Synergy optimization of energy management strategy for extended-range electric vehicles incorporating road noise perception

Yuxin Zhang, Yalian Yang, Yunge Zou and Changdong Liu

Energy, 2025, vol. 329, issue C

Abstract: Extended-range electric vehicles (EREVs) experience a notable increase in noise, vibration, and harshness (NVH) during range extender operation. To address this challenge, a multi-objective optimization energy management strategy incorporating road noise perception is proposed. First, a road noise prediction model is established, comprising pavement identification and velocity prediction sub-models. Based on this, an innovative NVH-oriented multi-objective Pontryagin's minimum principle (N-PMP) control algorithm is developed to optimize both fuel economy and NVH performance. Furthermore, by leveraging road noise prediction results, an integrated model predictive control (MPC)-N-PMP strategy is introduced to achieve ultra-quiet operation through the optimization of control variables. Simulation results demonstrate that the MPC-N-PMP algorithm effectively reduces noise levels while meeting real-time computational requirements compared to the MPC-PMP approach. Specifically, an 8.56 % reduction in NVH levels is achieved with only a marginal 2.32 % increase in fuel consumption, substantially enhancing overall vehicle comfort. Finally, the strategy's feasibility is validated through hardware-in-the-loop (HIL) experiments, laying a strong foundation for the future implementation of intelligent and efficient quiet control strategies in automotive applications.

Keywords: Range extender; Pontryagin's minimum principle; Road noise; Real-time control (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544225024259
Full text for ScienceDirect subscribers only

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:eee:energy:v:329:y:2025:i:c:s0360544225024259

DOI: 10.1016/j.energy.2025.136783

Access Statistics for this article

Energy is currently edited by Henrik Lund and Mark J. Kaiser

More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().