Research on Online Energy Management Strategy for Hybrid Energy Storage Electric Vehicles Under Adaptive Cruising Conditions

Zhiwen Zhang, Jie Tang, Jiyuan Zhang, Tianyu Li and Hao Chen ()
Additional contact information
Zhiwen Zhang: School of Vehicle and Energy, Yanshan University, Qinhuangdao 066000, China
Jie Tang: School of Vehicle and Energy, Yanshan University, Qinhuangdao 066000, China
Jiyuan Zhang: School of Vehicle and Energy, Yanshan University, Qinhuangdao 066000, China
Tianyu Li: School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130025, China
Hao Chen: School of Vehicle and Energy, Yanshan University, Qinhuangdao 066000, China

Sustainability, 2025, vol. 17, issue 7, 1-28

Abstract: To address the critical challenge of high energy consumption in single-source electric vehicles, this study proposes a hybrid energy storage system (HESS)-integrated energy management strategy (EMS). Firstly, the car-following and HESS models are constructed. Secondly, a multi-objective optimization framework balancing adaptive cruise control (ACC) optimal tracking quality and energy economy is developed, where the fast, non-dominated sorting genetic algorithm (NSGA-II) resolves dynamic power demands. Thirdly, the third-order Haar wavelet enables online rolling decomposition of power profiles. The high-frequency transient power is matched by a supercapacitor, while the low-frequency steady-state power is utilized as an input variable to the optimization controller. Then, a fuzzy logic controller dynamically optimizes HESS’s energy distribution based on state-of-charge (SOC) and load conditions. Finally, the cruise simulation model has been constructed utilizing the MATLAB/Simulink platform. Comparative analysis under the Urban Dynamometer Driving Schedule (UDDS) demonstrates a 3.71% reduction in the total power demand of the ego vehicle compared to the front vehicle. Compared to single-source configurations, the HESS ensures smoother SOC dynamics in lithium-ion batteries. After employing the third-order Haar wavelet for online rolling decomposition of the demand power, the high-frequency transient power matched by the lithium-ion battery is substantially reduced. Comparative analysis of three control strategies demonstrates that the wavelet-fuzzy logic approach exhibits superior comprehensive performance. Consequently, the proposed strategy effectively mitigates high-frequency transient peak charge/discharge currents in the lithium-ion battery and the energy consumption of the entire vehicle. This study provides a novel solution for energy storage systems in hybrid energy storage electric vehicles (HESEV) under ACC scenarios.

Keywords: adaptive cruise control; energy management strategy; fast, non-dominated sorting genetic algorithm; wavelet transform theory; fuzzy logic controller (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/7/3232/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/7/3232/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:7:p:3232-:d:1628367

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().