Battery durability and longevity based power management for plug-in hybrid electric vehicle with hybrid energy storage system. (1st October 2016)

• Record Type: Journal Article
• Authors: Zhang, Shuo; Xiong, Rui; Cao, Jiayi
• Is Part Of: Applied energy. Volume 179(2016)
• Page Start: 316
• Page End: 328
• Publication Date: 2016-10-01
• Subjects: Battery -- Ultracapacitor -- Hybrid energy storage system -- Dynamic programming -- Power management -- Plug-in hybrid electric vehicle; Power (Mechanics) -- Periodicals; Energy conservation -- Periodicals; Energy conversion -- Periodicals; 621.042
• DOI: 10.1016/j.apenergy.2016.06.153
• Languages: English
• ISSNs: 0306-2619

Abstract

Highlights: A novel procedure for developing an optimal power management strategy was proposed. Efficiency and durability were considered to improve the practical performance. Three control rules were abstracted from the optimization results with DP algorithm. The proposed control strategy was verified under different SoC and SoH conditions. The proposed strategy could further improve the energy efficiency obviously. Abstract: Efficiency and durability are becoming two key issues for the energy storage system in electric vehicles together with their associated power management strategies. In this paper, we present a procedure for the design of a near-optimal power management strategy for the hybrid battery and ultracapacitor energy storage system (HESS) in a plug-in hybrid electric vehicle. The design procedure starts by defining a cost function to minimize the electricity consumption of the HESS and to optimize the operating behavior of the battery. To determine the optimal control actions and power distribution between two power sources, a dynamic programming (DP)-based novel analysis method is proposed, and the optimization framework is presented accordingly. Through analysis of the DP control actions under different battery state-of-health (SoH) conditions, near-optimal rules are extracted. A rule based power management is proposed based on the abstracted rules and simulation results indicate that the new control strategy can improve system efficiency under different SoH and different SoC conditions. Ultimately, the performance of proposed strategy is further verified under different types of driving cycles including the MANHATTAN cycle, 1015 6PRIUS cycle and UDDSHDV cycle.