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Статті в журналах з теми "Complex parallel hybrid vehicle"
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Vu, Trieu Minh, Reza Moezzi, Jindrich Cyrus, Jaroslav Hlava, and Michal Petru. "Automatic Clutch Engagement Control for Parallel Hybrid Electric Vehicle." Energies 14, no. 21 (November 3, 2021): 7256. http://dx.doi.org/10.3390/en14217256.
Повний текст джерелаАнотація:
Automatic clutch engagement control is essential for all kinds of vehicle power transmissions. The controllers for vehicle power transmissions may include model-based or model-free approaches and must provide high transmission efficiency, fast engagement and low jerk. Most vehicle automatic transmissions are using torque converters with transmission efficiencies up to 96%. This paper presents the use of fuzzy logic control for a dry clutch in parallel hybrid electric vehicles. This controller can minimize the loss of power transmission since it can offer a higher transmission efficiency, up to 99%, with faster engagement, lower jerk and, thus, higher driving comfortability with lower cost. Fuzzy logic control is one of the model-free schemes. It can be combined with AI algorithms, neuro networks and virtual reality technologies in future development. Fuzzy logic control can avoid the complex modelling while maintaining the system’s high stability amid uncertainties and imprecise information. Experiments show that fuzzy logic can reduce the clutch slip and vibration. The new system provides 2% faster engagement speed than the torque converter and eliminates 70% of noise and vibration less than the manual transmission clutch.
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Maddumage, W. U., K. Y. Abeyasighe, M. S. M. Perera, R. A. Attalage, and P. Kelly. "Comparing Fuel Consumption and Emission Levels of Hybrid Powertrain Configurations and a Conventional Powertrain in Varied Drive Cycles and Degree of Hybridization." Science & Technique 19, no. 1 (February 5, 2020): 20–33. http://dx.doi.org/10.21122/2227-1031-2020-19-1-20-33.
Повний текст джерелаАнотація:
Hybrid electric powertrains in automotive applications aim to improve emissions and fuel economy with respect to conventional internal combustion engine vehicles. Variety of design scenarios need to be addressed in designing a hybrid electric vehicle to achieve desired design objectives such as fuel consumption and exhaust gas emissions. The work in this paper presents an analysis of the design objectives for an automobile powertrain with respect to different design scenarios, i. e. target drive cycle and degree of hybridization. Toward these ends, four powertrain configuration models (i. e. internal combustion engine, series, parallel and complex hybrid powertrain configurations) of a small vehicle (motorized three wheeler) are developed using Model Advisor software and simulated with varied drive cycles and degrees of hybridization. Firstly, the impact of vehicle power control strategy and operational characteristics of the different powertrain configurations are investigated with respect to exhaust gas emissions and fuel consumption. Secondly, the drive cycles are scaled according to kinetic intensity and the relationship between fuel consumption and drive cycles is assessed. Thirdly, three fuel consumption models are developed so that fuel consumption values for a real-world drive cycle may be predicted in regard to each powertrain configuration. The results show that when compared with a conventional powertrain fuel consumption is lower in hybrid vehicles. This work led to the surprisingly result showing higher CO emission levels with hybrid vehicles. Furthermore, fuel consumption of all four powertrains showed a strong correlation with kinetic intensity values of selected drive cycles. It was found that with varied drive cycles the average fuel advantage for each was: series 23 %, parallel 21 %, and complex hybrids 33 %, compared to an IC engine powertrain. The study reveals that performance of hybrid configurations vary significantly with drive cycle and degree of hybridization. The paper also suggests future areas of study.
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Roberge, Vincent, and Mohammed Tarbouchi. "Parallel Hybrid 2-Opt Flower Pollination Algorithm for Real-Time UAV Trajectory Planning on GPU." ITM Web of Conferences 48 (2022): 03007. http://dx.doi.org/10.1051/itmconf/20224803007.
Повний текст джерелаАнотація:
Abstract. The development of autonomous Unmanned Aerial Vehicles (UAVs) is a priority to many civilian and military organizations. An essential aspect of UAV autonomy is the ability for automatic trajectory planning. In this paper, we use a parallel Flower Pollination Algorithm (FPA) to deal with the problem's complexity and compute feasible and quasi-optimal trajectories for fixed-wing UAVs in complex 3D environments, taking into account the vehicle's flight properties. The global optimization algorithm is improved with the addition of 2-opt local search providing a significant improvement. The proposed trajectory planner in implemented and parallelized on a multicore processor (CPU) using OpenMP and a Graphics Processing Unit (GPU) using CUDA resulting in a 9.6x and a 68.5x speedup respectively compared to the sequential implementation on CPU. Index Terms—Flower Pollination Algorithm, Graphics Processing Unit, Parallel Programming, Trajectory Planning, Unmanned Aerial Vehicle.
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Finesso, Roberto, Ezio Spessa, and Mattia Venditti. "Layout design and energetic analysis of a complex diesel parallel hybrid electric vehicle." Applied Energy 134 (December 2014): 573–88. http://dx.doi.org/10.1016/j.apenergy.2014.08.007.
Повний текст джерела
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Toman, Rastislav, and Mikuláš Adámek. "Complex Evaluation of Heavy-Duty Truck Hybridization and Electrification Options." Strojnícky časopis - Journal of Mechanical Engineering 72, no. 3 (November 1, 2022): 97–112. http://dx.doi.org/10.2478/scjme-2022-0044.
Повний текст джерелаАнотація:
Abstract Parallel hybrid electric vehicle (HEV) powertrain topologies are easily applicable on an existing conventional powertrain, and are frequently used in passenger vehicles, with a goal to reduce the overall fleet CO2 emissions, either with mild, full, or plug-in capability. However, for the heavy-duty trucks, the powertrain electrification progresses more slowly. Therefore, the goal of this paper is to evaluate three different hybridization options, together with two electrification options, in comparison with conventional powertrain combined with 5.9 L 6-cylinder diesel internal combustion engine in a heavy-duty 7.5-ton application. All vehicle variants are evaluated in eight vehicle driving cycles replicating different heavy-duty use-cases at different cargo levels, also considering the economical aspect of these different electrification options, calculating the payback periods for each powertrain option. The energy management control strategy, that determines the power split between the ICE and electric motor for HEV variants is an optimal one, based on Pontryagin’s Minimum Principle. All models are programmed in-house in Python 3.9.0.
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Zheng, Wei, Qian Fan Zhang, and Shu Mei Cui. "Research on the Dynamic Performance and Parameter Design of Parallel Hybrid Electric Vehicle." Advanced Materials Research 108-111 (May 2010): 613–18. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.613.
Повний текст джерелаАнотація:
According to the Parallel Hybrid Electric Vehicle (PHEV) demands on powertrain systems, the dynamic models of PHEV are built in this paper. Base on the analysis of dynamical characteristics of both internal combustion engine (ICE) and electric machine (EM), the dynamic ability and fuel economy performance of PHEV is presented. The paper focuses on the parametric design of powertrain on vehicle performance, which provided the theoretical foundation for PHEV design. The paper also puts forward the control strategy of PHEV during the operating modes switching, which aims to solve the problem of the power distribution between the ICE and electric motor, which can effectively resolve process control problems of the complex PHEV system. By employing the dynamic model and performing MATLAB simulation, the results of simulation are given, which demonstrate that the PHEV improve performance well.
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Stevens, Gary, Juliana Early, Geoff Cunningham, Martin Murtagh, Roy Douglas, and Robert Best. "Multi-fidelity validation algorithm for next generation hybrid-electric vehicle system design." Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 233, no. 13 (January 25, 2019): 3438–48. http://dx.doi.org/10.1177/0954407018825015.
Повний текст джерелаАнотація:
With the evolution of increasingly complex hybrid-electric vehicle powertrains, the process of creating validated system models has become progressively more difficult to achieve. Increasing levels of confidence in how instantaneous vehicle energy states are captured is needed to take full advantage of the fuel consumption and emissions reduction potential of the vehicle to move towards more sustainable transportation systems. While many strategies for model validation exist, the majority rely on ascertaining comparisons with global system characteristics, for instance, total fuel consumption over a fixed driving event. However, these methods do not necessarily account for the rapidly fluctuating energy states which need to be understood to optimise the vehicle’s energy management strategy. The current work proposes a new validation approach which captures these instantaneous characteristics taking advantage of the high signal sampling rates available from modern data acquisition equipment rather than relying on drive cycle average or cumulative global behaviours. The method proposed provides a holistic view of the behaviours demonstrated by the vehicle model and identifies regions of poor system validation targeting areas for further model refinement. The algorithm is demonstrated on a new post-transmission, parallel mild-hybrid-electric bus. The model was developed in the MATLAB Simulink modelling environment. The validation algorithm is tested against vehicle dynamometer and test track data. With an increasing volume of mild and full hybrid vehicle configurations emerging, validation strategies such as the one proposed here are increasingly important for the design of energy management strategies to deliver the full potential benefits of the vehicle. The algorithm is proposed in a step by step method which can be automated to limit required user input.
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Volodarets, M., I. Gritsuk, I. Taran, V. Volkov, M. Bulgakov, and M. Izteleuova. "Features of modernization of a truck with a hybrid power transmission." Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, no. 1 (February 28, 2023): 80–87. http://dx.doi.org/10.33271/nvngu/2023-1/080.
Повний текст джерелаАнотація:
Purpose. Substantiation of peculiarities of modernization of a heavy-duty vehicle with a hybrid power transmission by using the formed set of analytical and technological solutions for power transmission under operating conditions. Methodology. For the developed functional model of a hybrid vehicle operation, the parameters of the functional model and its links are presented, the relationships between the elements are described, and the boundary conditions are formed. A combined series-parallel hybrid drive scheme has been used, as it has a higher efficiency compared to parallel and series ones. When operating in idle mode and low loads, the diesel generator set replenishes the energy reserve in the energy storage device and the vehicle is operated. To recharge the energy storage devices, it is possible to use the traction electric motor as a generator, and during operation it is used in the energy recovery mode during vehicle braking. An optimization mathematical model has been developed to determine the parameters of the power plant and energy storage device, taking into account operating conditions. A procedure has been developed along with, on its basis, a subroutine algorithm for calculating the required energy intensity of the energy storage device and the power of the vehicle’s power plant. An assessment of the modernization effectiveness of mining dump trucks by hybrid power transmission was made. Findings. A functional model of a hybrid vehicle operation under appropriate operating conditions has been developed, and the main parameters limitations of the state have been given. The corresponding procedures and algorithm for calculating the parameters of the energy storage device and the power unit were compiled and then were used in the corresponding computer calculation program. In the study on fuel efficiency, three BelAZ-7547 dump trucks were considered. The values of the kinetic energy configuration were determined with an increase in speed (acceleration) and with a decrease in speed (deceleration). An assessment of the upgrading effectiveness was made for mining trucks with hybrid power transmission. The payback period of the corresponding measures was 1.42 years. Originality. To determine the power storage and power unit parameters, a functional model of a hybrid vehicle operation and an optimization mathematical model for determining the parameters of the power plant and energy storage, taking into account operating conditions, have been developed. The substantiation of a complex of analytical and technological solutions for the power transmission of a hybrid mining dump truck under operating conditions has been carried out. Practical value. The results obtained are useful in the implementation of the modernization of heavy mining dump trucks with hybrid power transmission in the operating conditions.
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Zhong, Biqing, Bin Deng, and Han Zhao. "Simulation Model and Method for Active Torsional Vibration Control of an HEV." Applied Sciences 9, no. 1 (December 22, 2018): 34. http://dx.doi.org/10.3390/app9010034.
Повний текст джерелаАнотація:
Hybrid electric vehicles (HEV) might cause new noise vibration and harshness (NVH) problems, due to their complex powertrain systems. Therefore, in this paper, a new longitudinal dynamic simulation model of a series-parallel hybrid electric bus with an active torsional vibration control module is proposed. First, the schematic diagrams of the simulation model architecture and the active control strategy are given, and the dynamic models of the main components are introduced. Second, taking advantage of the characteristics of hybrid systems, a method of determining the key dynamic parameters by a bench test is proposed. Finally, in a typical bus-driving cycle for Chinese urban conditions, time domain and frequency domain processing methods are used to analyze vehicle body jerk, fluctuation of rotational speed, and torsional angle of the key components. The results show that the active control method can greatly improve the system’s torsional vibration performance when switching modes and at resonance.
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Taghavipour, Amir, and Ali Alipour. "HIL Evaluation of a Novel Real-time Energy Management System for an HEV with a Continuously Variable Transmission." Strojniški vestnik – Journal of Mechanical Engineering 67, no. 4 (April 26, 2021): 142–52. http://dx.doi.org/10.5545/sv-jme.2020.7017.
Повний текст джерелаАнотація:
One of the most important challenges facing automotive engineers is reducing vehicle fuel consumption and improving the drivability index. Modern hybrid electric powertrains play an important role in reducing fuel consumption. Continuously variable transmission (CVT) is an automatic transmission that can change the gear ratio seamlessly using a belt and pulleys. CVT performs with infinite gear ratios. Controlling and determining the optimal gear ratio, especially in a complex hybrid powertrain, is a major challenge. Therefore, a multi-parametric model predictive controller with real-time implementation capability is proposed that can handle the energy management task concurrently with gear shifting strategy in a parallel pre-transmission hybrid electric vehicle. The proposed controller hardware-in-the-loop (HIL) validation procedure on the high-fidelity Autonomie model shows significant improvement in fuel economy while maintaining drivability in three different driving schedules. HIL evaluation guarantees the real-time capability and the proposed controller readiness to be implemented to real-world control hardware.
Дисертації з теми "Complex parallel hybrid vehicle"
1
Kaloun, Adham. "Conception de chaînes de traction hybrides et électriques par optimisation sur cycles routiers." Thesis, Ecole centrale de Lille, 2020. http://www.theses.fr/2020ECLI0019.
Повний текст джерелаАнотація:
La conception des chaînes de traction hybrides est une tâche complexe, qui fait appel à des experts de différents domaines s'appuyant sur des compétences et des outils distincts. En plus de cela, la recherche d'une solution optimale nécessite un retour système. Cela peut être, selon la granularité des modèles de composants, très coûteux en temps de calcul. Ceci est d'autant plus vrai lorsque la performance du système est déterminée par sa commande, comme c'est le cas du véhicule hybride. En fait, différentes possibilités peuvent être sélectionnées pour fournir le couple requis aux roues pendant le cycle de conduite. Ainsi, le principal obstacle est d'atteindre l'optimalité tout en conservant une méthodologie rapide et robuste. Dans ces travaux de thèse, de nouvelles approches visant à exploiter le potentiel complet de l'hybridation sont proposées et comparées. La première stratégie est une approche bi-niveaux composée de deux blocs d'optimisation imbriqués: un processus d'optimisation des paramètres de design externe qui calcule la meilleure valeur de consommation de carburant à chaque itération en se basant sur une version améliorée de la programmation dynamique pour l'optimisation de la commande. Deux stratégies de conception systémique différentes basées sur le schéma itératif sont également proposées. La première approche est basée sur la réduction de modèle tandis que la seconde se repose sur des techniques précises de réduction de cycle. Cette dernière permet l'utilisation de modèles de haute précision sans pénaliser le temps de calcul. Une approche simultanée est ensuite mise en œuvre, qui optimise à la fois les variables de conception et les paramètres d'une nouvelle stratégie efficace à base de règles. Cette dernière permettra une optimisation plus rapide par rapport à l'optimisation directe de toutes les variables de décision. Enfin, une technique basée sur l'utilisation des méta-modèles est exploréeDesigning hybrid powertrains is a complex task, which calls for experts from various fields. In addition to this, finding the optimal solution requires a system overview. This can be, depending on the granularity of the models at the component level, highly time-consuming. This is even more true when the system’s performance is determined by its control, as it is the case of the hybrid powertrain. In fact, various possibilities can be selected to deliver the required torque to the wheels during the driving cycle. Hence, the main obstacle is to achieve optimality while keeping the methodology fast and robust. In this work, novel approaches to exploit the full potential of hybridization are proposed and compared. The first strategy is a bi-level approach consisting of two nested optimization blocks: an external design optimization process that calculates the best fuel consumption value at each iteration, found through control optimization using an improved version of dynamic programming. Two different systemic design strategies based on the iterative scheme are proposed as well. The first approach is based on model reduction while the second approach relies on precise cycle reduction techniques. The latter enables the use of high precision models without penalizing the calculation time. A co-optimization approach is implemented afterwards which adjusts both the design variables and parameters of a new efficient rule-based strategy. This allows for faster optimization as opposed to an all-at-once approach. Finally, a meta-model based technique is explored
2
Kaloun, Adham. "Conception de chaînes de traction hybrides et électriques par optimisation sur cycles routiers." Thesis, Centrale Lille Institut, 2020. http://www.theses.fr/2020CLIL0019.
Повний текст джерелаАнотація:
La conception des chaînes de traction hybrides est une tâche complexe, qui fait appel à des experts de différents domaines s'appuyant sur des compétences et des outils distincts. En plus de cela, la recherche d'une solution optimale nécessite un retour système. Cela peut être, selon la granularité des modèles de composants, très coûteux en temps de calcul. Ceci est d'autant plus vrai lorsque la performance du système est déterminée par sa commande, comme c'est le cas du véhicule hybride. En fait, différentes possibilités peuvent être sélectionnées pour fournir le couple requis aux roues pendant le cycle de conduite. Ainsi, le principal obstacle est d'atteindre l'optimalité tout en conservant une méthodologie rapide et robuste. Dans ces travaux de thèse, de nouvelles approches visant à exploiter le potentiel complet de l'hybridation sont proposées et comparées. La première stratégie est une approche bi-niveaux composée de deux blocs d'optimisation imbriqués: un processus d'optimisation des paramètres de design externe qui calcule la meilleure valeur de consommation de carburant à chaque itération en se basant sur une version améliorée de la programmation dynamique pour l'optimisation de la commande. Deux stratégies de conception systémique différentes basées sur le schéma itératif sont également proposées. La première approche est basée sur la réduction de modèle tandis que la seconde se repose sur des techniques précises de réduction de cycle. Cette dernière permet l'utilisation de modèles de haute précision sans pénaliser le temps de calcul. Une approche simultanée est ensuite mise en œuvre, qui optimise à la fois les variables de conception et les paramètres d'une nouvelle stratégie efficace à base de règles. Cette dernière permettra une optimisation plus rapide par rapport à l'optimisation directe de toutes les variables de décision. Enfin, une technique basée sur l'utilisation des méta-modèles est exploréeDesigning hybrid powertrains is a complex task, which calls for experts from various fields. In addition to this, finding the optimal solution requires a system overview. This can be, depending on the granularity of the models at the component level, highly time-consuming. This is even more true when the system’s performance is determined by its control, as it is the case of the hybrid powertrain. In fact, various possibilities can be selected to deliver the required torque to the wheels during the driving cycle. Hence, the main obstacle is to achieve optimality while keeping the methodology fast and robust. In this work, novel approaches to exploit the full potential of hybridization are proposed and compared. The first strategy is a bi-level approach consisting of two nested optimization blocks: an external design optimization process that calculates the best fuel consumption value at each iteration, found through control optimization using an improved version of dynamic programming. Two different systemic design strategies based on the iterative scheme are proposed as well. The first approach is based on model reduction while the second approach relies on precise cycle reduction techniques. The latter enables the use of high precision models without penalizing the calculation time. A co-optimization approach is implemented afterwards which adjusts both the design variables and parameters of a new efficient rule-based strategy. This allows for faster optimization as opposed to an all-at-once approach. Finally, a meta-model based technique is explored
3
Won, Jong-Seob. "Intelligent energy management agent for a parallel hybrid vehicle." Texas A&M University, 2004. http://hdl.handle.net/1969.1/271.
Повний текст джерелаАнотація:
This dissertation proposes an Intelligent Energy Management Agent (IEMA) for parallel hybrid vehicles. A key concept adopted in the development of an IEMA is based on
the premise that driving environment would affect fuel consumption and pollutant emissions, as well as the operating modes of the vehicle and the driver behavior do. IEMA incorporates a driving
situation identification component whose role is to assess the driving environment, the driving style of the driver, and the operating mode (and trend) of the vehicle using long and short
term statistical features of the drive cycle.
This information is subsequently used by the torque distribution and charge sustenance components of IEMA to determine the power
split strategy, which is shown to lead to improved fuel economy and reduced emissions.
4
Enang, Wisdom. "Robust real-time control of a parallel hybrid electric vehicle." Thesis, University of Bath, 2017. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.720652.
Повний текст джерелаАнотація:
The gradual decline in global oil reserves and the presence of ever so stringent emissions rules around the world have created an urgent need for the production of automobiles with improved fuel economy. HEVs (hybrid electric vehicles) have proved a viable option to guaranteeing improved fuel economy and reduced emissions. The fuel consumption benefits which can be realised when utilising HEV architecture are dependent on how much braking energy is regenerated, and how well the regenerated energy is utilised. The challenge in developing a real-time HEV control strategy lies in the satisfaction of often conflicting control constraints involving fuel consumption, emissions and driveability without over-depleting the battery state of charge at the end of the defined driving cycle. Reviewed literature indicates some research gaps and hence exploitable study areas for which this thesis intends to address. For example, despite the research advances made, HEV energy management is still lacking in several key areas: optimisation of braking energy regeneration; real-time sub-optimal control of HEV for robustness, charge sustenance and fuel reduction; and real-time vehicle speed control. Consequently, this thesis aims to primarily develop novel real-time near-optimal control strategies for a parallel HEV, with a view to achieving robustness, fuel savings and charge sustenance simultaneously, under various levels of obtainable driving information (no route preview information, partial route preview information). Using a validated HEV dynamic simulation model, the following novel formulations are proposed in this thesis and subsequently evaluated in real time: 1. A simple grouping system useful for classifying standard and real-world driving cycles on the basis of aggressivity and road type. 2. A simple and effective near-optimal heuristic control strategy with no access to route preview information. 3. A dynamic programming-inspired real-time near-optimal control strategy with no access to route preview information. 4. An ECMS (Equivalent Consumption Minimisation Strategy) inspired real-time near-optimal control strategy with no access to route preview information. 5. An ECMS-inspired real-time near-optimal control strategy with partial access to route preview information. 6. A dynamic programming based route-optimal vehicle speed control strategy which accounts for real-time dynamic effects like engine braking, while solving an optimisation problem involving the maximisation of fuel savings with little or no penalty to trip time. 7. A real-time vehicle speed control approach, which is based on smoothing the speed trajectory of the lead vehicle, consequently reducing the acceleration and deceleration events that the intelligent vehicle (follower vehicle) will undergo. This smoothing effect translates into reduced fuel consumption, which tends to increase with increasing traffic preview window. Among other studies performed in this thesis, the fuel savings potential of the proposed near-optimal controllers was investigated in real time over standard driving cycles and real-world driving profiles. Results from these analyses show that, over standard driving cycles, properly formulated near-optimal real-time controllers are able to achieve a fuel savings potential within 0.03% to 3.71% of the global optimal performance, without requiring any access to route preview information. It was also shown that as much as 2.44% extra fuel savings could be achieved over a driving route, through the incorporation of route preview information into a real-time controller. Investigations were also made into the real-time fuel savings that could be realised over a driving route, through vehicle speed control. Results from these analyses show that, compared to an HEV technology which comes at a bigger cost, far higher fuel savings, as much as 45.96%, could be achieved through a simple real-time vehicle speed control approach.
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Picot, Nathan M. "A STRATEGY TO BLEND SERIES AND PARALLEL MODES OF OPERATION IN A SERIES-PARALLEL 2-BY-2 HYBRID DIESEL/ELECTRIC VEHICLE." University of Akron / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=akron1189750096.
Повний текст джерела
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Engman, Jimmy. "Model Predictive Control for Series-Parallel Plug-In Hybrid Electrical Vehicle." Thesis, Linköpings universitet, Fordonssystem, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-69608.
Повний текст джерелаАнотація:
The automotive industry is required to deal with increasingly stringent legislationfor greenhouse gases. Hybrid Electric Vehicles, HEV, are gaining acceptance as thefuture path of lower emissions and fuel consumption. The increased complexityof multiple prime movers demand more advanced control systems, where futuredriving conditions also becomes interesting. For a plug-in Hybrid Electric Vehicle,PIHEV, it is important to utilize the comparatively inexpensive electric energybefore the driving cycle is complete, this for minimize the cost of the driving cycle,since the battery in a PIHEV can be charged from the grid. A strategy with lengthinformation of the driving cycle from a global positioning system, GPS, couldreduce the cost of driving. This by starting to blend the electric energy with fuelearlier, a strategy called blended driving accomplish this by distribute the electricenergy, that is charged externally, with fuel over the driving cycle, and also ensurethat the battery’s minimum level reaches before the driving cycle is finished. Astrategy called Charge Depleting Charge Sustaining, CDCS, does not need lengthinformation. This strategy first depletes the battery to a minimum State of Charge,SOC, and after this engages the engine to maintain the SOC at this level. In thisthesis, a variable SOC reference is developed, which is dependent on knowledgeabout the cycle’s length and the current length the vehicle has driven in the cycle.With assistance of a variable SOC reference, is a blended strategy realized. Thisis used to minimize the cost of a driving cycle. A comparison between the blendedstrategy and the CDCS strategy was done, where the CDCS strategy uses a fixedSOC reference. During simulation is the usage of fuel minimized; and the blendedstrategy decreases the cost of the driving missions compared to the CDCS strategy.To solve the energy management problem is a model predictive control used. Thedesigned control system follows the driving cycles, is charge sustaining and solvesthe energy management problem during simulation. The system also handlesmoderate model errors.Fordonsindustrin måste hantera allt strängare lagkrav mot utsläpp av emissioneroch växthusgaser. Hybridfordon har börjat betraktas som den framtida vägenför att ytterligare minska utsläpp och användning av fossila bränslen. Den ökadekomplexiteten från flera olika motorer kräver mera avancerade styrsystem. Begränsningarfrån motorernas energikällor gör att framtida förhållanden är viktigaatt estimera. För plug-in hybridfordon, PIHEV, är det viktigt att använda denvvijämförelsevis billiga elektriska energin innan fordonet har nått fram till slutdestinationen.Batteriets nuvarande energimängd mäts i dess State of Charge, SOC.Genom att utnyttja information om hur långt det är till slutdestinationen från ettGlobal Positioning System, GPS, blandar styrsystemet den elektriska energin medbränsle från början, detta kallas för blandad körning. En strategi som inte hartillgång till hur långt fordonet ska köras kallas Charge Depleting Charge Sustaining,CDCS. Denna strategi använder först energin från batteriet, för att sedanbörja använda förbränningsmotorn när SOC:s miniminivå har nåtts. Strategin attanvända GPS informationen är jämförd med en strategi som inte har tillgång tillinformation om körcykelns längd. Blandad körning använder en variabel SOC referens,till skillnad från CDCS strategin som använder sig av en konstant referenspå SOC:s miniminivå. Den variabla SOC referensen beror på hur långt fordonethar kört av den totala körsträckan, med hjälp av denna realiseras en blandad körning.Från simuleringarna visade det sig att blandad körning gav minskad kostnadför de simulerade körcyklerna jämfört med en CDCS strategi. En modellbaseradprediktionsreglering används för att lösa energifördelningsproblemet. Styrsystemetföljer körcykler och löser energifördelningsproblemet för de olika drivkällorna undersimuleringarna. Styrsystemet hanterar även måttliga modellfel.
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Khan, Bruno Shakou. "Optimization of the fuel consumption of a parallel hybrid electric vehicle." Thesis, Georgia Institute of Technology, 2001. http://hdl.handle.net/1853/16763.
Повний текст джерела
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Boyd, Steven J. "Hybrid Electric Vehicle Control Strategy Based on Power Loss Calculations." Thesis, Virginia Tech, 2006. http://hdl.handle.net/10919/34970.
Повний текст джерелаАнотація:
Defining an operation strategy for a Split Parallel Architecture (SPA) Hybrid Electric Vehicle (HEV) is accomplished through calculating powertrain component losses. The results of these calculations define how the vehicle can decrease fuel consumption while maintaining low vehicle emissions. For a HEV, simply operating the vehicle's engine in its regions of high efficiency does not guarantee the most efficient vehicle operation. The results presented are meant only to define a literal strategy; that is, an understanding as to why the vehicle should operate in a certain way under the given conditions. The literature review gives a background of hybrid vehicle control publications, and without the SPA HEV addressed or a hybrid analysis based on loss calculations between engine only and hybrid modes, there is a need for this paper. Once the REVLSE architecture and components are understood, the hybrid modes are explained. Then the losses for each hybrid mode are calculated, and both the conversion and assist efficiencies are detailed. The conversion efficiency represents the amount of additional fuel required to store a certain amount of energy in the battery, and this marginal efficiency can be higher than peak engine efficiency itself. This allows electric only propulsion to be evaluated against the engine only mode, and at low torques the electric motor is more efficient despite the roundtrip losses of the hybrid system.Master of Science
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Reinsel, Samuel Joseph. "Drive Quality Improvement and Calibration of a Post-Transmission Parallel Hybrid Electric Vehicle." Thesis, Virginia Tech, 2018. http://hdl.handle.net/10919/85046.
Повний текст джерелаАнотація:
The Hybrid Electric Vehicle Team (HEVT) of Virginia Tech is one of 16 university teams participating in EcoCAR 3, the latest competition in the Advanced Vehicle Technology Competitions (AVTC) organized by Argonne National Labs. EcoCAR 3 tasks teams with converting a 2016 Chevrolet Camaro into a hybrid electric vehicle with 5 main goals: reducing petroleum energy use and greenhouse gas emissions while maintaining safety, performance, and consumer acceptability. Over the last 4 years, HEVT has designed and built a plugin parallel hybrid electric vehicle with a unique powertrain architecture. This work deals with utilizing the unique powertrain layout of the HEVT Camaro to improve drive quality, a key component in consumer acceptability. Although there are many ways to approach drive quality, most aspects can be analyzed in the smoothness of the vehicle longitudinal acceleration response.
This research is focused on improving the drive quality of the vehicle developed for EcoCAR 3. Multiple algorithms are developed to address specific aspects of drive quality that can only be done with the powertrain developed. This begins by researching the control strategies used in modern automatic transmissions, and moves into the modeling strategy used to begin algorithm development. Two main strategies are developed and calibrated in the vehicle. The first being a strategy for reducing jerk in pure electric mode by limiting motor torque response. The second strategy aims to improve transmission shift quality by using the electric motor to reduce torque fluctuations at the driveshaft. The energy consumption impact of both of these strategies is also analyzed to ensure that drive quality does not come at the large expense of energy consumption.Master of Science
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Marquez, Brunal Eduardo De Jesus. "Model and Control System Development for a Plug-In Parallel Hybrid Electric Vehicle." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/71388.
Повний текст джерелаАнотація:
The Hybrid Electric Vehicle Team (HEVT) of Virginia Tech is participating in the EcoCAR 3 Advanced Vehicle Technology Competition series organized by Argonne National Labs (ANL), and sponsored by General Motors (GM) and the U.S. Department of Energy (DOE). EcoCAR 3 is a 4-year collegiate competition that challenges student with redesigning a 2016 Chevrolet Camaro into a hybrid. The five main goals of EcoCAR 3 are to reduce petroleum energy use (PEU) and green house gas (GHG) emissions while maintaining safety, consumer acceptability, and performance, with an increased focus on cost and innovation. HEVT selected a P3 Plug-in Parallel hybrid electric vehicle (PHEV) to meet design goals and competition requirements. This study presents different stages of the vehicle development process (VDP) followed to integrate the HEVT Camaro. This work documents the control system development process up to Year 2 of EcoCAR 3.
The modeling process to select a powertrain is the first stage in this research. Several viable powertrains and the respective vehicle technical specifications (VTS) are evaluated. The P3 parallel configuration with a V8 engine is chosen because it generated the set of VTS that best meet design goals and EcoCAR 3 requirements. The V8 engine also preserves the heritage of the Camaro, which is attractive to the established target market. In addition, E85 is chosen as the fuel for the powertrain because of the increased impact it has on GHG emissions compared to E10 and gasoline. The use of advanced methods and techniques like model based design (MBD), and rapid control prototyping (RCP) allow for faster development of engineering products in industry. Using advanced engineering techniques has a tremendous educational value, and these techniques can assist the development of a functional and safe hybrid control system. HEVT has developed models of the selected hybrid powertrain to test the control code developed in software. The strategy developed is a Fuzzy controller for torque management in charge depleting (CD) and charge sustaining (CS) modes. The developed strategy proves to be functional without having a negative impact of the energy consumption characteristics of the hybrid powertrain. Bench testing activities with the V8 engine, a low voltage (LV) motor, and high voltage (HV) battery facilitated learning about communication, safety, and functionality requirements for the three components. Finally, the process for parallel development of models and control code is presented as a way to implement more effective team dynamics.Master of Science
Книги з теми "Complex parallel hybrid vehicle"
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Repole, Donato. Research of Parallel Computing Neuro-fuzzy Networks for Unmanned Vehicles. RTU Press, 2021. http://dx.doi.org/10.7250/9789934226922.
Повний текст джерелаАнотація:
The Doctoral Thesis illustrates the author’s research in the field of VHDL based ‘neuro-fuzzy controllers’. The Thesis examines a novel software tool for the high-level ‘neuro-fuzzy controller’ description capable of executing controller simulations, optimisation tasks, performing learning / training tasks, and exporting the controller in VHDL code. The author introduces a design strategy that is looking for developing solutions for complex controller architecture of mobile robotic vehicles (of any nature) or even for multiple industrial application. This work enables further investigative research into autonomous robotics, particularly into the physical implementation of an autonomous aerial unmanned vehicle from an inexpensive RC plane.
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Drivetrain for Vehicles 2016. VDI Verlag, 2016. http://dx.doi.org/10.51202/9783181022764.
Повний текст джерелаАнотація:
The annual VDI-Congress Drivetrain for Vehicles is the most important meeting-point for the automotive industry regarding transmissions and driveline-technology. Vehicle manufacturers, transmissions suppliers and the whole supply-chain are presenting and discussing latest technology and trends. The future of drivetrain for vehicles will become very exciting. The number of electrified drivetrains will be growing in future. Things will get more complex with a hybrid drive and packages will be much more challenging. Therefore we are keen to find intelligent solutions. Furthermore we will face significant changes. The following megatrends are going to have big impact on future drivelines and on the whole value chain: • more and more challenging regulations to reduce environmental pollution caused by traffic, • the need for electrification of drivetrain in terms of hybrids and electric vehicles, • the understanding of the drivetrain system as an overall approach, • high pressure fo...
Частини книг з теми "Complex parallel hybrid vehicle"
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Rachananjali, K., K. Bala Krishna, S. Suman, and V. Tejasree. "Modeling of an ANFIS Controller for Series–Parallel Hybrid Vehicle." In Advances in Intelligent Systems and Computing, 631–43. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7868-2_60.
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Baños, Raul, Julio Ortega, and Consolación Gil. "Hybrid MPI/OpenMP Parallel Evolutionary Algorithms for Vehicle Routing Problems." In Applications of Evolutionary Computation, 653–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-45523-4_53.
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Fietz, Jonas, Mathias J. Krause, Christian Schulz, Peter Sanders, and Vincent Heuveline. "Optimized Hybrid Parallel Lattice Boltzmann Fluid Flow Simulations on Complex Geometries." In Euro-Par 2012 Parallel Processing, 818–29. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-32820-6_81.
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Zhou, Shilei, Paul Walker, and Nong Zhang. "Modelling and Vibration Characteristics Analysis of a Parallel Hydraulic Hybrid Vehicle." In Vibration Engineering for a Sustainable Future, 137–42. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47618-2_17.
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Vianna, Dalessandro Soares, Luiz S. Ochi, and Lúcia M. A. Drummond. "A parallel hybrid evolutionary metaheuristic for the period vehicle routing problem." In Lecture Notes in Computer Science, 183–91. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/bfb0097899.
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Jozefowiez, Nicolas, Frédéric Semet, and El-Ghazali Talbi. "Parallel and Hybrid Models for Multi-objective Optimization: Application to the Vehicle Routing Problem." In Parallel Problem Solving from Nature — PPSN VII, 271–80. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-45712-7_26.
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Krause, Mathias J., Thomas Gengenbach, and Vincent Heuveline. "Hybrid Parallel Simulations of Fluid Flows in Complex Geometries: Application to the Human Lungs." In Euro-Par 2010 Parallel Processing Workshops, 209–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21878-1_26.
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Schwan, Christian, and Martin Strehler. "Two FPTAS for the Constrained Shortest Path Problem Applied to Hybrid Vehicle Routing." In Modeling, Simulation and Optimization of Complex Processes HPSC 2015, 223–34. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-67168-0_18.
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Ouvrard, Hilde, Bruno Koobus, Maria-Vittoria Salvetti, Simone Camarri, and Alain Dervieux. "Variational Multiscale LES and Hybrid RANS/LES Parallel Simulation of Complex Unsteady Flows." In High Performance Computing for Computational Science - VECPAR 2008, 465–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-92859-1_41.
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Li, Chunming, Xiaoxia Sun, Chunming Shao, Lining Yang, Chenglong Shu, Danhua Niu, and Guozhu Wang. "Research on Energy Delivery of a Series–Parallel Hybrid Electric Vehicle Under Different Driving Conditions." In Lecture Notes in Electrical Engineering, 621–33. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5429-9_48.
Повний текст джерелаТези доповідей конференцій з теми "Complex parallel hybrid vehicle"
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Martelli, Massimo, Pietro Marani, and Silvia Gessi. "Series, Parallel, and Hybrid Series-Parallel Hydrostatic Transmission Architectures for Ground Locomotion." In ASME/BATH 2019 Symposium on Fluid Power and Motion Control. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/fpmc2019-1690.
Повний текст джерелаАнотація:
Abstract Ground locomotion of wheeled vehicles, in all-wheel drive configuration, is subject to unique, generally highly variable and not predictable, loading conditions on the driveline subsystem. Any sensible design must cope at least with the effects induced by slope changes, asymmetrical losses of adherence and cornering maneuvers. When severe constraints on the driveline layout make the implementation of standard mechanical transmissions unfeasible, a typical option is given by compound hydrostatic transmission architectures, with multiple dedicated motor-wheels. Requirements are then defined on two different levels: at vehicle level, traction functionality must never be lost; at hydraulic circuit level, all components must work within their nominal operating ranges and hydraulic stresses must be limited. Common standard topologies for motor connection, viz. series and parallel, come with different strengths and weaknesses, often requiring the implementation of auxiliary highly dissipative compensation components and/or complex electronic control, while a hybrid series-parallel concept, derived from a patented application, based on three-port motors allows the implementation of an effective, purely hydraulic system. In the present work, a general comparison of the above-mentioned architectures is provided, by means of numerical simulation, over a wide set of virtual experiments. Each architecture is analyzed: its specific features are described and the correlation between hydraulic performance/specifications and vehicle traction performance is pointed out.
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Won, Jong-Seob, and Reza Langari. "Fuzzy Torque Distribution Control for a Parallel Hybrid Electric Vehicle." In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/dsc-24505.
Повний текст джерелаАнотація:
Abstract A fuzzy torque distribution controller for energy management (and emission control) of a parallel-hybrid electric vehicle is proposed. The proposed controller is implemented in terms of a hierarchical architecture which incorporates the mode of operation of the vehicle as well as empirical knowledge of energy flow in each mode. Moreover, the rule set for each mode of operation of the vehicle is designed in view of an overall energy management strategy that ranges from maximal emphasis on battery charge sustenance to complete reliance on the electrical power source. The proposed control system is evaluated via computational simulations under the FTP75 urban drive cycle. Simulation results reveal that the proposed fuzzy torque distribution strategy is effective over the entire operating range of the vehicle in terms of performance, fuel economy as well as emissions.
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Gantt, Lynn R., Patrick M. Walsh, and Douglas J. Nelson. "Design and Development Process for a Range Extended Split Parallel Hybrid Electric Vehicle." In ASME 2010 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/detc2010-28576.
Повний текст джерелаАнотація:
The Hybrid Electric Vehicle Team of Virginia Tech (HEVT) is participating in the 2009–2011 EcoCAR: The NeXt Challenge Advanced Vehicle Technology Competition series organized by Argonne National Lab (ANL), and sponsored by General Motors Corporation (GM) and the U.S. Department of Energy (DOE). The goal of EcoCAR is for student engineers to take a GM-donated crossover SUV and re-engineer it to reduce greenhouse gas emissions and petroleum energy use, while maintaining performance, safety and consumer appeal. Following GM’s Vehicle Development Process (VDP), HEVT established team goals that meet or exceed the competition requirements for EcoCAR in the design of a plug-in range-extended hybrid electric vehicle. HEVT is split up into three subteams to complete the competition and meet the requirements of the vehicle development process. The Mechanical subteam is tasked with modifying and refining the Year 1 component specifications and designs for packaging in the vehicle. The Electrical subteam is tasked with implementing a safe high voltage system on the vehicle including the design and development of a Lithium Iron Phosphate (LiFePO4) energy storage subsystem (ESS) donated by A123 Systems. The Controls subteam is tasked with modeling the Vehicle Technical Specifications (VTS) so that the subteams can make intelligent design decisions. The Controls subteam also used a controller Hardware-In-the-Loop (HIL) simulation setup running a real-time vehicle model against the controller hardware to test the HEVT-designed Hybrid Vehicle Supervisory Controller (HVSC). The result of this design process is an Extended-Range Electric Vehicle (E-REV) that uses grid electric energy and E85 fuel for propulsion. The vehicle design is predicted to achieve an SAE J1711 utility factor-corrected fuel consumption of 2.9 l(ge)/100 km (82 mpgge) with an estimated all-electric range of 69 km (43 miles). Using corn-based E85 fuel in North America for the 2015 timeframe and an average North American electricity mix, the well-to-wheels petroleum energy use and greenhouse gas emissions are reduced by 90% and 30% respectively when compared to the stock vehicle: a 4-cylinder, gasoline-fueled Vue XE.
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Cikanek, Susan R., Robert C. Baraszu, Kathleen E. Bailey, N. Sureshbabu, and Matt Brackx. "Dynamic Model and Control Law for a Low Storage Requirement Parallel Hybrid Electric Vehicle." In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/dsc-24525.
Повний текст джерелаАнотація:
Abstract This paper describes mathematical modeling, analysis, simulation, and Hardware-in-the-Loop (HIL) results of a Low Storage Requirement Hybrid Electric Vehicle powertrain and control system. The hybrid powertrain is synthesized using a conventional spark-ignited internal combustion engine, an alternating current induction traction motor, a converterless automatic transmission, and a differential and halfshafts that drive front wheels. Component models are summarized and a complete powertrain model is presented. An operating strategy is also discussed together with HIL simulation results that demonstrate system performance.
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Bianchi, Domenico, Luciano Rolando, Lorenzo Serrao, Simona Onori, Giorgio Rizzoni, Nazar Al-Khayat, Tung-Ming Hsieh, and Pengju Kang. "A Rule-Based Strategy for a Series/Parallel Hybrid Electric Vehicle: An Approach Based on Dynamic Programming." In ASME 2010 Dynamic Systems and Control Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/dscc2010-4233.
Повний текст джерелаАнотація:
Dynamic programming (DP) provides the optimal global solution to the energy management problem for hybrid electric vehicles (HEVs), but needs complete a-priori knowledge of the driving cycle and has high computational requirements. This article presents a possible methodology to extract rules from the dynamic programming solution to design an implementable rule-based strategy. The case study considered is a series/parallel HEV, in which a clutch allows to switch from one configuration to another. The strategy works according to a two layer policy: the supervisory controller, which decides the powertrain configuration (either series or parallel), and the energy management, which decides the power split. The process of deriving the rules from the optimal solution is described. Then, the performance of the resulting rule-based strategy is studied and compared with the solution given by the dynamic programming, which functions as a benchmark.
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Jones, Stephen, Arno Huss, Sander Boksebeld, Niklas Wikström, and Gerald Teuschl. "Predictive Control utilizing Electronic Horizon for Hybrid & Range Extender Powertrains." In FISITA World Congress 2021. FISITA, 2021. http://dx.doi.org/10.46720/f2020-adm-036.
Повний текст джерелаАнотація:
A Hybrid Electric Vehicle (HEV) can achieve a considerably higher overall fuel economy than conventional vehicles. However, the fuel economy of HEVs strongly depends on the control strategy of the hybrid powertrain. Compared to conventional non-predictive hybrid control systems, predictive control methods can significantly further improve the fuel economy by anticipating future driving conditions such as hills, curves, speed limits, traffic flows, and in the future even geo-fenced low emission city zones. However, the selection of the driving mode and power distribution between multiple power sources which achieves the highest overall energy efficiency considering predictive information along the future driving route is a highly complex task. This complexity is further increased when taking into account the feasibility of the control actions, for example considering aspects such as driveability, NVH, emissions and lifetime durability, as well as real-time capability for online implementation on an HCU (Hybrid Control Unit). AVL’s predictive control methodology offers a flexible approach applicable to different hybrid types (e.g. HEV, Plug-in HEV and Range Extender) and powertrain topologies (e.g. parallel and series). It provides a real-time applicable control strategy that reduces the fuel/energy consumption, based on the preview of the future road type and topography and the likely velocity profile along the route, typically received from a digital map system in the form of an eHorizon, which may be enhanced with dynamic information from V2X. The control method consists of a long-horizon estimation that determines an energy efficient battery depletion strategy, which is subsequently tracked by an optimization-based short-horizon control method to select the driving mode and power distribution. The control method provides control requests for the different power sources, which can additionally explicitly consider constraints for feasibility and driveability (e.g. frequency of engine starts) to avoid unacceptable control policies. The performance of the control method is validated towards a globally optimal strategy obtained by an offline optimization using dynamic programming. The concept has been implemented on HCU hardware with limited computational resources, where its real-time capability was evaluated. In this paper, the predictive control methodology was applied on a hybrid passenger vehicle and the effectiveness of the strategy was demonstrated in a simulation environment. The predictive control method shows significant improvements in fuel economy, compared to a non-predictive and heuristic baseline control strategy.
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Madjlesi, Reza, Amir Khajepour, Brad Schubert, and Fathy Ismail. "A New Approach on Mounting Systems Optimization." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-41641.
Повний текст джерелаАнотація:
Vehicles are assemblies of subsystems or modules, which are developed in parallel at multiple locations and often for more than one vehicle. CAE software provides the integration of modules in a complete vehicle in parallel; however the whole system requires final adjustments and tunings. These adjustments, especially in suspensions and mounting systems are very time consuming and are generally based upon trial and error techniques. To reduce the number of trials, usually noise path analysis (NPA) is used. In this technique, the noise and vibration paths for each mount to the objective point are measured. Using the measured data, the dominant path is detected. A highly experienced NVH engineer now can use the information to tune the mount to satisfy the target response. This technique is appropriate if the subsystems are weakly coupled. This situation is not usually the case in engine mounting systems where any modification in one of the mounts may change the dominant path. An important step to reduce refinement time is to develop a method to obtain the overall model of the whole vehicle. In this paper, we introduce a new approach in vehicle’s NVH development. In this approach, the model of the vehicle for mounting system optimization is obtained based on the FRF synthesis. A hybrid analytical/experimental model of the vehicle is developed to predict the NVH response of the vehicle for any given mounting system. This model along with an optimization technique is used to arrive at the optimum mounting system for any objective function. The optimization method is linked with the noise path analysis (NPA), which is used to specify the dominant directions that the noise/vibration is transferred to the response point. These directions are used in the optimization procedure to find the optimum mounting system with minimum calculation time. Experimental results on a full size car are presented to evaluate new approach.
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Marshaus, Julie G., Mike A. Gall, Jennifer A. Topinka, and Glenn R. Bower. "Safety Aspects Related to the Development of a Full Aluminum Frame for the Year 2000, 1500 Series Chevy Suburban." In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/amd-25442.
Повний текст джерелаАнотація:
Abstract In conjunction with the FutureTruck collegiate design competition, The University of Wisconsin - Madison has integrated an all aluminum frame into their four-wheel drive, charge sustaining, parallel hybrid-electric sport utility vehicle. The base vehicle is a 2000 Chevrolet Suburban nicknamed the “Moollennium” and weighs approximately 2400 kg. The original GMT 830 frame constitutes 10% of the Suburban’s weight and has the largest weight reduction potential. In a cooperative effort with Tower Automotive, the University of Wisconsin-Madison has modeled, stamped and constructed two full aluminum frames using the GMT 430 tooling. The first frame, the UW 430 AL, was assembled to replicate the GMT 430 frame, while the second-generation frame, the UW 830 AL, mimicked the GMT 830 frame. FEA and traditional deflection and bending calculations were used to stiffen and strengthen the aluminum frame to acceptable levels. Front horn crush tests were used to optimize frontal impact energy absorption — the UW 830 AL design absorbs 36% more energy than the original GMT 430 steel frame with a 40% reduction in peak load. The complete aluminum frame weighs 120 kg — 98 kg lighter than the steel GMT 830 frame and 130 kg lighter than the steel GMT 430 frame.
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McMurran, R., A. C. Rao, and P. Jones. "Model based validation techniques for complex control systems." In IET Hybrid Vehicle Conference 2006. IEE, 2006. http://dx.doi.org/10.1049/cp:20060609.
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Li, Weimin, Guoqing Xu, Zhancheng Wang, and Yangsheng Xu. "A Hybrid Controller Design For Parallel Hybrid Electric Vehicle." In 2007 IEEE International Conference on Integration Technology. IEEE, 2007. http://dx.doi.org/10.1109/icitechnology.2007.4290517.
Повний текст джерелаЗвіти організацій з теми "Complex parallel hybrid vehicle"
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Development of an Adaptive Efficient Thermal/Electric Skipping Control Strategy Applied to a Parallel Plug-in Hybrid Electric Vehicle. SAE International, March 2022. http://dx.doi.org/10.4271/2022-01-0737.
Повний текст джерелаАнотація:
In recent years automobile manufacturers focused on an increasing degree of electrification of the powertrains with the aim to reduce pollutants and CO2 emissions. Despite more complex design processes and control strategies, these powertrains offer improved fuel exploitation compared to conventional vehicles thanks to intelligent energy management. A simulation study is here presented aiming at developing a new control strategy for a P3 parallel plug-in hybrid electric vehicle. The simulation model is implemented using vehicle modeling and simulation toolboxes in MATLAB/Simulink. The proposed control strategy is based on an alternative utilization of the electric motor and thermal engine to satisfy the vehicle power demand at the wheels (Efficient Thermal/Electric Skipping Strategy - ETESS). The choice between the two units is realized through a comparison between two equivalent fuel rates, one related to the thermal engine and the other related to the electric consumption. An adaptive function is introduced to develop a charge-blended control strategy. The novel adaptive control strategy (A-ETESS) is applied to estimate fuel consumption along different driving cycles. The control algorithm is implemented on a dedicated microcontroller unit performing a Processor-In-the-Loop (PIL) simulation. To demonstrate the reliability and effectiveness of the A-ETESS, the same adaptive function is built on the Equivalent Consumption Minimization Strategy (ECMS). The PIL results showed that the proposed strategy ensures a fuel economy similar to ECMS (worse of about 2% on average) and a computational effort reduced by 99% on average. This last feature reveals the potential for real-time on-vehicle applications.
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Vehicle Surge Reduction Technology during Towing in Parallel HEV Pickup Truck. SAE International, March 2022. http://dx.doi.org/10.4271/2022-01-0613.
Повний текст джерелаАнотація:
This paper proposes a technology to reduce vehicle surge during towing that utilizes motors and shifting to help ensure comfort in a parallel HEV pickup truck. Hybridization is one way to reduce fuel consumption and help realize carbon neutrality. Parallel HEVs have advantages in the towing, hauling, and high-load operations often carried out by pickup trucks, compared to other HEV systems. Since the engine, motor, torque converter, and transmission are connected in series in a parallel HEV, vehicle surge may occur when the lockup clutch is engaged to enhance fuel efficiency, similar to conventional powertrains. Vehicle surge is a low-frequency vibration phenomenon. In general, the source is torque fluctuation caused by the engine and tires, with amplification provided by first-order torsional driveline resonance, power plant resonance, suspension resonance, and cabin resonance. This vibration is amplified more during towing. Therefore, this paper proposes two surge reduction technologies to help achieve fuel efficiency and surge at the same time during towing. One technology is a gear shift control that avoids engine operating zones where two or more resonance frequencies coincide, which is realized by changing the equivalent inertia via appropriate gear selection. The second technology is an anti-vibration control, which makes effective use of the hybrid system motors by adding motor torque to suppress the relative displacement between the driveline and the tires.