Recent Developments and Applications in The Vehicular Embedded System Technologies

Authors

  • Bhaskar Roy Assistant Professor, Department of ECE, Asansol Engineering College

Keywords:

In-vehicle embedded electronic architecture, FPGA, real-time assessment

Abstract

In the last two decades, the no. of the computer-based features incorporated in automobiles has increased significantly. Even though vehicle manufacturing is expected to rise modestly in the next years, the embedded electronics, and specifically embedded software, is rising. In addition, hardware components' quality and performance are improving whereas their price is declining. Many novel functionalities that would be prohibitively expensive or impossible to implement using the mechanical as well as hydraulic technology may now be implemented using the software technology, thus addressing the end user's needs in the terms of safety as well as comfort. Customers can now purchase a secure, effective, and customised vehicle owing to such technologies, whereas carmakers seem to be able to the master product differentiation as well as the innovation. Several studies have indeed been undertaken to improve embedded system design and the newest technologies to create smart automobiles, which are reviewed in this article. DSPs, ASICs, FPGAs, as well as other microprocessor-based embedded systems are only a few of the many options out now (field-programmable gate arrays). There has been a lot of recent discussion on the use of AI (artificial intelligence) as well as fuzzy logic controllers in automobiles.

References

[1] Abu Hanifah, R., Toha, S. F., Hassan, M. K., & Ahmad, S. (2016). Power reduction optimization with swarm based technique in electric power assist steering system. Energy, 102, 444-452. https://doi.org/10.1016/j.energy.2016.02.050

[2] Ahmed, M., Zheng, Y., Amine, A., Fathiannasab, H., & Chen, Z. (2021). The role of artificial intelligence in the mass adoption of electric vehicles. Joule, 5(9), 2296-2322. https://doi.org/10.1016/j.joule.2021.07.012

[3] Bucaioni, A., Addazi, L., Cicchetti, A., Ciccozzi, F., Eramo, R., Mubeen, S., & Sjodin, M. (2018). MoVES: A model-driven methodology for vehicular embedded systems. IEEE Access, 6(c), 6424-6445. https://doi.org/10.1109/ACCESS.2018.2789400

[4] Chen, A., Zhang, X., & Zhou, Z. (2020). Machine learning: Accelerating materials development for energy storage and conversion. InfoMat, 2(3), 553-576. https://doi.org/10.1002/inf2.12094

[5] Chen, C., Zuo, Y., Ye, W., Li, X., Deng, Z., & Ong, S. P. (2020). A Critical Review of Machine Learning of Energy Materials. Advanced Energy Materials, 10(8), 1-36. https://doi.org/10.1002/aenm.201903242

[6] Chen, J. J., Hu, X. S., Mossé, D., & Thiele, L. (2010). Guest editorial special section on power-aware computing. IEEE Transactions on Industrial Informatics, 6(3), 253. https://doi.org/10.1109/TII.2010.2052390

[7] Chen, Y. L., Chiang, H. H., Chiang, C. Y., Liu, C. M., Yuan, S. M., & Wang, J. H. (2012). A vision-based driver nighttime assistance and surveillance system based on intelligent image sensing techniques and a heterogamous dual-core embedded system architecture. Sensors, 12(3), 2373-2399. https://doi.org/10.3390/s120302373

[8] Choi, J., & Cha, H. (2010). A processor power management scheme for handheld systems considering off-chip contributions. IEEE Transactions on Industrial Informatics, 6(3), 255-264. https://doi.org/10.1109/TII.2010.2050330

[9] Cotton, N. J., & Wilamowski, B. M. (2011). Compensation of nonlinearities using neural networks implemented on inexpensive microcontrollers. IEEE Transactions on Industrial Electronics, 58(3), 733-740. https://doi.org/10.1109/TIE.2010.2098377

[10] Elloy, J. P., & Simonot-Lion, F. (2002). An architecture description language for in-vehicle embedded system development. In IFAC Proceedings Volumes (IFAC-PapersOnline) (Vol. 15, Issue 1). IFAC. https://doi.org/10.3182/20020721-6-ES-1901.00060

[11] Faddel, S., Mohamed, A. A. S., & Mohammed, O. A. (2017). Fuzzy logic-based autonomous controller for electric vehicles charging under different conditions in residential distribution systems. Electric Power Systems Research, 148, 48-58. https://doi.org/10.1016/j.epsr.2017.03.009

[12] Ferrari, P., Flammini, A., Marioli, D., & Taroni, A. (2008). A distributed instrument for performance analysis of real-time ethernet networks. IEEE Transactions on Industrial Informatics, 4(1), 16-25. https://doi.org/10.1109/TII.2008.919016

[13] Grigorescu, S., Trasnea, B., Cocias, T., & Macesanu, G. (2020). A survey of deep learning techniques for autonomous driving. Journal of Field Robotics, 37(3), 362-386. https://doi.org/10.1002/rob.21918

[14] Guo, H., Low, K. S., & Nguyen, H. A. (2011). Optimizing the localization of a wireless sensor network in real time based on a low-cost microcontroller. IEEE Transactions on Industrial Electronics, 58(3), 741-749. https://doi.org/10.1109/TIE.2009.2022073

[15] Hammoudi, K., Benhabiles, H., Kasraoui, M., Ajam, N., Dornaika, F., Radhakrishnan, K., Bandi, K., Cai, Q., & Liu, S. (2015). Developing vision-based and cooperative vehicular embedded systems for enhancing road monitoring services. Procedia Computer Science, 52(1), 389-395. https://doi.org/10.1016/j.procs.2015.05.003

[16] Institute of Electrical and Electronics Engineers. (2012). IEEE A Review of Intelligent Control Techniques Energytech 2012 : May 29-31, 2012, Ohio. 1-5.

https://doi.org/10.1109/EnergyTech.2012.6304679

[17] Ishaque, K., Abdullah, S. S., Ayob, S. M., & Salam, Z. (2011). A simplified approach to design fuzzy logic controller for an underwater vehicle. Ocean Engineering, 38(1), 271-284. https://doi.org/10.1016/j.oceaneng.2010.10.017

[18] Kim, D. (2000). An Implementation of fuzzy logic controller on the reconfigurable fpga system. IEEE Transactions on Industrial Electronics, 47(3), 703-715.https://doi.org/10.1109/41.847911

[19] Li, J., Deng, Y., Wang, Y., Su, C., & Liu, X. (2018). CFD-Based research on control strategy of the opening of Active Grille Shutter on automobile. Case Studies in Thermal Engineering, 12(May), 390-395. https://doi.org/10.1016/j.csite.2018.05.009

[20] Li, X., Gan, C., Gou, K., & Zhang, Y. (2019). A novel WDM-MAN enabling cross-regional reconfiguration and comprehensive protection based on tangent-ring. Optics Communications, 430(July 2018), 416-427. https://doi.org/10.1016/j.optcom.2018.08.065

[21] Marshall, G. J., Mahony, C. P., Rhodes, M. J., Daniewicz, S. R., Tsolas, N., & Thompson, S. M. (2019). Thermal Management of Vehicle Cabins, External Surfaces, and Onboard Electronics: An Overview. Engineering, 5(5), 954-969. https://doi.org/10.1016/j.eng.2019.02.009

[22] Mohammedi, M., Kraa, O., Becherif, M., Aboubou, A., Ayad, M. Y., & Bahri, M. (2014). Fuzzy logic and passivity-based controller applied to electric vehicle using fuel cell and supercapacitors hybrid source. Energy Procedia, 50(0), 619-626. https://doi.org/10.1016/j.egypro.2014.06.076

[23] Monmasson, E., Idkhajine, L., Cirstea, M. N., Bahri, I., Tisan, A., & Naouar, M. W. (2011). FPGAs in industrial control applications. IEEE Transactions on Industrial Informatics, 7(2), 224-243. https://doi.org/10.1109/TII.2011.2123908

[24] Mubeen, S., Ashjaei, M., Nolte, T., Lundback, J., Galnander, M., & Lundback, K. L. (2016). Modeling of End-to-End Resource Reservations in Component-Based Vehicular Embedded Systems. Proceedings - 42nd Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2016, 283-292. https://doi.org/10.1109/SEAA.2016.22

[25] Mubeen, S., Ashjaei, M., & Sjodin, M. (2019). Holistic Modeling of Time Sensitive Networking in Component-Based Vehicular Embedded Systems. Proceedings - 45th Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2019, 131-139. https://doi.org/10.1109/SEAA.2019.00029

[26] Muñoz-castañer, J., Asorey-cacheda, R., Gil-castiñeira, F. J., González-castaño, F. J., & Rodríguez-hernández, P. S. (2011). Parallelism With Automotive Electronics. Control, 58(7), 3090-3100. https://doi.org/10.1109/TIE.2010.2077614

[27] Nag, S., & Lee, K. Y. (2019). Optimized Fuzzy Logic Controller for Responsive Charging of Electric Vehicles. IFAC-PapersOnLine, 52(4), 147-152. https://doi.org/10.1016/j.ifacol.2019.08.170

[28] Parikh, P., Sheth, S., Vasani, R., & Gohil, J. K. (2018). Implementing Fuzzy Logic Controller and PID Controller to a DC Encoder Motor - "a case of an Automated Guided Vehicle." Procedia Manufacturing, 20, 219-226. https://doi.org/10.1016/j.promfg.2018.02.032

[29] Rigas, E. S., Ramchurn, S. D., & Bassiliades, N. (2015). Managing Electric Vehicles in the Smart Grid Using Artificial Intelligence: A Survey. IEEE Transactions on Intelligent Transportation Systems, 16(4), 1619-1635. https://doi.org/10.1109/TITS.2014.2376873

[30] S.Poorani, T.V.S.Urmila Priya, K. U. K. S. R. (2005). Fpga Based Fuzzy Logic Controller for Electric Vehicle. Journal of The Institution of Engineers, Singapore, 45(5), 1.

[31] Sadagopan, V. K., Rajendran, U., & Francis, A. J. (2011). Anti theft control system design using embedded system. Proceedings of 2011 IEEE International Conference on Vehicular Electronics and Safety, ICVES 2011, 1-5. https://doi.org/10.1109/ICVES.2011.5983776

[32] Salewski, F., & Kowalewski, S. (2008). Hardware/software design considerations for automotive embedded systems. IEEE Transactions on Industrial Informatics, 4(3), 156-163. https://doi.org/10.1109/TII.2008.2002919

[33] Simonot-Lion, F. (2009). Guest editorial special section on in-vehicle embedded systems. IEEE Transactions on Industrial Informatics, 5(4), 372-374. https://doi.org/10.1109/TII.2009.2031747

[34] Slowik, A., & Kwasnicka, H. (2020). Evolutionary algorithms and their applications to engineering problems. Neural Computing and Applications, 32(16), 12363-12379. https://doi.org/10.1007/s00521-020-04832-8

[35] Soares, J., Vale, Z., Canizes, B., & Morais, H. (2013). Multi-objective parallel particle swarm optimization for day-ahead Vehicle-to-Grid scheduling. IEEE Symposium on Computational Intelligence Applications in Smart Grid, CIASG, 2012, 138-145. https://doi.org/10.1109/CIASG.2013.6611510

[36] Sun, F., Wang, H., Fu, F., & Li, X. (2010). Survey of FPGA low power design. Proceedings of 2010 International Conference on Intelligent Control and Information Processing, ICICIP 2010, PART 2, 547-550. https://doi.org/10.1109/ICICIP.2010.5565246

[37] Wilamowski, B. M., & Yu, H. (2010). References from online meetings. IEEE Transactions on Neural Networks, 21(6), 930-937. https://doi.org/10.1109/TNN.2010.2045657

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Published

2022-01-06

How to Cite

[1]
Bhaskar Roy 2022. Recent Developments and Applications in The Vehicular Embedded System Technologies. AG Volumes. (Jan. 2022), 41–54.