An real-time intelligent energy management based on deep reinforcement learning and model predictive control for hybrid electric vehicles considering battery life

Xiaokang Ma, Hui Liu, Lijin Han, Ningkang Yang and Mingyi Li

Energy, 2025, vol. 324, issue C

Abstract: To alleviate environmental pollution and energy crisis, the large-scale deployment of hybrid electric vehicles (HEVs) is a promising solution and their energy management is a critical technology for enhancing the fuel efficiency. This paper proposes a real-time energy management strategy (EMS) for HEVs that integrates model predictive control (MPC) with twin delayed deep deterministic policy gradient(TD3) to improve fuel economy and minimize battery degradation. First, considering the dynamic actual driving conditions, an online recursive high-order Markov Chain(MC) model is developed to predict the randomness of the environment in the MPC framework, an EMS controller is then developed based on the advanced TD3 algorithm to generate reliable State of Charge (SOC) reference sequences and action reference sequences. moreover, an improved Sequential Quadratic Programming (SQP) algorithm is devised to solve the MPC problem for enhancing real-time performance. Meanwhile, coordinated control algorithms on the dynamic conditions of the system is designed to incorporate the response characteristics of key system components into the energy management problem. Then, the DP, MPC-RL and Rule-based strategies are designed as baselines to compare with the proposed strategy under three unknown driving cycles. The results demonstrates satisfactory performance in fuel economy, real-time performance, robustness and reduction of battery life loss. Finally, a hardware-in-the-loop(HIL) experiment validates its practical applicability.

Keywords: Hybrid electric vehicle; Real time energy management; Model predictive control; Twin delayed deep deterministic policy gradient; Battery life; Improved sequence quadratic programming (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544225015737
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:324:y:2025:i:c:s0360544225015737

DOI: 10.1016/j.energy.2025.135931

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 ().