Decision-Flux Optimization-based energy management for battery-supercapacitor hybrid storage in electric vehicles: battery lifetime and efficiency enhancement

Scientific Reports

卷:16

Article

Zhen Wen¹  Maroun Kuoki²  Leren Qian³  Mohammad Khishe⁴ 

[1] Department of Biosciences, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, 602 105, Chennai, India

[2] Applied Science Research Center, Applied Science Private University, Amman, Jordan

[3] School of Automotive Engineering, Hunan Industry Polytechnic, Changsha, China

[4] School of Computing and Augmented Intelligence, Arizona State University, 85281, Tempe, AZ, USA

关键词: Flux optimization;    Energy management;    Electric vehicles;    Battery lifetime;    Efficiency enhancement;   

DOI  :  10.1038/s41598-026-57560-9

 received in 2026-03-13, accepted in 2026-06-08,  发布年份 2026

来源: Springer

【 摘 要 】

Battery-supercapacitor hybrid energy storage systems can reduce the transient loading of lithium-ion batteries in electric vehicles, but their benefit strongly depends on the energy-management parameters used to distribute power between the two storage devices. This study proposes Decision-Flux Optimization (DFO), a simulation-driven feasible-descent framework for calibrating the parameters of a battery/supercapacitor energy management strategy under full driving-cycle constraints. DFO uses induced operational trace of a candidate decision vector which comprises of battery state of charge, supercapacitor state of charge, power limits, voltage limits and end-of-cycle recovery constraints. Constraint satisfaction is considered as an admissibility condition and not as a term in the objective function. The objective is a combination of normalized RMS battery power, normalized energy-loss indicators, and only accepted updates are feasible trace-level transitions. The optimized parameters are computed offline and then deployed in the real-time control layer. Evaluation of the method is performed on ARTEMIS driving cycle through simulation and laboratory-scale controller validation. Compared with GA, PSO, RB-EMS, MPC, SRCPO, DSCEO, and ADRL-EMS benchmarks, DFO produced the lowest RMS battery power in the reported case study and maintained feasibility across repeated runs. The aging analysis indicates a model-estimated lifetime of 3720 equivalent cycles before the 80% capacity threshold, which should be interpreted as a comparative model-based durability estimate rather than a direct long-term lifetime measurement. Results indicate that trace level feasibility gating can be used to enhance repeatability, battery stress mitigation, and energy management for efficiency.

【 授权许可】

CC BY-NC-ND   
© The Author(s) 2026

【 图 表 】

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