Energy Management Strategy for Hybrid Energy Storage System based on Model Predictive Control

Journal of Electrical Engineering & Technology - Tập 18 - Trang 3265-3275 - 2023
Yongpeng Shen1, Yuanfeng Li1, Dongqi Liu2, Yanfeng Wang1, Jianbin Sun1, Songnan Sun1
1Department of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, China
2Department of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, China

Tóm tắt

Electric vehicle (EV) is developed because of its environmental friendliness, energy-saving and high efficiency. For improving the performance of the energy storage system of EV, this paper proposes an energy management strategy (EMS) based model predictive control (MPC) for the battery/supercapacitor hybrid energy storage system (HESS), which takes stabilizing the DC bus voltage and improving the efficiency of the system as two major optimization goals. In addition, an enumeration algorithm is presented to solve the optimization function. The experimental results show the performance of the proposed EMS which is able to enhance the overall instantaneous power and prevent the battery from overloading. Meanwhile, compared with the results of a single battery storage system, the maximum amplitude of the battery current in the HESS is reduced by 40.81% and whole system energy loss is reduced by 24.13% with the proposed power management strategy.

Tài liệu tham khảo

Shen Y, Li Y, Tang Y et al (2022) An energy management strategy based on fuzzy logic for hybrid energy storage system in electric vehicles. IEEJ Trans Electr Electron Eng 17(1):53–60 Su W, Eichi H, Zeng W et al (2011) A survey on the electrification of transportation in a smart grid environment. IEEE Trans Industr Inf 8(1):1–10 Shen Y, Sun S, Li Y et al (2022) Closed–loop haar wavelet power splitting method for vehicle–mounted hybrid energy storage system. IEEJ Transact Elect Electron Eng 18(2):235–242 Shen J, Dusmez S, Khaligh A (2014) Optimization of sizing and battery cycle life in battery/ultracapacitor hybrid energy storage systems for electric vehicle applications. IEEE Trans Industr Inf 10(4):2112–2121 Shen J, Khaligh A (2016) Design and real-time controller implementation for a battery-ultracapacitor hybrid energy storage system. IEEE Transact Industrial Inform 12(5):1910–1918 Shen Y, Zheng Z, Wang Q et al (2020) DC bus current sensed space vector pulsewidth modulation for three-phase inverter. IEEE Transact Transport Elect 7(2):815–824 Shen Y, Wang Q, Liu D et al (2021) A mixed SVPWM technique for three-phase current reconstruction with single DC negative rail current sensor. IEEE Trans Power Electron 37(5):5357–5372 Shen Y, He T, Wang Q et al (2022) Secure transmission and intelligent analysis of demand-side data in smart grids-A 5G NB-IoT framework. Front Energy Res 585:2586. https://doi.org/10.3389/fenrg.2022.892066 Kouchachvili L, Yaïci W, Entchev E (2018) Hybrid battery/supercapacitor energy storage system for the electric vehicles. J Power Sources 374:237–248 Tie SF, Tan CW (2013) A review of energy sources and energy management system in electric vehicles. Renew Sustain Energy Rev 20:82–102 Hu KW, Yi PH, Liaw CM (2015) An EV SRM drive powered by battery/supercapacitor with G2V and V2H/V2G capabilities. IEEE Trans Industr Electron 62(8):4714–4727 Borhan H A, Vahidi A (2010) Model predictive control of a power-split hybrid electric vehicle with combined battery and ultracapacitor energy storage. In Proceedings of the 2010 American control conference (pp. 5031–5036), IEEE. Mardani MM, Khooban MH, Masoudian A et al (2018) Model predictive control of DC–DC converters to mitigate the effects of pulsed power loads in naval DC microgrids. IEEE Trans Industr Electron 66(7):5676–5685 Choi ME, Lee JS, Seo SW (2014) Real-time optimization for power management systems of a battery/supercapacitor hybrid energy storage system in electric vehicles. IEEE Trans Veh Technol 63(8):3600–3611 Shen Y, Liu D, Liang W et al (2022) Current reconstruction of three-phase voltage source inverters considering current ripple. IEEE Transact Transport Elect. https://doi.org/10.1109/TTE.2022.3199431 Shen Y, Liu D, Liu P et al (2022) Error self-calibration of phase current reconstruction based on random pulse width modulation. IEEE J Emerg Select Top Power Electron 10(6):7502–7513 Bentley P, Stone DA, Schofield N (2005) The parallel combination of a VRLA cell and supercapacitor for use as a hybrid vehicle peak power buffer. J Power Sources 147(1–2):288–294 Zhang Q, Li G (2019) Experimental study on a semi-active battery-supercapacitor hybrid energy storage system for electric vehicle application. IEEE Trans Power Electron 35(1):1014–1021 Lu X, Chen Y, Fu M et al (2019) Multi-objective optimization-based real-time control strategy for battery/ultracapacitor hybrid energy management systems. IEEE Access 7:11640–11650 Wang L, Wang Y, Liu C et al (2019) A power distribution strategy for hybrid energy storage system using adaptive model predictive control. IEEE Trans Power Electron 35(6):5897–5906 Khan MMS, Faruque MO, Newaz A (2017) Fuzzy logic based energy storage management system for MVDC power system of all electric ship. IEEE Trans Energy Convers 32(2):798–809 Divva R, Prasad V (2019). Fuzzy logic management of hybrid energy storage system. In 2019 4th international conference on recent trends on electronics, information, communication & technology (RTEICT) , IEEE. Shabbir W, Evangelou SA (2019) Threshold-changing control strategy for series hybrid electric vehicles. Appl Energy 235:761–775 Wang Y, Sun Z, Chen Z (2019) Energy management strategy for battery/supercapacitor/fuel cell hybrid source vehicles based on finite state machine. Appl Energy 254:113707 Shen Y, Sun J, Yang X, et al (2020). Symlets wavelet transform based power management of hybrid energy storage system. In 2020 IEEE 4th conference on energy internet and energy system integration (EI2) , IEEE. Moreno J, Ortúzar ME, Dixon JW (2006) Energy-management system for a hybrid electric vehicle, using ultracapacitors and neural networks. IEEE Trans Industr Electron 53(2):614–623 Alaoui C (2019). Hybrid vehicle energy management using deep learning. In 2019 International conference on intelligent systems and advanced computing sciences (ISACS) , IEEE. Shen J, Khaligh A (2015) A supervisory energy management control strategy in a battery/ultracapacitor hybrid energy storage system. IEEE Transact Transport Elect 1(3):223–231 Akar F, Tavlasoglu Y, Vural B (2016) An energy management strategy for a concept battery/ultracapacitor electric vehicle with improved battery life. IEEE Transact Transport Electrif 3(1):191–200 Golchoubian P, Azad NL (2017) Real-time nonlinear model predictive control of a battery–supercapacitor hybrid energy storage system in electric vehicles. IEEE Trans Veh Technol 66(11):9678–9688 Zhai C, Luo F, Liu Y (2020) A novel predictive energy management strategy for electric vehicles based on velocity prediction. IEEE Trans Veh Technol 69(11):12559–12569 Chen S, Yang Q, Zhou J et al (2020) A model predictive control method for hybrid energy storage systems. CSEE Journal of Power and Energy Systems 7(2):329–338