Performance Parameters based on Drive Cycle." ITM Web of Conferences 40 (2021): 01007. http://dx.doi.org/10.1051/itmconf/20214001007.
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Electric vehicle plays a significant role, in the future transportation across the world. EV has the potential to reduce air pollution and emission of Greenhouse gasses significantly compared to the existing fossil-fuel-based vehicles. Even though substantial progress can be expected in the area of embarked energy storage technologies, charging infrastructure, customer acceptance of Electric Vehicles is still limited due to the problems of Driving range anxiety and long battery charging time. We can solve most of these problems with the infrastructure development ,optimum sizing and design of the vehicle components and extensive study on vehicle dynamics under various real-time driving conditions. This research focuses on the Matlab software based co-simulation of Electric Vehicle system, including the battery pack and motor, to predict the vehicle performance parameters like driving range, efficiency, power requirement, and energy characteristics under different driving scenarios. The vehicle’s acceleration performance, energy consumption, and efficiency are determined by simulation and verified analytically. Using ADVISOR software the fuel economies and tail pipe emission for various vehicle models are determined by simulation and results are compared with Hybrid Electric vehicle models.
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Zaeri, Naser. "A heterogeneous short-range communication platform for internet of vehicles." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 3 (June 1, 2021): 2165. http://dx.doi.org/10.11591/ijece.v11i3.pp2165-2177.
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The automotive industry is rapidly accelerating toward the development of innovative industry applications that feature management capabilities for data and applications alike in cars. In this regard, more internet of vehicles solutions are emerging through advancements of various wireless medium access-control technologies and the internet of things. In the present work, we develop a short-range communication–based vehicular system to support vehicle communication and remote car control. We present a combined hardware and software testbed that is capable of controlling a vehicle’s start-up, operation and several related functionalities covering various vehicle metric data. The testbed is built from two microcontrollers, Arduino and Raspberry Pi 3, each of which individually controls certain functions to improve the overall vehicle control. The implementation of the heterogeneous communication module is based on the Institute of Electrical and Electronics Engineers (IEEE) 802.11 and IEEE 802.15 medium access control technologies. Further, a control module on a smartphone was designed and implemented for efficient management. Moreover, we study the system connectivity performance by measuring various important parameters including the coverage distance, signal strength, download speed and latency. This study covers the use of this technology setup in different geographical areas over various time spans.
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R, Tejashwini, and Dr Subodh Kumar Panda. "Design and Development of Vehicle Theft Detection, Tracking and Accident Identifier System using IoT." Journal of University of Shanghai for Science and Technology 23, no. 07 (July 8, 2021): 420–25. http://dx.doi.org/10.51201/jusst/21/07168.
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Vehicle security is one of the major concerns that the entire world is currently experiencing. People generally own automobiles, yet these automobiles are not always secure. Vehicle theft occurs in parking lots, public places, and other unsafe areas. The vehicle’s manufacturer does not consider the vehicle security system to be a factor in the overall cost of the vehicle. Nowadays, only a few vehicles come equipped with high-priced security systems. Door locking, alarm system, GSM, GPS, and other security features are built into high-end vehicles only. There is a necessity to build a low-cost security system for vehicles that common people can afford it and the manufacture can built-in the security system in a wide range of automobiles. This paper proposed a method for vehicle theft detection, tracking, and accident identification using the Internet of Things.
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Wang, Limian, Shumao Wang, and Zhenghe Song. "Control Strategy and Performance Simulation Study on Extended Range Electric Vehicle." E3S Web of Conferences 79 (2019): 03006. http://dx.doi.org/10.1051/e3sconf/20197903006.
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Electric vehicles are recognized as an effective way to alleviate the energy crisis and environmental degradation, and extended range electric vehicles which have both the technical advantages of hybrid electric vehicles and pure electric vehicles, have gradually become a research hotspot in the automotive industry. In this paper, the system structure design of the extended range electric vehicle is carried out. On the basis of the pure electric vehicle, the engine and generator set are added. The control strategy model is established and the simulation research is carried out. The results show that the proposed control strategy model optimizes the working range of the range extender, takes into account the performance of the battery and the drive motor, and shows good tracking characteristics.
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Petovello, Mark G., Kyle O'Keefe, Phil Wei, and Chaminda Basnayake. "Assessment of Different Sensor Configurations for Collaborative Driving in Urban Environments." International Journal of Navigation and Observation 2013 (March 10, 2013): 1–16. http://dx.doi.org/10.1155/2013/767313.
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Vehicle-to-vehicle relative navigation of a network of vehicles travelling in an urban canyon is assessed using least-squares and Kalman filtering covariance simulation techniques. Between-vehicle differential GPS is compared with differential GPS augmented with between-vehicle ultrawideband range and bearing measurements. The three measurement types are combined using both least-squares and Kalman filtering to estimate the horizontal positions of a network of vehicles travelling in the same direction on a road in a simulated urban canyon. The number of vehicles participating in the network is varied between two and nine while the severity of the urban canyon was varied from 15-to 65-degree elevation mask angles. The effect of each vehicle’s azimuth being known a priori, or unknown is assessed. The resulting relative positions in the network of vehicles are then analysed in terms of horizontal accuracy and statistical reliability of the solution. The addition of both range and bearing measurements provides protection levels on the order of 2 m at almost all times where DGPS alone only rarely has observation redundancy and often exhibits estimated accuracies worse than 200 m. Reliability is further improved when the vehicle azimuth is assumed to be known a priori.
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Zhao, Hongxing, Ruichun He, and Xiaoyan Jia. "Estimation and Analysis of Vehicle Exhaust Emissions at Signalized Intersections Using a Car-Following Model." Sustainability 11, no. 14 (July 23, 2019): 3992. http://dx.doi.org/10.3390/su11143992.
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A signalized intersection is a high fuel consumption and high emission node of a traffic network. It is necessary to study the emission characteristics of vehicles at signalized intersections in order to reduce vehicle emissions. In this study, the combination of a car-following model and the vehicle specific power emission model was used to estimate the vehicle emissions, including the CO2, CO, HC, and nitric oxide (NOX) emissions, at unsaturated signalized intersections. The results of simulations show that, under the influence of the signal light, the substantial changes in a vehicle’s trajectory increase the CO2, CO, HC, and NOX emissions. The CO2, CO, HC, and NOX emissions from vehicles at signalized intersections were further analyzed in terms of signal timing, vehicle arrival rate, traffic interference, and road section speed. The results show that an increase in the signal cycle, the vehicle arrival rate, and the traffic interference amplitude result in increases in the CO2, CO, HC, and NOX emissions per vehicle at the intersection inbound approach, and an increase in the green signal ratio and the vehicle road section speed within a specified range has a positive significance for reducing the CO2, CO, HC, and NOX emissions of vehicles in the study range. The proposed method can be flexibly applied to the analysis of vehicle emissions at unsaturated signalized intersections. The obtained results provide a reference for the control and management of signalized intersections.
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EL-KABBANY, AHMED, and A. RAMIREZ-SERRANO. "TERRAIN ROUGHNESS ASSESSMENT FOR HIGH SPEED UGV NAVIGATION IN UNKNOWN HETEROGENEOUS TERRAINS." International Journal of Information Acquisition 07, no. 02 (June 2010): 165–76. http://dx.doi.org/10.1142/s0219878910002142.
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This paper addresses the problem of determining the maximum allowable speed (V) of a vehicle traversing unknown off-road terrains. The calculated maximum speed achieves the fastest navigation without exceeding an allowable range of transmitted force (Fall) to the vehicle's frame. The proposed system enables the vehicle to transit between different terrains safely. The system's input are: (i) a 3D range image of the terrain and (ii) the vehicle's dimensions and characteristics (e.g., suspension parameters). First the terrain roughness is assessed; then the corresponding maximum allowable speed is calculated. In this paper a novel Roughness Index (RI) is used to represent the terrain roughness. This index is calculated based on the standard deviation of the terrain points' elevations (3D range image). A closed form expression of the maximum allowable vehicle speed is developed (as function of the vehicle's properties, Fall, RI, and probability of not exceeding Fall). The proposed system can be used as a driver assistant system to enhance the vehicle performance, increase its life time, and reduce the maintenance cost. In addition, it is a key module in Unmanned Ground Vehicles (UGVs) navigation systems; as it provides the navigation system with necessary information for path and speed planning.
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Shimizu, Osamu, Sakahisa Nagai, Toshiyuki Fujita, and Hiroshi Fujimoto. "Potential for CO2 Reduction by Dynamic Wireless Power Transfer for Passenger Vehicles in Japan." Energies 13, no. 13 (June 30, 2020): 3342. http://dx.doi.org/10.3390/en13133342.
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In this study, a novel system named the third-generation wireless in-wheel motor (WIWM-3), which has a dynamic wireless power transfer (DWPT) system, is developed. It can extend the cruise range, which is one of the key specifications of electric vehicles. DWPT also reduces CO2 emission as the driving resistance is reduced due to light weight of the batteries. In this study, CO2 emission by an internal combustion vehicle, a long range drivable electric vehicle with the same cruise range, and an electric vehicle with WIWM-3 equipped with the DWPT system are analyzed using actual measurement data and calculated data based on actual measurement or specification data. A WPT system with WIWM-3 achieves 92.5% DC-to-DC efficiency as indicated by an actual measurement at the nominal position. Thus, the electric vehicle with DWPT can reduce up to 62% of CO2 emission in internal combustion vehicles, and the long-range drivable vehicle emits 17% more CO2 than the electric vehicle with DWPT. Moreover, it is expected that by 2050, electric vehicles with DWPT will reduce CO2 emissions from internal combustion vehicles by 95% in Japan. DWPT systems make electric vehicles more sustainable and, hence, more acceptable for consumers.
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An, Xiaopan, Yu Liu, Hanzhengnan Yu, Zhichao Liu, Songbo Qi, and Yang Wang. "Application of shortening time test in battery electric range calculation of PEV based on CLTC-P." E3S Web of Conferences 268 (2021): 01045. http://dx.doi.org/10.1051/e3sconf/202126801045.
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In order to obtain the actual results of battery electric range test, and meet the demand of fiscal subsidy policy introduction of new energy vehicles, some modifications of the standard GB/T 18386.1 Test Method for Energy Consumption and Range of Electric Vehicles- part1: Light-duty Vehicles are revised by drafting group. Such as China Light-duty vehicle Test Cycle for passenger car (CLTC-P), Shortened time test method, etc. To prove the reasonability of Shortened time test to measure battery electric range (BER) based on CLTC-P, two sets of vehicle tests were carried out. Results show that shortened time test greatly reduce test time, and the weighting factor setting of DS1 and DS2 is reasonable. Although some deviation between Shortened time test and consecutive cycle test exist, but not regularly. It is related to the vehicle energy regulation strategy individually. Finally, it is recommended that the test vehicle should be forced to break 10 minutes after the end of CSSM.
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Wahono, Bambang, Widodo Budi Santoso, Arifin Nur, and Amin. "Analysis of Range Extender Electric Vehicle Performance Using Vehicle Simulator." Energy Procedia 68 (April 2015): 409–18. http://dx.doi.org/10.1016/j.egypro.2015.03.272.
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Gu, Qiang, and Xiu Sheng Cheng. "Electric Vehicle Transmission Gear Ratio Optimization Based on Particle Swarm Optimization." Applied Mechanics and Materials 187 (June 2012): 20–26. http://dx.doi.org/10.4028/www.scientific.net/amm.187.20.
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The driving range of electric vehicles is less than traditional vehicles due to the restriction of energy storage. It is raising the efficiency of each power component that is one of increasing electric vehicle driving range methods. A particle swarm optimization is used to optimize transmission gear ratio on established electric vehicle power component models. A simulation that simulates the energy consumption of vehicle after gear ratio optimization is given to compare with the actual energy consumption data of the vehicle before gear ratio optimization. The results show that the energy consumption and driving range of the latter are better than the former therefore this optimization is valid.
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Tian, Daxin, Yong Yuan, Jian Wang, Haiying Xia, and Jian Wang. "Collision avoidance on winding roads using dedicated short-range communication." Transport 33, no. 2 (January 16, 2017): 461–69. http://dx.doi.org/10.3846/16484142.2016.1278032.
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The emergence of wireless communication technologies such as Dedicated Short-Range Communication (DSRC) has promoted the evolution of collision warning from simple ranging-sensor-based systems to cooperative systems. In cooperative systems, path prediction is a promising method for reflecting a driver’s intention and estimating the future position of vehicles. In this study, a short-term trajectory-modelling method is proposed to predict vehicle motion behaviour in the cooperative vehicular environment. In addition, a collision detection algorithm for winding roads is presented based on a model for determining the minimum distance of vehicles’ future trajectories. The cooperative collision avoidance system’s performance is analysed through simulation, providing useful theoretical insights into the effects of DSRC technology on vehicle collision avoidance in a curved road environment.
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Khan Ankur, Atiquzzaman, Stefan Kraus, Thomas Grube, Rui Castro, and Detlef Stolten. "A Versatile Model for Estimating the Fuel Consumption of a Wide Range of Transport Modes." Energies 15, no. 6 (March 18, 2022): 2232. http://dx.doi.org/10.3390/en15062232.
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The importance of a flexible and comprehensive vehicle fuel consumption model cannot be understated for understanding the implications of the modal changes currently occurring in the transportation sector. In this study, a model is developed to determine the tank-to-wheel energy demand for passenger and freight transportation within Germany for different modes of transport. These modes include light-duty vehicles (LDVs), heavy-duty vehicles (HDVs), airplanes, trains, ships, and unmanned aviation. The model further estimates future development through 2050. Utilizing standard driving cycles, backward-looking longitudinal vehicle models are employed to determine the energy demand for all on-road vehicle modes. For non-road vehicle modes, energy demand from the literature is drawn upon to develop the model. It is found that various vehicle parameters exert different effects on vehicle energy demand, depending on the driving scenario. Public transportation offers the most energy-efficient means of travel in the forms of battery electric buses (33.9 MJ/100 pkm), battery electric coaches (21.3 MJ/100 pkm), fuel cell electric coaches (32.9 MJ/100 pkm), trams (43.3 MJ/100 pkm), and long-distance electric trains (31.8 MJ/100 pkm). International shipping (9.9 MJ/100 tkm) is the most energy-efficient means of freight transport. The electrification of drivetrains and the implementation of regenerative braking show large potential for fuel consumption reduction, especially in urban areas. Occupancy and loading rates for vehicles play a critical role in determining the energy demand per passenger-kilometer for passenger modes, and tonne-kilometer for freight modes.
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Liu, Changhong, Rizacan Sarikaya, Ismar Chew, and Nicholas Jon Robinson. "(Digital Presentation) Using Simulations to Determine the Effects of the Lithium-Ion Battery Pack Sizes on Performance of Electric Vehicles." ECS Meeting Abstracts MA2022-02, no. 3 (October 9, 2022): 198. http://dx.doi.org/10.1149/ma2022-023198mtgabs.
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Internal combustion engine (ICE) vehicles have a longer driving range with a full tank of gas than lithium-ion battery-powered electric vehicles (EVs). Alongside having a higher purchase cost and a lack of charging infrastructure, the range of EVs is a large deterrent to potential buyers. One solution to increasing the range of EVs is using a battery pack with a higher capacity. However, increasing the capacity typically involves an increase in lithium-ion battery cells, which leads to a higher weight, higher vehicle cost, lower energy efficiency, and higher battery charging time. In addition, regenerative braking recovers the vehicle's kinetic energy which is related to speed and weight. To find the optimal battery pack size, a numeric road test simulation can be used to determine how battery pack size affects energy efficiency, driving range, charging time, and cost. This is more optimal than a real-life road test since inconsistent variables like traffic conditions and weather can be controlled. This paper applies work-energy mathematic modeling of an electric vehicle under different EPA dynamometer driving schedules to investigate the problem proposed above, using an EV model with 21700 type lithium-ion cells. In addition, total vehicle weight, motor efficiency, wheel sizes/weight, and the weight of passengers will also be considered. The simulation revealed that when the total vehicle weight reaches a certain point, it can regenerate significant kinetic energy back to the battery pack to increase the range. Figure 1
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Chaudhari, A. R., and R. H. Thring. "Energy economy analysis of the G-Wiz: a two-year case study based on two vehicles." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 225, no. 11 (July 20, 2011): 1505–17. http://dx.doi.org/10.1177/0954407011408369.
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This paper presents the data recorded from two G-Wiz Reva electric vehicles (EVs) over a period of two years and approximately 8000 km on each vehicle. The analysis of the vehicle data demonstrates that the range of the vehicle obtained for a certain state-of-charge (SOC) drop was not consistent. The results show that the main factor affecting the available range was irregular vehicle usage. The recharge energy consumption patterns of the vehicle were identified and it was demonstrated that infrequent vehicle usage increased energy consumed by the vehicle. A maximum range of 66.8 km was achieved when the vehicle was regularly used, but this fell to 42.8 km when it was infrequently used. The energy economy when the vehicle was regularly used was 8.3 km/kWh. Additionally, the analysis results identify the need to determine discharge rate of the vehicle batteries to determine the precise effects on the available range and energy consumption of the vehicle.
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Holjevac, Nikola, Federico Cheli, and Massimiliano Gobbi. "A simulation-based concept design approach for combustion engine and battery electric vehicles." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 7 (June 7, 2018): 1950–67. http://dx.doi.org/10.1177/0954407018777350.
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The early concept design of a vehicle is becoming increasingly crucial to determine the success of a car. Broadening market competition, more stringent regulations and fast technological changes require a prompt response from carmakers, and computer-aided engineering has emerged in recent years as the promising way to provide more efficient and cost-effective design and to cut development time and costs. The work presented in this paper shows an approach based on computer-aided engineering to determine vehicle’s energy consumption and performance. The different vehicle’s subsystem are first analyzed separately by using dedicated simulation tools and then integrated to obtain the entire vehicle. The work covers a wide range of vehicle layouts. Internal combustion engine vehicles and battery electric vehicles are considered and various transmission configurations are contemplated with respect to some of the most adopted solutions for these vehicles. The simulation results allow to identify the most effective design variables regarding the combustion engine and the electric motor and to compare the different layouts over various car segments. The results clearly point out that for internal combustion engine vehicles, the combustion engine is the crucial component that defines the vehicle’s characteristics and particularly the energy consumption. Conversely, battery electric vehicles show a more balanced distribution of the losses, and therefore to improve the vehicle’s behavior, different components should be considered in detail. Nevertheless, the choice of the number of electric motors and the transmission choice play a significant role in defining the vehicle performances.
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Shamma, Zarin Subah, Bridger Jones, Max Clark, Carter Bailey, and Mario Harper. "Electric vehicle range prediction estimator (EVPRE)." Software Impacts 13 (August 2022): 100369. http://dx.doi.org/10.1016/j.simpa.2022.100369.
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Franke, Jörg, Michael Weigelt, Peter M. Bican, and Kilian Batz. "Analysis of Electric Vehicle Range Potentials." ATZ worldwide 121, no. 5 (April 26, 2019): 78–83. http://dx.doi.org/10.1007/s38311-019-0044-0.
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Simpson, Tyler, George Bousfield, Austin Wohleb, and Christopher Depcik. "Electric Vehicle Simulations Based on Kansas-Centric Conditions." World Electric Vehicle Journal 13, no. 8 (July 26, 2022): 132. http://dx.doi.org/10.3390/wevj13080132.
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Range anxiety is a significant contributor to consumer reticence when purchasing electric vehicles (EVs). To alleviate this concern, new commercial EVs readily achieve over 200 miles of range, as found by the United States Environmental Protection Agency (EPA). However, this range, measured under idealized conditions, is often not encountered in real-world conditions. As a result, this effort describes the simplest model that incorporates all key factors that affect the range of an EV. Calibration of the model to EPA tests found an average deviation of 0.45 and 0.57 miles for highway and city ranges, respectively, among seven commercial EVs. Subsequent predictions found significant losses based on the impact of road grade, wind, and vehicle speed over a Kansas interstate highway. For cabin conditioning, up to 57.8% and 37.5% losses in range were found when simulating vehicles at 20 °F and 95 °F, respectively. Simulated aging of the vehicle battery pack showed range losses up to 53.1% at 100,000 miles. Model extensions to rain and snow illustrated corresponding losses based on the level of precipitation on the road. All model outcomes were translated into an Excel spreadsheet that can be used to predict the range of a generic EV over Kansas-centric roads.
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Koju, Surya Man, and Nikil Thapa. "FPGA Based Vehicle to Vehicle Communication in Spartan 3E." Journal of Science and Engineering 8 (November 12, 2020): 14–21. http://dx.doi.org/10.3126/jsce.v8i0.32858.
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This paper presents economic and reconfigurable RF based wireless communication at 2.4 GHz between two vehicles. It implements digital VLSI using two Spartan 3E FPGAs, where one vehicle receives the information of another vehicle and shares its own information to another vehicle. The information includes vehicle’s speed, location, heading and its operation, such as braking status and turning status. It implements autonomous vehicle technology. In this work, FPGA is used as central signal processing unit which is interfaced with two microcontrollers (ATmega328P). Microcontroller-1 is interfaced with compass module, GPS module, DF Player mini and nRF24L01 module. This microcontroller determines the relative position and the relative heading as seen from one vehicle to another. Microcontroller-2 is used to measure the speed of vehicle digitally. The resulting data from these microcontrollers are transmitted separately and serially through UART interface to FPGA. At FPGA, different signal processing such as speed comparison, turn comparison, distance range measurement and vehicle operation processing, are carried out to generate the voice announcement command, warning signals, event signals, and such outputs are utilized to warn drivers about potential accidents and prevent crashes before event happens.
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Lee, Seung-Mok. "Ultrawideband (UWB)-based precise short-range localization for wireless power transfer to electric vehicles in parking environments." PeerJ Computer Science 7 (May 27, 2021): e567. http://dx.doi.org/10.7717/peerj-cs.567.
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As the necessity of wireless charging to support the popularization of electric vehicles (EVs) emerges, the development of a wireless power transfer (WPT) system for EV wireless charging is rapidly progressing. The WPT system requires alignment between the transmitter coils installed on the parking lot floor and the receiver coils in the vehicle. To automatically align the two sets of coils, the WPT system needs a localization technology that can precisely estimate the vehicle’s pose in real time. This paper proposes a novel short-range precise localization method based on ultrawideband (UWB) modules for application to WPT systems. The UWB module is widely used as a localization sensor because it has a high accuracy while using low power. In this paper, the minimum number of UWB modules consisting of two UWB anchors and two UWB tags that can determine the vehicle’s pose is derived through mathematical analysis. The proposed localization algorithm determines the vehicle’s initial pose by globally optimizing the collected UWB distance measurements and estimates the vehicle’s pose by fusing the vehicle’s wheel odometry data and the UWB distance measurements. To verify the performance of the proposed UWB-based localization method, we perform various simulations and real vehicle-based experiments.
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Armenta-Déu, Carlos, and Erwan Cattin. "Real Driving Range in Electric Vehicles: Influence on Fuel Consumption and Carbon Emissions." World Electric Vehicle Journal 12, no. 4 (September 26, 2021): 166. http://dx.doi.org/10.3390/wevj12040166.
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This paper is focused on the determination of real driving ranges for electric vehicles (EV’s) and how it influences fuel consumption and carbon emissions. A precise method to evaluate the driving range of an EV can establish the correct reduction in GEI amount, mainly CO and CO2, ejected to the environment. The comparison of the daily driving range between an internal combustion engine (ICE) vehicle and an EV provides a useful tool for determining actual fuel saved during a daily trip and a method to compute carbon emissions saved depending on the type of ICE vehicle. Real driving range has been estimated on the basis of a daily trip consisting of five different segments, acceleration, deceleration, constant speed, ascent and descent, which reproduce the different types of driving. The modelling has been developed for urban routes since they are the most common and the most polluted environment where the use of electric vehicles is applied. The effects of types of driving have been taken into account for the calculation of the driving range by considering three main types of driving: aggressive, normal and moderate. The types of vehicle in terms of shape and size as well as dynamic conditions and the types of roads have also been considered for the determination of the driving range. Specific software has been developed to predict electric vehicle range under real driving conditions as a function of the characteristic parameters of a daily trip.
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Hwang, Jenn-Jiang, Jia-Sheng Hu, and Chih-Hong Lin. "A Novel Range-Extended Strategy for Fuel Cell/Battery Electric Vehicles." Scientific World Journal 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/363094.
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The range-extended electric vehicle is proposed to improve the range anxiety drivers have of electric vehicles. Conventionally, a gasoline/diesel generator increases the range of an electric vehicle. Due to the zero-CO2emission stipulations, utilizing fuel cells as generators raises concerns in society. This paper presents a novel charging strategy for fuel cell/battery electric vehicles. In comparison to the conventional switch control, a fuzzy control approach is employed to enhance the battery’s state of charge (SOC). This approach improves the quick loss problem of the system’s SOC and thus can achieve an extended driving range. Smooth steering experience and range extension are the main indexes for development of fuzzy rules, which are mainly based on the energy management in the urban driving model. Evaluation of the entire control system is performed by simulation, which demonstrates its effectiveness and feasibility.
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Phatak, Jyothi P., L. Venkatesha, and C. S. Raviprasad. "Driving cycle based battery rating selection and range analysis in EV applications." International Journal of Power Electronics and Drive Systems (IJPEDS) 12, no. 2 (June 1, 2021): 637. http://dx.doi.org/10.11591/ijpeds.v12.i2.pp637-649.
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<p>The energy consumption of electric vehicles (EVs)depends on traffic environment, terrain, resistive forces acting on vehicle, vehicle characteristics and driving habits of driver. The battery pack in EV is the main energy storage element and the energy capacity determines the range of vehicle. This paper discusses the behavior of battery when EV is subjected to different driving environments such as urban and highway. The battery rating is selected based on requirement of driving cycle. The MATLAB/Simulink model of battery energy storage system (BESS) consisting of battery, bidirectional DC/DCconverter and electric propulsion system is built. The simulation is carried out and the performance of BESS is tested for standard driving cycles which emulate actual driving situations. It has been shown that, the amount of the energy recovered by battery during deceleration depends on the amount of regenerative energy available in the driving cycle. If the battery recovers more energy during deceleration, the effective energy consumed by it reduces and the range of the vehicle increases.</p>
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Greene, David L. "Estimating daily vehicle usage distributions and the implications for limited-range vehicles." Transportation Research Part B: Methodological 19, no. 4 (August 1985): 347–58. http://dx.doi.org/10.1016/0191-2615(85)90041-4.
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Mendjargal, Tulga, Eiji Yamasue, and Hiroki Tanikawa. "Estimation of the Lifespan of Imported Passenger Vehicles in Mongolia." Sustainability 14, no. 21 (November 6, 2022): 14582. http://dx.doi.org/10.3390/su142114582.
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In the last few decades, there has been an increase in second-hand imported vehicles in developing countries, including Mongolia. However, the extension of vehicle lifespans abroad promotes circular economy activities. In this study, we investigated the lifespan of second-hand imported passenger vehicles and their implication for the future sustainability of the transportation sector in Mongolia. The methodology used in this study comprised three stages. First, we conducted surveys to investigate the trends in second-hand vehicles in Mongolia. Next, the results from the survey on passenger vehicles were classified into three major categories based on their mode of operation, namely fuel, liquefied gas petroleum (gas), and the hybrid engine vehicle (HV) (of which the Toyota Prius is the most used vehicle in Mongolia). Finally, we estimated the average lifespan of vehicles using the Weibull distribution to measure before and after the import. The results show that the total average lifespans of all vehicles range between 17.3 and 20.2 years, respectively. The results highlight the different shape parameters of each vehicle category (fuel, gas, and HV), providing a better understanding of each vehicle’s lifespan and providing insights on the future management of second-hand imported vehicles, lifecycles, and recycling potentials for the successful development of sustainable transport policies in Mongolia.
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Ewert, Ricardo, Kai Martins-Turner, Carina Thaller, and Kai Nagel. "Using a Route-based and Vehicle Type specific Range Constraint for Improving Vehicle Routing Problems with Electric Vehicles." Transportation Research Procedia 52 (2021): 517–24. http://dx.doi.org/10.1016/j.trpro.2021.01.061.
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Cannavacciuolo, Gianmatteo, Claudio Maino, Daniela Anna Misul, and Ezio Spessa. "A Model for the Estimation of the Residual Driving Range of Battery Electric Vehicles Including Battery Ageing, Thermal Effects and Auxiliaries." Applied Sciences 11, no. 19 (October 8, 2021): 9316. http://dx.doi.org/10.3390/app11199316.
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Sustainable mobility has recently become a priority of research for on-road vehicles. Shifting towards vehicle electrification is one of the most promising solutions concerning the reduction in pollutant emissions and greenhouse gases, especially for urban areas. Nevertheless, battery electric vehicles might carry substantial limitations compared with other technologies. Specifically, the electric range could be highly affected by the ageing process, non-optimal thermal management of the battery and cabin conditioning. In this paper, a model for the estimation of the residual range of electric vehicles is proposed accounting for the influence of battery state of health, battery pack temperature, power consumption of the main vehicle auxiliaries, and battery pre-heating on the residual driving range. The results of the model application to an L7 battery electric vehicle highlighted that the electric range can be highly affected by several factors related to real-world driving conditions and can consistently differ from nominal values.
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Kawabata, Kuniaki, Daisuke Itoh, Yasushi Hada, Daisuke Chugo, Hayato Kaetsu, and Hajime Asama. "Self-Localization Method Utilizing Environment-Embedded Information and Range Sensory Information." Journal of Robotics and Mechatronics 18, no. 2 (April 20, 2006): 131–38. http://dx.doi.org/10.20965/jrm.2006.p0131.
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In this current research, we are developing an automatic navigation system for outdoor vehicles. Especially, in this paper we propose self-localization method based on the information stored in Information Assistant (IA) devices and range sensor information. IA is a sort of electronics device with wireless communication function based on RF-ID and stored local environment map. The vehicle reads reference data from distributed IAs in the environment and compares such data and scanning range data by using Laser Range Finder (LRF). A probabilistic calculation is introduced to match the sensory information and environment-embedded information. We had the experiment for verifying the validity of our localization method using outdoor vehicle.
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Shroff, Surbhi R. "Review on Electric Vehicle." International Journal for Research in Applied Science and Engineering Technology 10, no. 1 (January 31, 2022): 1667–70. http://dx.doi.org/10.22214/ijraset.2022.40095.
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Abstract: Due to the problems caused by the gasoline engine on the environment and people, the automotive industry has turned to the electrical powered vehicle. This report explains how an electric vehicle works and compares the electric vehicle to the internal combustion engine and hybrid vehicle. The report provides some of the advantages and disadvantages of the electric vehicle. At a time when the fuel prices are rocketing sky high , the daily running cost of a vehicle and its cost of ownership are hitting the roof and there is a dire need to protect our environment , alternative means of transport are few . Electric vehicle are slow expensive with limited range the solution comes in the form of electrical vehicle . Keywords: Plug in hybrid electric vehicles, Energy management System Electric Vehicles, Energy transmission, Battery technology.
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Hung, Yi Hsuan, Chien Hsun Wu, Chun Ying Lin, and Yu Ming Tung. "System Dynamics Analysis and Mode-Switch Control for a 3-Mode Range-Extender Electric Vehicle." Applied Mechanics and Materials 459 (October 2013): 361–67. http://dx.doi.org/10.4028/www.scientific.net/amm.459.361.
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This paper studies the system modeling and mode-switch control for a novel 3-mode (serial/parallel/pure electric) range-extender electric vehicle (REEV). The REEV is modeled with low-order dynamics of 8 subsystems: the driving pattern, drivers behavior, lithium batteries, a spark-ignition engine, a traction motor, a generator, a 6-speed transmission, and a longitudinal vehicle dynamics. Dynamics of the REEV is the integration of above subsystems. To properly evaluate the system performance of the REEV, a rule-based mode-switch control rule is designed with 7 operation modes (System Ready, EV, Serial, Coast Down, Coast-Down Regen., Idle Regen., Parallel). By applying the control rules for the 3-mode REEV, the vehicle can properly operate. Simulation is conducted on the Matlab/Simulink platform. The results show that this study details the system dynamics of subsystems and the vehicle. Meanwhile the rule-based control strategy governs the subsystems well. The developed simulator can be utilized for specification designs of real vehicles and for vehicle control unit designs in the near future.
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Figenbaum, Erik, and Christian Weber. "Estimating Real-World Emissions of PHEVs in Norway by Combining Laboratory Measurement with User Surveys." World Electric Vehicle Journal 9, no. 2 (August 10, 2018): 31. http://dx.doi.org/10.3390/wevj9020031.
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The paper presents the results of experimental testing of the exhaust emission and energy consumption of two gasoline plug-in hybrid vehicles in an emission testing laboratory with different drive cycles and drive modes and at summer and winter temperatures. One was a compact vehicle with a type approval electric mode range of 50 km, the other a mid-sized vehicle with an electric mode range of 31 km. Additionally, an online survey of 2065 private plug-in hybrid vehicles (PHEV) owners investigated the usage pattern of the vehicles. Combining the laboratory tests with the user survey results provided an estimate for the reduction of CO2-emission of PHEVs in use in Norway. The main conclusion is that the PHEV is a vehicle type that needs to match well with the use pattern to produce low CO2- and local emissions. The achievable CO2-emission reduction was proportional to the range in electric drive-mode (E-mode), i.e., 50 km range resulted in about 50% reduction.
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G. S. Naganathan, S. Selvaperumal, R. Nagarajan, and P. Nedumal Pugazhenthi. "Electric Bike Range Estimation using Fuzzy Logic Controller." December 2022 4, no. 4 (November 30, 2022): 225–36. http://dx.doi.org/10.36548/jei.2022.4.002.
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Electric Vehicles (EV) are the prompt solution to significantly lowering the use of fossil fuels and CO2 emissions from the transport industry. There is a continuing growth in the number of EVs in use, but their huge acceptance by customers is associated to the quality they can provide. Nowadays, different types of electric vehicles are moving toward green awareness, and one among them is the electric motorcycle which is a considerable vehicle in India. Though there are many benefits of driving electric motorcycles, because of the limited driving range and inadequate charging stations, it is still not generally accepted in the industry. Range anxiety is the major market concern that is solved by the implementation of an additional range estimating technique that can ease the "range anxiety" caused by the restricted range of EVs. Therefore, this paper proposes a fuzzy logic controller model for the estimation of the EV range based on the battery's state of charge and the load's power usage. In this work, the load power consumption of the vehicle and the status of the battery charge are selected as inputs and the EV range is selected as a Fuzzy Logic Controller output. This model is implemented in the Matlab/Simulink environment.
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Zhu, Guoming G., and Chengsheng Miao. "Real-Time Co-optimization of Vehicle Route and Speed Using Generic Algorithm for Improved Fuel Economy." Mechanical Engineering 141, no. 03 (March 1, 2019): S08—S15. http://dx.doi.org/10.1115/1.2019-mar-4.
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Making future vehicles intelligent with improved fuel economy and satisfactory emissions are the main drivers for current vehicle research and development. The connected and autonomous vehicles still need years or decades to be widely used in practice. However, some advanced technologies have been developed and deployed for the conventional vehicles to improve the vehicle performance and safety, such as adaptive cruise control (ACC), automatic parking, automatic lane keeping, active safety, super cruise, and so on. On the other hand, the vehicle propulsion system technologies, such as clean and high efficiency combustion, hybrid electric vehicle (HEV), and electric vehicle, are continuously advancing to improve fuel economy with satisfactory emissions for traditional internal combustion engine powered and hybrid electric vehicles or to increase cruise range for electric vehicles.
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Widartono, B. S., T. H. Purwanto, and S. T. V. Andi. "Long range unmanned aerial vehicles simple method for monitoring and mapping." IOP Conference Series: Earth and Environmental Science 1039, no. 1 (September 1, 2022): 012051. http://dx.doi.org/10.1088/1755-1315/1039/1/012051.
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Abstract Remote monitoring is the solution and is also widely used to many problems that rely on surveys that require speed of information such as disaster, security, health, environment, and many more. Sensor images obtained from aerial imagery will provide an overview of a broad area with relatively reliable results. Remote monitoring is often constrained by various system devices that exist on unmanned vehicles. The development of simple techniques can increase the accessibility of vehicles in remote areas by chain-control so that field and system limitations can be overcome by developing this technique. The aims of this research are 1) to modify the vehicle system so that its cruising range and monitoring can be increased; 2) to conduct a study on the results of trials of cruising power enhancement techniques. The method that will be used is the chain-control technique so that the control of the vehicle for monitoring (aerial photography) can be carried out by a multi-operator.
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Yang, Yi, Guimei Cao, Ge Zhang, and Shiyun Xie. "Wireless Power Transfer Positioning System with Wide Range Direction-Guided Based on Symmetrical Triple-U Auxiliary Pad." World Electric Vehicle Journal 13, no. 8 (August 1, 2022): 140. http://dx.doi.org/10.3390/wevj13080140.
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An important area of research in electric vehicle wireless power transfer systems is the detection of the secondary pad, which is vital evidence to determine whether the vehicle is in the effective charging area. However, the detection based on sensors mostly will reconstruct the vehicle structure and has a limit on versatility in all kinds of vehicles and the applicability of magnetic couplers and the influence on the primary pad. Therefore, an auxiliary pad structure and corresponding positioning method for offset estimation utilizing the existing inverter and secondary pad in the vehicle system are proposed. Firstly, to satisfy the needs of different positioning heights and avoid the effect on the primary pad, a triple-U positioning auxiliary pad is designed to assist positioning. Secondly, the direction-guided trajectory and detection algorithm are proposed to modify the vehicle location in real-time after analyzing the corresponding equivalent mutual inductance feature trajectory, according to the magnetic field characteristics of various typical magnetic couplers intervened by the proposed triple-U auxiliary pad. Finally, a prototype system is built to validate the applicability and feasibility of the triple-U auxiliary pad, where the positioning accuracy is within 10 mm, and the maximum recognizable recognition range can reach 300 mm × 300 mm, and the direction-guided trajectory is accurate, which can satisfy the actual positioning requirements of electric vehicles.
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Wiebe, Wilhelm, Thomas v. Unwerth, and Sven Schmitz. "Hydrogen pump for hydrogen recirculation in fuel cell vehicles." E3S Web of Conferences 155 (2020): 01001. http://dx.doi.org/10.1051/e3sconf/202015501001.
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A promising alternative to fossil-fuelled vehicles are battery-powered vehicles and fuel cell (FC) vehicles. The major differences between fuel cell and battery-powered vehicles are the range and refuelling times of each vehicle type. With a hydrogen (Hed vehicles are the range and refuelling times of each vehicle type. With a hydrogen (H2) fuelling time of approx. 5 minutes it is possible to cover a distance of up to 800 km with a fuel cell vehicle. These properties make a fuel cell vehicle comparable to a fossil fuel powered vehicle. Furthermore, due to short fuelling times and long range capabilities, fuel cell vehicles are more suitable for long-distance, trucking and agriculture than battery-powered vehicles. The aim of current research is to increase the profitability of fuel cells by reducing costs and improving performance. To ensure a high performance of the fuel cell stack, more hydrogen is supplied to the stack than is needed for the reaction. Therefore, unused hydrogen is pumped back to the anode inlet of the FC-stack using a jet pump or a recirculation blower. In this study, the application of an electrochemical compressor or hydrogen pump (HP) for hydrogen recirculation is suggested. The hydrogen pump is an innovative H2 transport technology with the additional functions of compression and purification in the recirculation system. Hydrogen pumps are very efficient compared to mechanical compressors due to the almost isothermal conditions they operate under. Furthermore, due to the modular design, hydrogen compressors can utilize a minimal amount of space in vehicles.
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Wei, Tongchuan, and H. Christopher Frey. "Evaluation of the Precision and Accuracy of Cycle-Average Light Duty Gasoline Vehicles Tailpipe Emission Rates Predicted by Modal Models." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 7 (June 17, 2020): 566–84. http://dx.doi.org/10.1177/0361198120924006.
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A vehicle specific power (VSP) modal model and the MOtor Vehicle Emission Simulator (MOVES) Operating Mode (OpMode) model have been used to evaluate and quantify the fuel use and emission rates (FUERs) for on-road vehicles. These models bin second-by-second FUERs based on factors such as VSP, speed, and others. The validity of binning approaches depends on their precision and accuracy in predicting variability in cycle-average emission rates (CAERs). The objective is to quantify the precision and accuracy of the two modeling methods. Since 2008, North Carolina State University has used portable emission measurement systems to measure tailpipe emission rates for 214 light duty gasoline vehicles on 1,677 driving cycles, including 839 outbound cycles and 838 inbound cycles on the same routes. These vehicles represent a wide range of characteristics and emission standards. For each vehicle, the models were calibrated based on outbound cycles and were validated based on inbound cycles. The goodness-of-fit of the calibrated models was assessed using linear least squares regression without intercept between model-predicted versus empirical CAERs for individual vehicles. Based on model calibration and validation, the coefficients of determination ( R2) typically range from 0.60 to 0.97 depending on the vehicle group and pollutant, indicating moderate to high precision, with precision typically higher for higher-emitting vehicle groups. The slopes of parity plots for each vehicle group and all vehicles typically range from 0.90 to 1.10, indicating good accuracy. The two modeling approaches are similar to each other at the microscopic and macroscopic levels.
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Herrera, Erika M., Javier Panadero, Patricia Carracedo, Angel A. Juan, and Elena Perez-Bernabeu. "Determining Reliable Solutions for the Team Orienteering Problem with Probabilistic Delays." Mathematics 10, no. 20 (October 14, 2022): 3788. http://dx.doi.org/10.3390/math10203788.
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In the team orienteering problem, a fixed fleet of vehicles departs from an origin depot towards a destination, and each vehicle has to visit nodes along its route in order to collect rewards. Typically, the maximum distance that each vehicle can cover is limited. Alternatively, there is a threshold for the maximum time a vehicle can employ before reaching its destination. Due to this driving range constraint, not all potential nodes offering rewards can be visited. Hence, the typical goal is to maximize the total reward collected without exceeding the vehicle’s capacity. The TOP can be used to model operations related to fleets of unmanned aerial vehicles, road electric vehicles with limited driving range, or ride-sharing operations in which the vehicle has to reach its destination on or before a certain deadline. However, in some realistic scenarios, travel times are better modeled as random variables, which introduce additional challenges into the problem. This paper analyzes a stochastic version of the team orienteering problem in which random delays are considered. Being a stochastic environment, we are interested in generating solutions with a high expected reward that, at the same time, are highly reliable (i.e., offer a high probability of not suffering any route delay larger than a user-defined threshold). In order to tackle this stochastic optimization problem, which contains a probabilistic constraint on the random delays, we propose an extended simheuristic algorithm that also employs concepts from reliability analysis.
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Liu, Hanwu, Yulong Lei, Yao Fu, and Xingzhong Li. "Parameter matching and optimization for power system of range-extended electric vehicle based on requirements." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 234, no. 14 (July 7, 2020): 3316–28. http://dx.doi.org/10.1177/0954407020936781.
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For the research on crucial technologies of range-extended electric vehicle, the first problem to be solved is parameter matching and efficiency optimization for range-extended electric vehicle power and transmission system. Parameter matching and optimization of range-extended electric vehicle power and transmission system are multi-objective optimization problem. Evaluation and analysis of multi-objective optimization problem should be mutually independent and balanced. With the aim of guaranteeing vehicle’s comprehensive performance, a parameter matching and optimization method for range-extended electric vehicle power and transmission system is proposed in this paper. First, the house of quality model of range-extended electric vehicle is established to determine weight coefficient of vehicle performance indicator based on market requirements instead of experience. Based on co-simulation control model which is established in Matlab-Simulink and AVL-Cruise, 40 groups of orthogonal tests are performed, and the sensitivity of characteristic parameters is analyzed to explore the coupling law among vehicle performance indicators, so as to clarify the entry point for parameter matching and optimization. The simulation results show that the characteristic parameters not only have a significant influence but also have a coupling effect on the vehicle performance indicators. The analysis of variance shows that there is a limitation in optimal level combination of various factors only by range. Then, particle swarm optimization algorithm is selected to optimize the parameters of range-extended electric vehicle power and transmission system based on sensitivity analysis results obtained above. The study reveals that it is more efficient and reasonable to match the range-extended electric vehicle power and transmission system with a smaller battery capacity and a “medium-sized” auxiliary power unit which can achieve adequate dynamic performance, lower purchase cost, longer driving range and less energy consumption. Finally, a comparative simulation between the range-based analysis and particle swarm optimization-based analysis is conducted, the simulation results indicate that the optimized design parameters solution can significantly improve the technical indicators of the vehicle.
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HUANG, Luoyi, Jiao YAO, Wei WU, and Xiaoguang YANG. "Feasibility Analysis of Vehicle-to-vehicle Communication on Suburban Road." PROMET - Traffic&Transportation 25, no. 5 (October 27, 2013): 483–93. http://dx.doi.org/10.7307/ptt.v25i5.446.
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With the evolution of advanced wireless communication technologies, tremendous efforts have been invested in vehicular networking, particularly the construction of a vehicle-to-vehicle communication system that supports high speed and mobility. In vehicle-to-vehicle communication environment, vehicles constantly exchange information using wireless technology. This paper aims to propose a vehicle-to-vehicle communication system and validate the feasibility of the system on a suburban road in China. Two vehicles were used equipped with IEEE 802.11p based DSRC (Dedicated Short Range Communications) device to construct a vehicle-to-vehicle communication platform. The system architecture consisting of hardware and software was described in details. Then, communication characteristics such as RSSI (Received Signal Strength Indicator), latency and PLR (packet loss rate) were analyzed. Additionally, GPS-related information (such as ground speed and location) was obtained through field test on a suburban road in Shanghai and Taicang City. The test results demonstrate satisfactory performance of the proposed system.
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Shokravi, Hoofar, Hooman Shokravi, Norhisham Bakhary, Mahshid Heidarrezaei, Seyed Saeid Rahimian Koloor, and Michal Petrů. "A Review on Vehicle Classification and Potential Use of Smart Vehicle-Assisted Techniques." Sensors 20, no. 11 (June 8, 2020): 3274. http://dx.doi.org/10.3390/s20113274.
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Vehicle classification (VC) is an underlying approach in an intelligent transportation system and is widely used in various applications like the monitoring of traffic flow, automated parking systems, and security enforcement. The existing VC methods generally have a local nature and can classify the vehicles if the target vehicle passes through fixed sensors, passes through the short-range coverage monitoring area, or a hybrid of these methods. Using global positioning system (GPS) can provide reliable global information regarding kinematic characteristics; however, the methods lack information about the physical parameter of vehicles. Furthermore, in the available studies, smartphone or portable GPS apparatuses are used as the source of the extraction vehicle’s kinematic characteristics, which are not dependable for the tracking and classification of vehicles in real time. To deal with the limitation of the available VC methods, potential global methods to identify physical and kinematic characteristics in real time states are investigated. Vehicular Ad Hoc Networks (VANETs) are networks of intelligent interconnected vehicles that can provide traffic parameters such as type, velocity, direction, and position of each vehicle in a real time manner. In this study, VANETs are introduced for VC and their capabilities, which can be used for the above purpose, are presented from the available literature. To the best of the authors’ knowledge, this is the first study that introduces VANETs for VC purposes. Finally, a comparison is conducted that shows that VANETs outperform the conventional techniques.
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Jo, Hanghun, and Heungsoon Kim. "Developing a Traffic Model to Estimate Vehicle Emissions: An Application in Seoul, Korea." Sustainability 13, no. 17 (August 30, 2021): 9761. http://dx.doi.org/10.3390/su13179761.
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In this study, a traffic demand model was created based on a simulation network, and another model was built to calculate exhaust-gas emissions generated by vehicles based on the emission function. Subsequently, emissions for three scenarios were analyzed based on the traffic restriction policy according to the vehicle grading system implemented in Seoul. According to the results of the analysis, emission reduction under the vehicle restriction policy was the highest among passenger cars in the low-speed range, while the emissions of cargo trucks in the high-speed range were found to be high. The emissions showed a high ratio of carbon monoxide and nitrogen oxides, and high emissions were generated from liquefied petroleum gas and diesel vehicles. Furthermore, the effects of vehicle restriction policy were confirmed to reduce emissions from diesel and other vehicle types. Using the established model, we were able to confirm that the vehicle restriction policy contributed to the improvement of air quality. Furthermore, the diesel vehicle restriction policy also had an impact on reducing the emissions of vehicle types other than those using diesel.