Journal articles: 'Automotive sensors'

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Liu, Ji. "Automobile Sensor Technology Development and Application Research." Applied Mechanics and Materials 727-728 (January 2015): 704–7. http://dx.doi.org/10.4028/www.scientific.net/amm.727-728.704.

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This paper introduces the developing course of auto sensor and impetus, automotive electronic system in various sensors practical level, gives the best technical index, and the current sensor in the application of automotive electronic control system, and shows the development trend of the automotive sensors and the forecast, points out the development direction of modern sensor technology is integrated and intelligent, likely has a huge market share in the future several kinds of new sensors, and finally the development of the automotive sensors are described briefly and the market forecast.

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Gomes, Tiago, Ricardo Roriz, Luís Cunha, Andreas Ganal, Narciso Soares, Teresa Araújo, and João Monteiro. "Evaluation and Testing System for Automotive LiDAR Sensors." Applied Sciences 12, no. 24 (December 18, 2022): 13003. http://dx.doi.org/10.3390/app122413003.

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The world is facing a great technological transformation towards fully autonomous vehicles, where optimists predict that by 2030 autonomous vehicles will be sufficiently reliable, affordable, and common to displace most human driving. To cope with these trends, reliable perception systems must enable vehicles to hear and see all their surroundings, with light detection and ranging (LiDAR) sensors being a key instrument for recreating a 3D visualization of the world in real time. However, perception systems must rely on accurate measurements of the environment. Thus, these intelligent sensors must be calibrated and benchmarked before being placed on the market or assembled in a car. This article presents an Evaluation and Testing Platform for Automotive LiDAR sensors, with the main goal of testing both commercially available sensors and new sensor prototypes currently under development in Bosch Car Multimedia Portugal. The testing system can benchmark any LiDAR sensor under different conditions, recreating the expected driving environment in which such devices normally operate. To characterize and validate the sensor under test, the platform evaluates several parameters, such as the field of view (FoV), angular resolution, sensor’s range, etc., based only on the point cloud output. This project is the result of a partnership between the University of Minho and Bosch Car Multimedia Portugal.

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Rasshofer, R. H., and K. Gresser. "Automotive Radar and Lidar Systems for Next Generation Driver Assistance Functions." Advances in Radio Science 3 (May 12, 2005): 205–9. http://dx.doi.org/10.5194/ars-3-205-2005.

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Abstract. Automotive radar and lidar sensors represent key components for next generation driver assistance functions (Jones, 2001). Today, their use is limited to comfort applications in premium segment vehicles although an evolution process towards more safety-oriented functions is taking place. Radar sensors available on the market today suffer from low angular resolution and poor target detection in medium ranges (30 to 60m) over azimuth angles larger than ±30°. In contrast, Lidar sensors show large sensitivity towards environmental influences (e.g. snow, fog, dirt). Both sensor technologies today have a rather high cost level, forbidding their wide-spread usage on mass markets. A common approach to overcome individual sensor drawbacks is the employment of data fusion techniques (Bar-Shalom, 2001). Raw data fusion requires a common, standardized data interface to easily integrate a variety of asynchronous sensor data into a fusion network. Moreover, next generation sensors should be able to dynamically adopt to new situations and should have the ability to work in cooperative sensor environments. As vehicular function development today is being shifted more and more towards virtual prototyping, mathematical sensor models should be available. These models should take into account the sensor's functional principle as well as all typical measurement errors generated by the sensor.

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Russell, M. E., C. A. Drubin, A. S. Marinilli, W. G. Woodington, and M. J. Del Checcolo. "Integrated automotive sensors." IEEE Transactions on Microwave Theory and Techniques 50, no. 3 (March 2002): 674–77. http://dx.doi.org/10.1109/22.989952.

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Bogue, Robert. "Advanced automotive sensors." Sensor Review 22, no. 2 (June 1, 2002): 113–18. http://dx.doi.org/10.1108/02602280210421217.

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Tutunea, Dragos, George Gherghina, and Adrian Constantin Cernaianu. "Study of Inductive Sensors for Automotive Applications." Applied Mechanics and Materials 822 (January 2016): 341–45. http://dx.doi.org/10.4028/www.scientific.net/amm.822.341.

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There is an ever increasing demand for use of inductive speed sensors in a broad range of applications. They are used in typical applications such as cam and crank shaft position/speed and wheel and turbo shaft speed measurement. This paper describes the type of inductive sensor found on vehicles and the difficulties of detecting at low speeds. In the laboratory of Mechatronics an experimental device has been done to measure the speed using an inductive speed sensor. The experimental results are satisfactory and show the possibility of the inductive sensors to be used in automotive industry.

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Tutunea, Dragos, Ilie Dumitru, Oana Victoria Oţăt, Laurentiu Racila, Ionuţ Daniel Geonea, and Claudia Cristina Rotea. "Oxygen Sensor Testing for Automotive Applications." Applied Mechanics and Materials 896 (February 2020): 249–54. http://dx.doi.org/10.4028/www.scientific.net/amm.896.249.

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During the operation of internal combustion engines the air-fuel ratio (A/F) is an important parameter which affects fuel consumption and pollutant emissions. The automotive oxygen sensor (Lambda) measures the quantity of residual oxygen in the combustion gases. Sensor degradation in time due to the exposure to high temperatures causes a distortion in controlling the A/F with the increase in gas emissions. In this paper an experimental stand is designed to test oxygen sensor degradation in laboratory condition. Four oxygen sensors were tested function of temperature and time recording their variation in resistance and voltage. The results showed similar values in the curves for all sensors tested.

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Tanev, A., P. Mitsev, and T. Lazarova. "Challenging Sensing Solutions Designed by Sensata Bulgaria." Information Technologies and Control 15, no. 4 (December 1, 2017): 28–39. http://dx.doi.org/10.1515/itc-2017-0035.

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Abstract This paper presents novel green automotive platinum sensing technology together with pressure sensors design principles and applications. In recent years, worldwide emissions legislation has been introduced and is rapidly becoming more stringent. With alternative vehicular propulsion methods far from becoming mainstream reality, leading automotive providers have intensified efforts in the direction of reducing the harmful footprint of their products. This is being accomplished via smaller, appropriately designed internal combustion engines, necessitating an increased and higher-performance sensor content per vehicle. This paper elaborates on temperature sensor application in automotive exhaust gas performance sensing and as well as pressure sensors in different challenging automotive applications with very high pressure levels.

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Schriefl, Mario Anton, Matthias Longin, and Alexander Bergmann. "Charging-Based PN Sensing of Automotive Exhaust Particles." Proceedings 2, no. 13 (January 3, 2019): 805. http://dx.doi.org/10.3390/proceedings2130805.

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Mobile measurement of particle number concentration (PN) in the exhaust of motor vehicles has recently become an integral part of emission legislation. Charge-based sensing techniques for the examination of PN, like Diffusion Charging (DC), represent a promising alternative to condensational particle counters (CPCs) as established PN sensors, because they enable to build robust, compact and energy efficient systems. However, due to the charging process, particle properties like size and morphology have a big impact on the sensor’s PN response. For particles of different size and shape we experimentally investigated those impacts using own-built charging-based sensors. The PN response of the DC sensor showed desired behavior for compact NaCl particles, but less satisfying behavior for combustion aerosol standard (CAST) particles, which is a widely used test aerosol for automotive applications. With a photoelectric charger, the PN response of CAST particles was significantly better.

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Westbrook, M. H. "Sensors for automotive application." Journal of Physics E: Scientific Instruments 18, no. 9 (September 1985): 751–58. http://dx.doi.org/10.1088/0022-3735/18/9/004.

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Turner, J. D., and L. Austin. "Sensors for automotive telematics." Measurement Science and Technology 11, no. 2 (January 19, 2000): R58—R79. http://dx.doi.org/10.1088/0957-0233/11/2/202.

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Fleming, W. J. "Overview of automotive sensors." IEEE Sensors Journal 1, no. 4 (2001): 296–308. http://dx.doi.org/10.1109/7361.983469.

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Perka, Bogdan, Andrzej Szafraniec, and Radosław Figura. "A method of direct diagnostics of thermoresistive temperature sensors in vehicle." AUTOBUSY – Technika, Eksploatacja, Systemy Transportowe 24, no. 6 (June 30, 2019): 234–39. http://dx.doi.org/10.24136/atest.2019.157.

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The article discusses thermistor temperature sensors used in automotive vehicles. The characteristic types R=f(T) of thermoresistors as well as their technical and operational parameters are presented. The applications of particular types of thermoresistors in temperature measurements in automotive vehicles are discussed. On the example of the coolant temperature sensors diagnostics is presented. The test results and conclusion regarding the tested sensor diagnostics is presented. The test result and conclusions regarding the tested sensors are presented.

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Bartsch, A., F. Fitzek, and R. H. Rasshofer. "Pedestrian recognition using automotive radar sensors." Advances in Radio Science 10 (September 18, 2012): 45–55. http://dx.doi.org/10.5194/ars-10-45-2012.

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Abstract. The application of modern series production automotive radar sensors to pedestrian recognition is an important topic in research on future driver assistance systems. The aim of this paper is to understand the potential and limits of such sensors in pedestrian recognition. This knowledge could be used to develop next generation radar sensors with improved pedestrian recognition capabilities. A new raw radar data signal processing algorithm is proposed that allows deep insights into the object classification process. The impact of raw radar data properties can be directly observed in every layer of the classification system by avoiding machine learning and tracking. This gives information on the limiting factors of raw radar data in terms of classification decision making. To accomplish the very challenging distinction between pedestrians and static objects, five significant and stable object features from the spatial distribution and Doppler information are found. Experimental results with data from a 77 GHz automotive radar sensor show that over 95% of pedestrians can be classified correctly under optimal conditions, which is compareable to modern machine learning systems. The impact of the pedestrian's direction of movement, occlusion, antenna beam elevation angle, linear vehicle movement, and other factors are investigated and discussed. The results show that under real life conditions, radar only based pedestrian recognition is limited due to insufficient Doppler frequency and spatial resolution as well as antenna side lobe effects.

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Lozoya-Santos, Jorge de-J., L. C. Félix-Herrán, Juan C. Tudón-Martínez, Adriana Vargas-Martinez, and Ricardo A. Ramirez-Mendoza. "Design and Implementation of an IoT-Oriented Strain Smart Sensor with Exploratory Capabilities on Energy Harvesting and Magnetorheological Elastomer Transducers." Applied Sciences 10, no. 12 (June 26, 2020): 4387. http://dx.doi.org/10.3390/app10124387.

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This work designed and implemented a new low-cost, Internet of Things-oriented, wireless smart sensor prototype to measure mechanical strain. The research effort explores the use of smart materials as transducers, e.g., a magnetorheological elastomer as an electrical-resistance sensor, and a cantilever beam with piezoelectric sensors to harvest energy from vibrations. The study includes subsequent and validated results with a magnetorheological elastomer transducer that contained multiwall carbon nanotubes with iron particles, generated voltage tests from an energy-harvesting system that functions with an array of piezoelectric sensors embedded in a rubber-based cantilever beam, wireless communication to send data from the sensor’s central processing unit towards a website that displays and stores the handled data, and an integrated manufactured prototype. Experiments showed that electrical-resistivity variation versus measured strain, and the voltage-generation capability from vibrations have the potential to be employed in smart sensors that could be integrated into commercial solutions to measure strain in automotive and aircraft systems, and civil structures. The reported experiments included cloud-computing capabilities towards a potential Internet of Things application of the smart sensor in the context of monitoring automotive-chassis vibrations and airfoil damage for further analysis and diagnostics, and in general structural-health-monitoring applications.

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Srinivasan, K. P., and T. Muthuramalingam. "Fabrication and Performance Evolution of AgNP Interdigitated Electrode Touch Sensor for Automotive Infotainment." Sensors 21, no. 23 (November 29, 2021): 7961. http://dx.doi.org/10.3390/s21237961.

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In the present scenario, a considerable assiduity is provided to develop novel human-machine interface technologies that rapidly outpace the capabilities of display technology in automotive industries. It is necessary to use a new cockpit design in conjunction with a fully automated driving environment in order to enhance the driving experience. It can create a seamless and futuristic dashboard for automotive infotainment application. In the present study, an endeavor was made to equip the In-vehicle bezels with printed capacitive sensors for providing superior sensing capabilities. Silver Nanoparticles based interdigitated pattern electrodes were formed over polycarbonate substrates to make printed capacitive sensors using screen printing process. The developed sensor was investigated to evaluate the qualitative and quantitative measures using direct and in-direct contact of touch. The proposed approach for sensors pattern and fabrication can highly impact on sensor performance in automotive infotainment application due to the excellent spatial interpolation with lower cost, light weight, and mechanical flexibility.

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Goelles, Thomas, Birgit Schlager, and Stefan Muckenhuber. "Fault Detection, Isolation, Identification and Recovery (FDIIR) Methods for Automotive Perception Sensors Including a Detailed Literature Survey for Lidar." Sensors 20, no. 13 (June 30, 2020): 3662. http://dx.doi.org/10.3390/s20133662.

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Perception sensors such as camera, radar, and lidar have gained considerable popularity in the automotive industry in recent years. In order to reach the next step towards automated driving it is necessary to implement fault diagnosis systems together with suitable mitigation solutions in automotive perception sensors. This is a crucial prerequisite, since the quality of an automated driving function strongly depends on the reliability of the perception data, especially under adverse conditions. This publication presents a systematic review on faults and suitable detection and recovery methods for automotive perception sensors and suggests a corresponding classification schema. A systematic literature analysis has been performed with focus on lidar in order to review the state-of-the-art and identify promising research opportunities. Faults related to adverse weather conditions have been studied the most, but often without providing suitable recovery methods. Issues related to sensor attachment and mechanical damage of the sensor cover were studied very little and provide opportunities for future research. Algorithms, which use the data stream of a single sensor, proofed to be a viable solution for both fault detection and recovery.

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Schmidt, Rainer. "Pressure sensors for automotive applications." ATZautotechnology 1, no. 6 (November 2001): 62–64. http://dx.doi.org/10.1007/bf03246659.

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Fleming, Bill. "Sensors?A Forecast [Automotive Electronics]." IEEE Vehicular Technology Magazine 8, no. 3 (September 2013): 4–12. http://dx.doi.org/10.1109/mvt.2013.2268420.

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Treutler, C. P. O. "Magnetic sensors for automotive applications." Sensors and Actuators A: Physical 91, no. 1-2 (June 2001): 2–6. http://dx.doi.org/10.1016/s0924-4247(01)00621-5.

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Nonomura, Yutaka. "Automotive Sensors and MEMS Technology." IEEJ Transactions on Sensors and Micromachines 126, no. 8 (2006): 387–92. http://dx.doi.org/10.1541/ieejsmas.126.387.

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Subbarao, E. C. "Oxygen Sensors for Automotive Applications." Transactions of the Indian Ceramic Society 49, no. 3 (January 1990): 47–59. http://dx.doi.org/10.1080/0371750x.1990.10822991.

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Fleming, William J. "New Automotive Sensors—A Review." IEEE Sensors Journal 8, no. 11 (November 2008): 1900–1921. http://dx.doi.org/10.1109/jsen.2008.2006452.

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Kobayashi, Hiroshi. "Development process for automotive sensors." Sensors and Actuators 19, no. 4 (September 1989): 415–26. http://dx.doi.org/10.1016/0250-6874(89)87090-8.

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Kallenbach, Rainer, Jiri Marek, Udo-Martin Gomez, and Laura Weingarten-Platz. "Micromachined sensors for automotive applications." ATZelektronik worldwide 1, no. 4 (December 2006): 20–21. http://dx.doi.org/10.1007/bf03242101.

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Zosel, J., F. De_Blauwe, and U. Guth. "Chemical Sensors for Automotive Application." Advanced Engineering Materials 3, no. 10 (October 2001): 797. http://dx.doi.org/10.1002/1527-2648(200110)3:10<797::aid-adem797>3.0.co;2-l.

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Petrov, Roman, Viktor Leontiev, Oleg Sokolov, Mirza Bichurin, Slavcho Bozhkov, Ivan Milenov, and Penko Bozhkov. "A Magnetoelectric Automotive Crankshaft Position Sensor." Sensors 20, no. 19 (September 25, 2020): 5494. http://dx.doi.org/10.3390/s20195494.

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The paper is devoted to the possibility of using magnetoelectric materials for the production of a crankshaft position sensor for automobiles. The composite structure, consisting of a PZT or LiNbO3 piezoelectric with a size of 20 mm × 5 mm × 0.5 mm, and plates of the magnetostrictive material Metglas of the appropriate size were used as a sensitive element. The layered structure was made from a bidomain lithium niobate monocrystal with a Y + 128° cut and amorphous metal of Metglas. Various combinations of composite structures are also investigated; for example, asymmetric structures using a layer of copper and aluminum. The output characteristics of these structures are compared in the resonant and non-resonant modes. It is shown that the value of the magnetoelectric resonant voltage coefficient was 784 V/(cm·Oe), and the low-frequency non-resonant magnetoelectric coefficient for the magnetoelectric element was about 3 V/(cm·Oe). The principle of operation of the position sensor and the possibility of integration into automotive systems, using the CAN bus, are examined in detail. To obtain reliable experimental results, a special stand was assembled on the basis of the SKAD-1 installation. The studies showed good results and a high prospect for the use of magnetoelectric sensors as position sensors and, in particular, of a vehicle’s crankshaft position sensor.

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Varga, Balázs, Mátyás Szalai, Árpád Fehér, Szilárd Aradi, and Tamás Tettamanti. "Mixed-reality Automotive Testing with SENSORIS." Periodica Polytechnica Transportation Engineering 48, no. 4 (August 3, 2020): 357–62. http://dx.doi.org/10.3311/pptr.15851.

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Highly automated and autonomous vehicles become more and more widespread changing the classical way of testing and validation. Traditionally, the automotive industry has pursued testing rather in real-world or in pure virtual simulation environments. As a new possibility, mixed-reality testing has also appeared enabling an efficient combination of real and simulated elements of testing. Furthermore, vehicles from different OEMs will have a common interface to communicate with a test system. The paper presents a mixed-reality test framework for visualizing perception sensor feeds real-time in the Unity 3D game engine. Thereby, the digital twin of the tested vehicle and its environment are realized in the simulation. The communication between the sensors of the tested vehicle and the central computer running the test is realized via the standard SENSORIS interface. The paper outlines the hardware and software requirements towards such a system in detail. To show the viability of the system a vehicle in the loop test has been carried out.

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Paliwal, Sachin, and Birinderjit Singh Kalyan. "Driver’s Activity Detection System using Human antenna." Indian Journal of Energy and Energy Resources 1, no. 3 (May 30, 2022): 4–6. http://dx.doi.org/10.54105/ijeer.c1007.051322.

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Now a days we can see that there are many cases which are occurring due to the drowsiness of drivers and that has become a main problem of the automotive industry. To overcome this in automotive industry the introduction of new technologies that is by introducing of new sensor which can detect the different activities. Detection of activities by sensors is for biological measuring such as heartbeat, oxygen level, respiration activity, etc. By applying such widespread variety of sensor usage in the system has a very high implementation cost and also very complexity which is a bit challenging design. In this paper, we are going study that how humantenna effect is used to detect and test the drive drowsiness by using simple and budget sensors in automotive industry.

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Caprita, Horia V., and Dan Selisteanu. "Improvement of Automotive Sensors by Migrating AUTOSAR End-to-End Communication Protection Library into Hardware." Elektronika ir Elektrotechnika 28, no. 5 (October 26, 2022): 34–44. http://dx.doi.org/10.5755/j02.eie.31154.

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This paper explores new methods to increase the level of safety of data transfer between sensors and electronic control units (ECUs) in automotive communication. A new model of basic sensors to be used in automotive electronics is proposed. This model contains hardware modules that implement the end-to-end communication protection (E2E) mechanism, as defined by the Automotive Open System Architecture (AUTOSAR) standard. By adding this feature inside the sensors, it is possible that, in addition to increasing the safety level, these sensors can be directly connected to the network ECUs via standard communication buses (e.g., Local Interconnect Network (LIN), Controller Area Network (CAN), Flexray, etc.). This paper describes the model, design, and mapping (in a Field Programmable Gate Array device (FPGA)) of the hardware E2E module capable of generating the Cyclic Redundancy Code (CRC) and counter signal for a customized message. This message represents the output of the new sensor E2E module used in a safety communication as requested by the automotive E2E standard. The model is validated also by comparing the data output of the E2E hardware with the data output of the AUTOSAR software E2E library. Finally, future needs and directions are suggested in this area.

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Gierth, Paul, Lars Rebenklau, Klaus Augsburg, Eric Bachmann, and Lars Niedermeyer. "Novel thermocouples for automotive applications." Journal of Sensors and Sensor Systems 7, no. 1 (February 2, 2018): 43–49. http://dx.doi.org/10.5194/jsss-7-43-2018.

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Abstract. Measurement of temperatures in engine and exhaust systems in automotive applications is necessary for thermal protection of the parts and optimizing of the combustion process. State-of-the-art temperature sensors are very limited in their response characteristic and installation space requirement. Miniaturized sensor concepts with a customizable geometry are needed. The basic idea of this novel sensor concept is to use thick-film technology on component surfaces. Different standardized and especially nonstandard material combinations of thermocouples have been produced for the validation of this technology concept. Application-oriented measurements took place in the exhaust system of a test vehicle and were compared to standard laboratory conditions.

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Klein, Linda, Yvonne Joseph, and Matthias Kröger. "Product Integration of Established Crash Sensors for Safety Applications in Lightweight Vehicles." Sensors 21, no. 21 (October 21, 2021): 6994. http://dx.doi.org/10.3390/s21216994.

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The functionality of products increases when more sensors are used. This trend also affects future automobiles and becomes even more relevant in connected and autonomous applications. Concerning automotive lightweight design, carbon fibre-reinforced polymers (CFRP) are suitable materials. However, their drawbacks include the relatively high manufacturing costs of CFRP components in addition to the difficulty of recycling. To compensate for the increased expenditure, the integration of automotive sensors in CFRP vehicle structures provides added value. As a new approach, established sensors are integrated into fibre-reinforced polymer (FRP) structures. The sensors are usually mounted to the vehicle. The integration of sensors into the structure saves weight and space. Many other approaches specifically develop new sensors for integration into FRP structures. With the new approach, there is no need for elaborate development of new sensors since established sensors are used. The present research also showed that the range of applications of the sensors can be extended by the integration. The present paper outlines the functional behaviour of the integrated sensor utilized for crashing sensing. First of all, the integration quality of the sensor is relevant. Different requirements apply to the usual mounting of the sensor. The self-sensing structure must fulfil those requirements. Moreover, unfamiliar characteristics of the new surrounding structure might affect the sensing behaviour. Thus, the sensing behaviour of the self-sensing composite was analyzed in detail. The overarching objective is the general integration of sensors in products with reasonable effort.

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Thiessen, T., and M. Prochaska. "A new high-integrated weak field sensor for automotive applications." Advances in Radio Science 7 (May 18, 2009): 89–94. http://dx.doi.org/10.5194/ars-7-89-2009.

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Abstract. Especially in the field of automotive applications smart sensor systems for magnetic field sensing face increasing requirements concerning low cost, low power consumption and high magnetic performance. Over the past years AMR sensors play a decisive role in this application area because of their robustness and stability. In the following a high-integrated smart sensor system for magnetic field sensing is presented. A novel approach for the detection of weak magnetic fields is shown, which is based on an AC-excitation of AMR elements. In contrast to common used sensors this concept is based on a nonlinear AMR element without Barber pole construction. By means of this methodology sensitivity as well as temperature and life time stability is significantly improved, while the production costs compared to common-used sensors are reduced. Within this novel approach new signal conditioning algorithms and analog circuit topologies are presented, which are able to meet low offset and low noise requirements.

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., Saida. "MEMS Technology in Automotive Industry." International Journal for Research in Applied Science and Engineering Technology 9, no. VI (June 25, 2021): 2702–5. http://dx.doi.org/10.22214/ijraset.2021.35508.

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The car business has consistently been a region, where the likelihood to investigate more and to accomplish cutting edge innovation stays a test. As the market is developing, the potential outcomes are being investigated on a more extensive scale. Furthermore, these developing prospects are progressively requesting the exploration for the more exact working of the auto using different sensors and the coordination angles related with them. While improving the quality/execution of the vehicle, the need to diminish the size of sensors consistently stays a test. Throughout the timeframe, the innovation has progressed and these difficulties are taken consideration using MEMS (Micro electro mechanical frameworks) incorporated frameworks. MEMS helps in contriving microscale sensors with higher precision in little size and minimal expense. In the auto, there exists a colossal requirement for these introducing these sensors and using them to refine the exhibition attributes of the vehicles.

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Koenig, A., T. Rehg, and R. Rasshofer. "Statistical sensor fusion of ECG data using automotive-grade sensors." Advances in Radio Science 13 (November 3, 2015): 197–202. http://dx.doi.org/10.5194/ars-13-197-2015.

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Abstract. Driver states such as fatigue, stress, aggression, distraction or even medical emergencies continue to be yield to severe mistakes in driving and promote accidents. A pathway towards improving driver state assessment can be found in psycho-physiological measures to directly quantify the driver's state from physiological recordings. Although heart rate is a well-established physiological variable that reflects cognitive stress, obtaining heart rate contactless and reliably is a challenging task in an automotive environment. Our aim was to investigate, how sensory fusion of two automotive grade sensors would influence the accuracy of automatic classification of cognitive stress levels. We induced cognitive stress in subjects and estimated levels from their heart rate signals, acquired from automotive ready ECG sensors. Using signal quality indices and Kalman filters, we were able to decrease Root Mean Squared Error (RMSE) of heart rate recordings by 10 beats per minute. We then trained a neural network to classify the cognitive workload state of subjects from heart rate and compared classification performance for ground truth, the individual sensors and the fused heart rate signal. We obtained an increase of 5 % higher correct classification by fusing signals as compared to individual sensors, staying only 4 % below the maximally possible classification accuracy from ground truth. These results are a first step towards real world applications of psycho-physiological measurements in vehicle settings. Future implementations of driver state modeling will be able to draw from a larger pool of data sources, such as additional physiological values or vehicle related data, which can be expected to drive classification to significantly higher values.

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Sekhar, Ravi, Nitin Solke, and Pritesh Shah. "Lean Manufacturing Soft Sensors for Automotive Industries." Applied System Innovation 6, no. 1 (February 3, 2023): 22. http://dx.doi.org/10.3390/asi6010022.

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Lean and flexible manufacturing is a matter of necessity for the automotive industries today. Rising consumer expectations, higher raw material and processing costs, and dynamic market conditions are driving the auto sector to become smarter and agile. This paper presents a machine learning-based soft sensor approach for identification and prediction of lean manufacturing (LM) levels of auto industries based on their performances over multifarious flexibilities such as volume flexibility, routing flexibility, product flexibility, labour flexibility, machine flexibility, and material handling. This study was based on a database of lean manufacturing and associated flexibilities collected from 46 auto component enterprises located in the Pune region of Maharashtra State, India. As many as 29 different machine learning models belonging to seven architectures were explored to develop lean manufacturing soft sensors. These soft sensors were trained to classify the auto firms into high, medium or low levels of lean manufacturing based on their manufacturing flexibilities. The seven machine learning architectures included Decision Trees, Discriminants, Naive Bayes, Support Vector Machine (SVM), K-nearest neighbour (KNN), Ensembles, and Neural Networks (NN). The performances of all models were compared on the basis of their respective training, validation, testing accuracies, and computation timespans. Primary results indicate that the neural network architectures provided the best lean manufacturing predictions, followed by Trees, SVM, Ensembles, KNN, Naive Bayes, and Discriminants. The trilayered neural network architecture attained the highest testing prediction accuracy of 80%. The fine, medium, and coarse trees attained the testing accuracy of 60%, as did the quadratic and cubic SVMs, the wide and narrow neural networks, and the ensemble RUSBoosted trees. Remaining models obtained inferior testing accuracies. The best performing model was further analysed by scatter plots of predicted LM classes versus flexibilities, validation and testing confusion matrices, receiver operating characteristics (ROC) curves, and the parallel coordinate plot for identifying manufacturing flexibility trends for the predicted LM levels. Thus, machine learning models can be used to create effective soft sensors that can predict the level of lean manufacturing of an enterprise based on the levels of its manufacturing flexibilities.

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Fleck, Sven, Benjamin May, Gwen Daniel, and Chris Davies. "Data driven degradation of automotive sensors and effect analysis." Electronic Imaging 2021, no. 17 (January 18, 2021): 180–1. http://dx.doi.org/10.2352/issn.2470-1173.2021.17.avm-180.

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Autonomous driving plays a crucial role to prevent accidents and modern vehicles are equipped with multimodal sensor systems and AI-driven perception and sensor fusion. These features are however not stable during a vehicle’s lifetime due to various means of degradation. This introduces an inherent, yet unaddressed risk: once vehicles are in the field, their individual exposure to environmental effects lead to unpredictable behavior. The goal of this paper is to raise awareness of automotive sensor degradation. Various effects exist, which in combination may have a severe impact on the AI-based processing and ultimately on the customer domain. Failure mode and effects analysis (FMEA) type approaches are used to structure a complete coverage of relevant automotive degradation effects. Sensors include cameras, RADARs, LiDARs and other modalities, both outside and in-cabin. Sensor robustness alone is a well-known topic which is addressed by DV/PV. However, this is not sufficient and various degradations will be looked at which go significantly beyond currently tested environmental stress scenarios. In addition, the combination of sensor degradation and its impact on AI processing is identified as a validation gap. An outlook to future analysis and ways to detect relevant sensor degradations is also presented.

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Datlinger, Christoph, and Mario Hirz. "Benchmark of Rotor Position Sensor Technologies for Application in Automotive Electric Drive Trains." Electronics 9, no. 7 (June 28, 2020): 1063. http://dx.doi.org/10.3390/electronics9071063.

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Rotor shaft position sensors are required to ensure the efficient and reliable control of Permanent Magnet Synchronous Machines (PMSM), which are often applied as traction motors in electrified automotive powertrains. In general, various sensor principles are available, e.g., resolvers and inductive- or magnetoresistive sensors. Each technology is characterized by strengths and weaknesses in terms of measurement accuracy, space demands, disturbing factors and costs, etc. Since the most frequently applied technology, the resolver, shows some weaknesses and is relatively costly, alternative technologies have been introduced during the past years. This paper investigates state-of-the-art position sensor technologies and compares their potentials for use in PMSM in automotive powertrain systems. The corresponding evaluation criteria are defined according to the typical requirements of automotive electric powertrains, and include the provided sensor accuracy under the influence of mechanical tolerances and deviations, integration size, and different electrical- and signal processing-related parameters. The study presents a mapping of the potentials of different rotor position sensor technologies with the target to support the selection of suitable sensor technologies for specified powertrain control applications, addressing both system design and components development.

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Prosser, S. J. "Automotive sensors: past, present and future." Journal of Physics: Conference Series 76 (July 1, 2007): 012001. http://dx.doi.org/10.1088/1742-6596/76/1/012001.

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Mukundan, R., Eric L. Brosha, Fernando Garzon, Robert Novak, and Rick Soltis. "Nitrogen Oxide Sensors For Automotive Applications." ECS Transactions 3, no. 10 (December 21, 2019): 195–202. http://dx.doi.org/10.1149/1.2357259.

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Skaria, Sruthy, Akram Al-Hourani, Robin J. Evans, Kandeepan Sithamparanathan, and Udaya Parampalli. "Interference Mitigation in Automotive Radars Using Pseudo-Random Cyclic Orthogonal Sequences." Sensors 19, no. 20 (October 15, 2019): 4459. http://dx.doi.org/10.3390/s19204459.

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The number of small sophisticated wireless sensors which share the electromagnetic spectrum is expected to grow rapidly over the next decade and interference between these sensors is anticipated to become a major challenge. In this paper we study the interference mechanisms in one such sensor, automotive radars, where our results are directly applicable to a range of other sensor situations. In particular, we study the impact of radar waveform design and the associated receiver processing on the statistics of radar–radar interference and its effects on sensing performance. We propose a novel interference mitigation approach based on pseudo-random cyclic orthogonal sequences (PRCOS), which enable sensors to rapidly learn the interference environment and avoid using frequency overlapping waveforms, which in turn results in a significant interference mitigation with analytically tractable statistical characterization. The performance of our new approach is benchmarked against the popular random stepped frequency waveform sequences (RSFWS), where both simulation and analytic results show considerable interference reduction. Furthermore, we perform experimental measurements on commercially available automotive radars to verify the proposed model and framework.

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Daves, Glenn G. "Trends in Automotive Packaging." Additional Conferences (Device Packaging, HiTEC, HiTEN, and CICMT) 2014, DPC (January 1, 2014): 001818–50. http://dx.doi.org/10.4071/2014dpc-keynote_th1_daves.

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The long-term trend in automobiles has been increasing electronics content over time. This trend is expected to continue and drives diverse functional, form factor, and reliability requirements. These requirements, in turn, are leading to changes in the package types selected and the performance specifications of the packages used for automotive electronics. Several examples will be given. This abstract covers the development of a distributed high temperature electronics demonstrator for integration with sensor elements to provide digital outputs that can be used by the FADEC (Full Authority Digital Electronic Control) system or the EHMS (Engine Health Monitoring System) on an aircraft engine. This distributed electronics demonstrator eliminates the need for the FADEC or EHMS to process the sensor signal, which will assist in making the overall system more accurate and efficient in processing only digital signals. This will offer weight savings in cables, harnesses and connector pin reduction. The design concept was to take the output from several on-engine sensors, carry out the signal conditioning, multiplexing, analogue to digital conversion and data transmission through a serial data bus. The unit has to meet the environmental requirements of DO-160 with the need to operate at 200°C, with short term operation at temperatures up to 250°C. The work undertaken has been to design an ASIC based on 1.0 μm Silicon on Insulator (SOI) device technology incorporating sensor signal conditioning electronics for sensors including resistance temperature probes, strain gauges, thermocouples, torque and frequency inputs. The ASIC contains analogue multiplexers, temperature stable voltage band-gap reference and bias circuits, ADC, BIST, core logic, DIN inputs and two parallel ARINC 429 serial databuses. The ASIC was tested and showed to be functional up to a maximum temperature of 275°C. The ASIC has been integrated with other high temperature components including voltage regulators, a crystal oscillator, precision resistors, silicon capacitors within a hermetic hybrid package. The hybrid circuit has been assembled within a stainless steel enclosure with high temperature connectors. The high temperature electronics demonstrator has been demonstrated operating from −40°C to +250°C. This work has been carried out under the EU Clean Sky HIGHTECS project with the Project being led by Turbomeca (Fr) and carried out by GE Aviation Systems (UK), GE Research – Munich (D) and Oxford University (UK).

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Essl, Christiane, Lauritz Seifert, Michael Rabe, and Anton Fuchs. "Early Detection of Failing Automotive Batteries Using Gas Sensors." Batteries 7, no. 2 (April 12, 2021): 25. http://dx.doi.org/10.3390/batteries7020025.

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Safety for automotive lithium-ion battery (LIB) applications is of crucial importance, especially for electric vehicle applications using batteries with high capacity and high energy density. In case of a defect inside or outside the cell, serious safety risks are possible including extensive heat generation, toxic and flammable gas generation, and consequently fire and explosion. New regulations (GB 38031-2020) require a warning for passengers at least five minutes before serious incidents. This regulation can hardly be fulfilled with state-of-the-art battery monitoring. In this study, gases produced during battery failure before and during a thermal runaway (TR) are investigated in detail and the use of different gas sensors as early detectors of battery incidents is tested and proposed. The response of several commercially available gas sensors is tested in four battery failure cases: unwanted electrolysis of voltage carrying parts, electrolyte vapor, first venting of the cell and the TR. The experiments show that battery failure detection with gas sensors is possible but depends highly on the failure case. The chosen gas sensor can detect H2 produced by unwanted electrolysis and electrolyte vapor and gases produced by degassing of state-of-the-art LIBs. The results may contribute significantly to failure detection and improvement of battery safety.

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Hudec, Premysl, and Viktor Adler. "On the Testing of Advanced Automotive Radar Sensors by Means of Target Simulators." Sensors 20, no. 9 (May 9, 2020): 2714. http://dx.doi.org/10.3390/s20092714.

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The rapid development and wide commercial implementation of automotive radar sensors are strengthening the already considerable interest in matching radar target simulators. Such simulators boast promising results when used for both essential functional inspections of active sensors and the high-speed testing of numerous traffic scenarios while examining complex reactions of automobile electronic systems. For these purposes, advanced versions of target simulators enabling a generation of multiple targets moving at different velocities and ranges are required. The design, practical implementation and system programming of advanced sensor simulator setups require a detailed analytical description concerning all important technical aspects. An abundance of detailed information on the behavior and parameters of automotive radar sensors can be found in the references, but similar knowledge on sensor simulator setups is lacking. This article presents detailed analyses of the all-important RF parameters, where special attention is paid to phase noise, and its analytical description takes into account an even greater number of simulated targets. The derived analytical formulas enable both an optimal setup implementation and system programming of a wide range of practical testing procedures.

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Kumari B.M, Kusuma, Sampada Sethi, Ramakanth Kumar P, Nishant Kumar, and Atulit Shankar. "Driver Drowsiness Detection System Using Sensors." International Journal of Informatics and Communication Technology (IJ-ICT) 6, no. 3 (December 1, 2017): 139. http://dx.doi.org/10.11591/ijict.v6i3.pp139-145.

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<p>A low-cost and simple distributed sensors model that is particularly suitable for measuring eye blink of the driver, accident and hand position on a steering wheel. These sensors can be used in automotive active safety systems that aim at detecting driver’s fatigue, a major issue to prevent road accidents. The key point of this approach is to design a prototype of sensor units, so that it can serve as platform for integrating different kinds of sensors into the steering wheel. Since the sensors are attached to the steering wheel, therefore they can’t be detached by the driver. It will also detect dangerous stylish driving which may lead to fatal accidents. The major drawback is that the eye blink sensors frame worn by the driver can be removed causing the sensor non-operational. The outcome is that the vibrator attached to eye blink sensor’s frame vibrates if the driver shuts his eyes for approximately 3 seconds and also the LCD displays the respective warning message. The wheel is slowed or stopped depending on the condition. This is accompanied by the vehicle’s owner being notified through the GSM module, so the owner can retrieve the driver’s location, photograph and a list of nearby police stations through an android mobile application. Therefore, driver can be alerted during drowsiness and the owner can be notified simultaneously.</p>

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Machdi, Agustini Rodiah, and Yamato Tan. "Performance Analysis on Wireless Sensor Network Based on Zigbee Wireless Communication Protocol." JREC (Journal of Electrical and Electronics) 9, no. 2 (January 12, 2022): 25–30. http://dx.doi.org/10.33558/jrec.v9i2.3188.

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This journal discusses the performance analysis of a Wireless Sensor Network (WSN) system based on the Zigbee Wireless Communication protocol. Zigbee in this system is used for sensor communications that do not require high data transmission speeds, such as sensor applications, such as temperature, humidity, light, pressure, and other sensors. The analysis carried out is to examine the QoS of a network system based on the topology used in the Zigbee protocol-based WSN system. The results of the study show that the use of topology is very influential on the availability, stable speed, and accuracy of the data transmitted between these sensors.

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Sequeira, Gerald Joy, Robert Lugner, Ulrich Jumar, and Thomas Brandmeier. "A validation sensor based on carbon-fiber-reinforced plastic for early activation of automotive occupant restraint systems." Journal of Sensors and Sensor Systems 8, no. 1 (January 10, 2019): 19–35. http://dx.doi.org/10.5194/jsss-8-19-2019.

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Abstract. In the automotive industry, sensors and sensor systems are one of the most important components in upcoming challenges like highly automated and autonomous driving. Forward-looking sensors (radar, lidar and cameras) have the technical capability to already provide important (pre-)crash information, such as the position of contact, relative crash velocity and overlap (width of contact) before the crash occurs. Future safety systems can improve crash mitigation with sophisticated vehicle safety strategies based on this information. One such strategy is an early activation of restraint systems compared with conventional passive safety systems. These integrated safety systems consist of a combination of predictive forward-looking sensors and occupant restraint systems (airbags, belt tensioners, etc.) to provide the best occupant safety in inevitable crash situations. The activation of the restraint systems is the most critical decision process and requires a very robust validation system to avoid false activation. Hence, the information provided by the forward-looking sensor needs to be highly reliable. A validation sensor is required to check the plausibility of crucial information from forward-looking sensors used in integrated safety systems for safe automated and autonomous driving. This work presents a CFRP-based (carbon-fiber-reinforced plastic) validation sensor working on the principle of change in electrical resistance when a contact occurs. This sensor detects the first contact, gives information on impact position (where the contact occurs) and provides information on the overlap. The aim is to activate the vehicle restraint systems at near T0 (time of first contact). Prototypes of the sensor were manufactured in house and manually and were evaluated. At first, the sensor and its working principle were tested with a pendulum apparatus. In the next stage, the sensor was tested in a real crash test. The comparison of the signals from the CFRP-based sensor with presently used crash sensors in the vehicle highlights its advantages. The crash event can be identified at 0.1 ms after the initial contact. The sensor also provides information on impact position at 1.2 ms and enables a validation of the overlap development. Finally, a possible algorithm for the vehicle safety system using forward-looking sensors with a validation sensor is described.

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Lim, Hyung-Sok, and Choul-Young Kim. "ISO26262-Compliant Inductive Long-Stroke Linear-Position Sensors as an Alternative to Hall-Based Sensors for Automotive Applications." Sensors 23, no. 1 (December 26, 2022): 245. http://dx.doi.org/10.3390/s23010245.

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To ensure safety, vehicle companies require position sensors that maintain accuracy and avoid target loss even in harsh automotive environments. Most vehicle position sensors are Hall-based, but even improved gradiometric 3D Hall sensors using the arctangent operation are vulnerable to external magnetic fields (EXMFs) and encounter difficulty at long-stroke (LS) positions. An ISO26262-compliant inductive position sensor (IPS) employing a 3.5 MHz-induced magnetic field source (much higher in frequency than vehicle–environment EXMFs) is proposed in this study as an alternative. To meet the safety goal, a threshold LS distance of 12 mm was set. Then the IPS was compared to existing Hall-based sensors. The B field of the existing 3D sensor was weak at LS and the airgap between sensor face and magnet target caused a large error in accuracy, whereas the IPS was not affected by LS. Because of its high excitation frequency, the IPS was also largely unaffected by EXMFs, as was demonstrated by ISO11452-8 and 0.1 T immunity tests. The proposed IPS outperformed existing 3D Hall sensors, achieving stable accuracy within ±0.85% for different airgaps (1.5–2.5 mm) and proving robust to magnetic and LS effects.

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Zhao, Yu, Zhi Wei Guan, and Feng Du. "Design of Automotive Intelligent Preloaded Safety Belt." Advanced Materials Research 1046 (October 2014): 219–22. http://dx.doi.org/10.4028/www.scientific.net/amr.1046.219.

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This paper introduces the significance of automotive safety belt, designs intelligent preloaded safety belt system. The system is made up of early warning sensors, seat belt furl system and core controller based on the MC9S12DP256. This article focuses on the structural optimization and circuit design of the controller. The designed test-bed is able to predict the dangerous occurrence and control the safety belt tightening through processing early warning signal of the sensor, implements the safety belt active preload function and meet the needs of active safety.

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Sugawara, Tsutomu, Hiroshi Matsumoto, Hiroki Ito, Shingo Sato, and Masanari Kokubu. "Co-fired Platinum High Temperature Sensor Element." Additional Conferences (Device Packaging, HiTEC, HiTEN, and CICMT) 2016, HiTEC (January 1, 2016): 000056–60. http://dx.doi.org/10.4071/2016-hitec-56.

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Abstract In recent years, initiatives for improving the fuel consumptions have been accelerated to reduce the CO2 emissions in exhaust gas from an automotive engine; as a measure against global warming. One of the known techniques to reduce CO2 emissions, is more accurate temperature measurement of the engine. For such application, sensors such as thermistors or thin-film platinum temperature sensors have been widely used for sensing exhaust gas temperature. Especially, the thin-film platinum temperature sensors were favorable because of its linearity in resistance to temperature dependensy and accuracy in temperature measurements. However, the deformation of a resistor circuit in thin-film platinum temperature sensor elements have been observed after used in high temperature. The deformation causes the resistance drifts which leads to less accurate temperature measurements. In this study, durability of the co-fired platinum temperature sensor element was examined for high temperature application. As of result, we found that the resistance drift of the co-fired platinum temperature sensor elements were smaller than that of the thin-film platinum temperature sensor elements; after storage test at 1100 °C. Thus, the co-fired platinum temperature sensor elements can be used for higher temperature sensing, which can contribute to the reduction of CO2 emission of automotive engines.

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Journal articles on the topic 'Automotive sensors'

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