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Adaptive Optimal Management Strategy for Hybrid Vehicles Based on Pontryagin’s Minimum Principle
Technical Paper
2020-01-1191
ISSN: 0148-7191, e-ISSN: 2688-3627
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English
Abstract
The energy management strategies (EMS) for hybrid electric vehicles (HEV) have a great impact on the fuel economy (FE). The Pontryagin's minimum principle (PMP) has been proved to be a viable control strategy for HEV. The optimal costate of the PMP control can be determined by the given information of the driving conditions. Since the full knowledge of future driving conditions is not available, this paper proposed a dynamic optimization method for PMP costate without the prediction of the driving cycle. It is known that the lower fuel consumption the method yields, the more efficiently the engine works. The selection of costate is designed to make the engine work in the high efficiency range. Compared with the rule-based control, the proposed method by the principle of Hamiltonian, can make engine working points have more opportunities locating in the middle of high efficiency range, instead of on the boundary of high efficiency range. Besides a hard and soft constraints of battery SOC are defined to balance the control of optimal costate and the working state of battery. Simulations based on the standard driving cycles are conducted to verify the FE performance. The results are compared with other control strategies to show the effect of proposed method in unknown driving condition.
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Citation
Zhu, M., Wu, X., and Xu, M., "Adaptive Optimal Management Strategy for Hybrid Vehicles Based on Pontryagin’s Minimum Principle," SAE Technical Paper 2020-01-1191, 2020, https://doi.org/10.4271/2020-01-1191.Data Sets - Support Documents
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References
- Kim , N. and Rousseau , A.P. Comparison between Rule-Based and Instantaneous Optimization for a Single-Mode, Power-Split HEV SAE Technial Paper 2011-01-0873 2011 https://doi.org/10.4271/2011-01-0873
- Peng , J. , He , H. , and Xiong , R. Rule Based Energy Management Strategy for a Series-Parallel Plug-in Hybrid Electric Bus Optimized by Dynamic Programming Appl. Energy 185 1633 1643 Jan. 2017
- Solouk , A. , Shahbakhtim , M. , and Mahjoob , M. Energy Management and Control of a Hybrid Electric Vehicle with an Integrated Low Temperature Combustion (LTC) Engine Proc. ASME Dyn. Syst. Control Conf San Antonio, TX, USA 2014 V002T20A005
- Onori , S. , Serrao , L. , and Rizzoni , G. Hybrid Electric Vehicles: Energy Management Strategies (SpringerBriefs in Electrical and Computer Engineering) New York, NY, USA Springer 2016
- Vajedi , M. , Taghavipour , A. , Azad , N.L. , and McPhee , J. A Comparative Analysis of Route-Based Power Management Strategies for Real-Time Application in Plug-in Hybrid Electric Vehicles Proc. Amer. Control Conf Portland, OR, USA Jun. 2014 2612 2617
- Tianheng , F. , Lin , Y. , Qing , G. , Yanqing , H. et al. A Supervisory Control Strategy for Plug-In Hybrid Electric Vehicles Based on Energy Demand Prediction and Route Preview IEEE Trans. Veh. Technol. 64 5 1691 1700 May 2015
- Zhang , C. and Vahidi , A. Route Preview in Energy Management of Plugin Hybrid Vehicles IEEE Trans. Control Syst. Technol. 20 2 546 553 Mar. 2012
- Zhang , C. , Vahidi , A. , Pisu , P. , Li , X. , and Tennant , K. Role of Terrain Preview in Energy Management of Hybrid Electric Vehicles IEEE Trans. Veh. Technol. 59 3 1139 1147 Mar. 2010
- Sciarretta , A. , Back , M. , and Guzzella , L. Optimal Control of Parallel Hybrid Electric Vehicles IEEE Trans. Control Syst. Technol. 12 3 352 363 May 2004
- Hu , Y. , Yang , L. , Yan , B. , Yan , T. , and Ma , P. An Online Rolling Optimal Control Strategy for Commuter Hybrid Electric Vehicles Based on Driving Condition Learning and Prediction IEEE Trans. Veh. Technol. 65 6 4312 4327 Jun. 2016
- Chasse , A. , Sciarretta , A. , and Chauvin , J. Online Optimal Control of a Parallel Hybrid with Costate Adaptation Rule IFAC Proceedings Volumes 43 7 99 104 2010
- Chasse , A. , Hafidi , G. , Pognant-Gros , P. , and Sciarretta , A. Supervisory Control of Hybrid Powertrains: An Experimental Benchmark of Offline Optimization and Online Energy Management IFAC Proceedings Volumes 42 26 109 117 2011
- Kim , N. , Cha , S. , and Peng , H. Optimal Control of Hybrid Electric Vehicles Based on Pontryagin’s Minimum Principle IEEE Trans. Control Syst. Technol. 19 5 1279 1287 Sep. 2011
- Jiang , Q. , Ossart , F. , and Marchand , C. Comparative Study of Real-Time HEV Energy Management Strategies IEEE Trans. Control Syst. Technol. 66 12 10879 10888 Dec. 2017
- Rezaei , A. , Burl , J.B. , and Zhou , B. Estimation of the ECMS Equivalent Factor Bounds for Hybrid Electric Vehicles IEEE Trans. Control Syst. Technol. 26 6 2198 2205 Nov. 2018
- Rezaei , A. , Zhou , J.B. , and Rezaei , M. A New Real-Time Optimal Energy Management Strategy for Parallel Hybrid Electric Vehicles IEEE Trans. Control Syst. Technol. 27 27 830 837 Mar. 2019
- Guan , J. , Chen , B. , Huang , Y. and Chiu , Y. Adaptive Power Management Strategy for Hybrid Electric Vehicle with Belt-driven Starter Generator Proceedings of 2015 IEEE 12th International Conference on Networking, Sensing and Control Apr 2015
- Huang , Y. , Wang , H. , Khajepour , A. , He , H. , and Ji , J. Model Predictive Control Power Management Strategies for HEVs: A Review J. Power Sources 341 91 106 Feb. 2017
- Solouk , A. and Shahbakhti , M. Energy Optimization and Fuel Economy Investigation of a Series Hybrid Electric Vehicle Integrated with Diesel/RCCI Engines Energies 9 12 1020 2016