Computationally Efficient Energy Management in Hybrid Electric Vehicles Based on Approximate Pontryagin's Minimum Principle

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dc.authoridpang, hui/0000-0001-7550-8376
dc.authoridCoskun, Serdar/0000-0002-7080-0340
dc.authoridWang, Lihua/0000-0003-2962-6667
dc.contributor.authorZhang, Fengqi
dc.contributor.authorWang, Lihua
dc.contributor.authorCoskun, Serdar
dc.contributor.authorCui, Yahui
dc.contributor.authorPang, Hui
dc.date.accessioned2025-03-17T12:25:12Z
dc.date.available2025-03-17T12:25:12Z
dc.date.issued2020
dc.departmentTarsus Üniversitesi
dc.description.abstractThis article presents an energy management method for a parallel hybrid electric vehicle (HEV) based on approximate Pontryagin's Minimum Principle (A-PMP). The A-PMP optimizes gearshift commands and torque distribution for overall energy efficiency. As a practical numerical solution in PMP, the proposed methodology utilizes a piecewise linear approximation of the engine fuel rate and state of charge (SOC) derivative by considering drivability and fuel economy simultaneously. Moreover, battery aging is explicitly studied by introducing a control-oriented model, which aims to investigate the effect of battery aging on the optimization performance in the development of the HEVs. An approximate energy management strategy with piecewise linear models is then formulated by the A-PMP, which targets a better performance for the Hamiltonian optimization. The gearshift map is extracted from the optimal results in the standard PMP to hinder frequent gearshift by considering both drivability and fuel economy. Utilizing an approximated Hamilton function, the torque distribution, gearshift command, and the battery aging degradation are jointly optimized under a unified framework. Simulations are performed for dynamic programming (DP), PMP, and A-PMP to validate the effectiveness of the proposed approach. The results indicate that the proposed methodology achieves a close fuel economy compared with the DP-based optimal solution. Moreover, it improves the computation efficiency by 50% and energy saving by 3.5%, compared with the PMP, while ensuring good drivability and fuel efficiency.
dc.description.sponsorshipNational Natural Science Foundation of China [51905419]; Natural Science Basic Research Program in Shaanxi Province of China; Fundamental Research Fund for the Central Universities of China [300102229514]
dc.description.sponsorshipThis work was supported in part by the National Natural Science Foundation of China (Grant No.51905419), the Natural Science Basic Research Program in Shaanxi Province of China (Grant No.2019JQ-503) and the Fundamental Research Fund for the Central Universities of China (Grant No.300102229514).
dc.identifier.doi10.3390/wevj11040065
dc.identifier.issn2032-6653
dc.identifier.issue4
dc.identifier.scopus2-s2.0-85093837879
dc.identifier.scopusqualityQ2
dc.identifier.urihttps://doi.org/10.3390/wevj11040065
dc.identifier.urihttps://hdl.handle.net/20.500.13099/1555
dc.identifier.volume11
dc.identifier.wosWOS:000937479400005
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherMdpi
dc.relation.ispartofWorld Electric Vehicle Journal
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20250316
dc.subjecthybrid electric vehicles
dc.subjectenergy management strategy
dc.subjectPontryagin's minimum principle (PMP)
dc.subjectdrivability
dc.titleComputationally Efficient Energy Management in Hybrid Electric Vehicles Based on Approximate Pontryagin's Minimum Principle
dc.typeArticle

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