Modelling and fuzzy logic based control scheme for a series hybrid electric vehicle

Year 2023, Volume: 7 Issue: 1, 106 - 120, 31.03.2023

Latif Kasım Uysal , Necmi Altın

https://doi.org/10.30521/jes.1107190

Cited By: 1

Abstract

Ever stricter emission regulations, declining petroleum resources, increasing pollution, and global warming triggered an interest in e-mobility. Although fully electrified transportation is targeted, hybrid electric vehicles have become attractive during this transition period due to reasons such as battery challenges, range anxiety, grid capacity, and charging infrastructure. Hybrid electrical vehicles require challenging energy management systems due to the increasing number of components and energy conversions. This paper aims to introduce a simple yet effective control scheme to control the battery state-of-charge (SOC) and regenerative braking of a hybrid electric vehicle. For this purpose, a fuzzy logic controller is developed, three inputs as the SOC, driver demand, and vehicle velocity are defined. Instead of torque or power requirement, which are commonly used as controller inputs in the literature, a more straightforward method is adopted by using the accelerator and brake pedal positions. The controller manages the engine power and regenerative braking intensity. A series hybrid electric vehicle model is created in the MATLAB/Simulink environment to validate the performance of the proposed controller. The proposed controller aims to keep the SOC between 30-40% after charge depleting mode, and ensures prevention of regenerative braking at high SOC values to prevent overcharging. Simulations have been performed according to NEDC and WLTC, show that the proposed controller is able to realize design objectives.

Keywords

Energy management, Fuzzy logic control, Modeling, Series hybrid electric vehicle

References

• [1] Shafikhani, I, Sundström, C, Åslund, J, Frisk, E. MPC-based energy management system design for a series HEV with battery life optimization. In: 2021 European Control Conference (ECC). 29 June-2 July 2021.IEEE, Delft, Netherlands: pp. 2591-2596. DOI: 10.23919/ECC54610.2021.9655224
• [2] Cheng, M, B. Chen, Nonlinear Model Predictive Control of a Power-Split Hybrid Electric Vehicle with Consideration of Battery Aging. Journal of Dynamic Systems, Measurement, and Control 2019;141(8): 081008.DOI: 10.1115/1.4042954
• [3] Johanyák, Z, Ailer, PG, Göcs, L. A Simple Fuzzy Logic Based Power Control for a Series Hybrid Electric Vehicle.In: 6th International Scientific and Expert Conference of the International TEAM Society;6-8 Oct. 2015: Kecskemet, Hungary: pp. 207-212
• [4] Liu, X, Fan, Q, Zheng, K, Duan, J, Wang, Y. Constant SOC control of a series Hybrid Electric Vehicle with long driving range. In: 2010 IEEE International Conference on Information and Automation; 20-23 June 2010: IEEE, Harbin, China:pp. 1603-1608. DOI: 10.1109/ICINFA.2010.5512260.
• [5] Mahyiddin, S.H., Mohamed, M. R., Mustaffa, Z.,Khor, A. C., Sulaiman, M. H., Ahmad, H., Rahman, S. A.Fuzzy logic energy management system of series hybrid electric vehicle. In: 4th IET Clean Energy and Technology Conference (CEAT 2016); 14-15 Nov. 2016:Kuala Lumpur, Malaysia: Institution of Engineering and Technology, pp. 1-6.DOI: 10.1049/cp.2016.1267.
• [6] Li, S.G., Sharkh, S. M., Walsh, F.C., Zhang, C.N. Energy and Battery Management of a Plug-In Series Hybrid Electric Vehicle Using Fuzzy Logic. IEEE Transactions on Vehicular Technology 2011; 60(8):3571-3585.DOI: 10.1109/TVT.2011.2165571.
• [7] Sher, F., Chen, S., Raza, A., Rasheed, T., Razmkhah, O., Rashid, T., Rafi-ul-Shan, P.M., Erten, B. Novel strategies to reduce engine emissions and improve energy efficiency in hybrid vehicles. Cleaner Engineering and Technology 2021; 2: 100074. DOI: 10.1016/j.clet.2021.100074.
• [8] Phan, D., Bab-Hadiashar, A., Fayyazi, M., Hoseinnezhad, R., Jazar, R.N., Khayyam, H. Interval Type 2 Fuzzy Logic Control for Energy Management of Hybrid Electric Autonomous Vehicles. IEEE Transactions on Intelligent Vehicles 2021; 6(2): 210-220. DOI: 10.1109/TIV.2020.3011954.
• [9] Singh, K, Bansal, H, Singh, D. Feed-forward modeling and real-time implementation of an intelligent fuzzy logic-based energy management strategy in a series–parallel hybrid electric vehicle to improve fuel economy. Electrical Engineering 2020; 102: 967–987. DOI: 10.1007/s00202-019-00914-6
• [10] Zhang, H, Cao, D, Du, H. Modeling, Dynamics and Control of Electrified Vehicles.NSW, Australia; Woodhead Publishing, 2017, pp. 123,168.
• [11] Ehsani, M, Gao, Y, Emadi, A. Modern Electric, Hybrid Electric, and Fuel Cell Vehicles: Fundamentals, Theory, and Design. Boca Raton: CRC Press, 2010. pp. 254-258.
• [12] Zhang, P, Yan, F, Du, C. A comprehensive analysis of energy management strategies for hybrid electric vehicles based on bibliometrics. Renewable and Sustainable Energy Reviews 2015;48: 88-104. DOI: 10.1016/j.rser.2015.03.093
• [13] Bhaskar, P.B., Deshmukh, S., Khannan, P., Shaik, A.Recent Trends on Drivetrain Control Strategies and Battery Parameters of a Hybrid Electric Vehicle.SAE International2019; 1-12. DOI: 10.4271/2019-28-0155
• [14] Basma, H., Mansour, C., Halaby, H., Baz Radwan, A.Methodology to Design an Optimal Rule-Based Energy Management Strategy Using Energetic Macroscopic Representation: Case of Plug-In Series Hybrid Electric Vehicle.Advances in Automobile Engineering 2018; 7(3): pp. 1000188-1000188.DOI: 10.4172/2167-7670.1000188.
• [15] Zhang, B., Zhang, J., Xu, F., Shen, T. Optimal control of power-split hybrid electric powertrains with minimization of energy consumption. Applied Energy 2020; 266: 114873. DOI: 10.1016/j.apenergy.2020.114873.
• [16] Bayındır, K, Gözüküçük, M, Teke, A. A comprehensive overview of hybrid electric vehicle: Powertrain configurations, powertrain control techniques and electronic control units. Energy Conversion and Management 2011; 52: 1305-1313.DOI: 10.1016/j.enconman.2010.09.028.
• [17] Chen, Z, Zhang, X, Mi, CC. Slide Mode and Fuzzy Logic Based Powertrain Controller for the Energy Management and Battery Lifetime Extension of Series Hybrid Electric Vehicles. Journal of Asian Electric Vehicles 2010;8(2): 1425-1432.DOI: 10.4130/jaev.8.1425.
• [18] Shabbir, W, Evangelou, SA. Threshold-changing control strategy for series hybrid electric vehicles. Applied Energy 2019; 235: 761-775. DOI: 10.1016/j.apenergy.2018.11.003.
• [19] Zoroofi, S. Modeling and Simulation of Vehicular Power Systems.MSc, Chalmers University of Technology, Göteborg, Sweden, 2008.
• [20] Onori, S, Tribioli, L. Adaptive Pontryagin’s Minimum Principle supervisory controller design for the plug-in hybrid GM Chevrolet Volt. Applied Energy 2015; 147: 224-234. DOI: 10.1016/j.apenergy.2015.01.021.
• [21] Pan, C, Wang, J., Dai, W., Chen, L., Chen, L. Constant current control for regenerative braking of passive series hybrid power system. International Transactions on Electrical Energy Systems 2020; 30(11): e12577. DOI: 10.1002/2050-7038.12577.
• [22] Grebe, UD, Nitz, LT. Voltec – The Propulsion System for Chevrolet Volt and Opel Ampera. ATZ Auto Technology 2011; 11(2): 28-35.
• [23] Muratoğlu, Y, Alkaya, A. Elektrikli Araç Teknolojisi ve Pil Yönetim Sistemi – İnceleme [Electric Vehicle Technology and Battery Management System – Review]. Elektrik Mühendisliği 2016; 458: 10-14.
• [24] Lim, D.Y., Im, J.K., Choi, J.H., Chung, G.B.PSIM Simulator for Analysis of Series HEV Operation. The Transactions of the Korean Institute of Power Electronics 2010; 15(6):487-497. DOI: 10.6113/TKPE.2010.15.6.487.
• [25] Omar, N., Widanage, D., Abdel Monem, M., Firouz, Y., Hegazy, O., Van den Bossche, P., Coosemans, T., Van Mierlo, J. Optimization of an advanced battery model parameter minimization tool and development of a novel electrical model for lithium-ion batteries. International Transactions on Electrical Energy Systems 2014; 24(12): 1747-1767. DOI: 10.1002/etep.1815.
• [26] Wang, Y., Tian, J., Sun, Z., Wang, L., Xu, R., Li, M., Chen, Z. A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems. Renewable and Sustainable Energy Reviews 2020; 131: 110015. DOI: 10.1016/j.rser.2020.110015.
• [27] Manthopoulos, A, Wang, X. A Review and Comparison of Lithium-Ion Battery SOC Estimation Methods for Electric Vehicles. In: IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society,18-21 October 2020: IEEE, Singapore: pp. 2385-2392.
• [28] Jongerden, M, Haverkort, BR. Battery Modeling. Enschede, Holland:Centre for Telematics and Information Technology, University of Twente, 2008.
• [29] Williamson, S., Energy Management Strategies for Electric and Plug-in Hybrid Electric Vehicles. New York,USA: Springer,2013.
• [30] Chen, B, Evangelou, SA, Lot, R. Series Hybrid Electric Vehicle Simultaneous Energy Management and Driving Speed Optimization. IEEE/ASME Transactions on Mechatronics 2019; 24(6): 2756-2767. DOI: 10.1109/TMECH.2019.2943320.