Multi-objective optimization and power control for electric vehicle V2G considering battery degradation

SHEN Yongpeng; ZHANG Yegui; HE Ting; LIU Dongqi; WANG Yanfeng

doi:10.19783/j.cnki.pspc.251242

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Multi-objective optimization and power control for electric vehicle V2G considering battery degradation

更新时间：2026-07-27

- Multi-objective optimization and power control for electric vehicle V2G considering battery degradation
- Power System Protection and Control Vol. 54, Issue 13, (2026)
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- DOI：10.19783/j.cnki.pspc.251242
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- Published：2026
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SHEN Yongpeng, ZHANG Yegui, HE Ting, et al. Multi-objective optimization and power control for electric vehicle V2G considering battery degradation[J]. Power System Protection and Control, 2026, 54(13).
DOI：

SHEN Yongpeng, ZHANG Yegui, HE Ting, et al. Multi-objective optimization and power control for electric vehicle V2G considering battery degradation[J]. Power System Protection and Control, 2026, 54(13). DOI： 10.19783/j.cnki.pspc.251242.

摘要

针对电动汽车在车辆-电网双向互动(vehicle-to-grid

V2G)模式下现有能量管理策略难以在最大化用户收益与抑制电池加速老化之间实现精细化权衡，提出了计及电池损耗的电动汽车V2G功率多目标优化动态规划策略。首先，区别于传统经验循环次数或成本系数方法，构建了耦合深度放电(depth of discharge

DOD)与荷电状态(state of charge

SOC)的动力电池寿命损耗量化模型。其次，以V2G收益最大、电池损耗最小为目标，以充放电功率为控制变量、SOC为状态变量，建立V2G能量管理控制模型。进而，结合实时电价与所提老化模型，设计了基于动态规划的V2G功率最优控制方法，并给出逆向递推求解与正向状态转移过程。最后，在初始SOC为20%、50%和80%条件下进行算例分析。实验结果表明，所提策略以收益减少29.99%为代价，实现动力电池容量损耗减少68.23%，验证了其在权衡V2G经济性与电池寿命、延缓电池衰减方面的显著优势。

Abstract

To address the difficulty of existing energy management strategies for electric vehicles operating in the vehicle-to-grid (V2G) mode in achieving a refined trade-off between maximizing user benefits and mitigating accelerated battery aging

this paper proposes a multi-objective optimal dynamic programming strategy for V2G power control considering battery degradation. First

unlike conventional methods based on empirical cycle counts or cost coefficients

a quantitative model of power battery lifetime degradation is constructed by coupling the depth of discharge (DOD) and the state of charge (SOC). Second

a V2G energy management control model is established with the objectives of maximizing V2G revenue and minimizing battery degradation

where charging/discharging power serves as the control variable and SOC as the state variable. Then

by integrating real-time electricity prices with the proposed degradation model

an optimal V2G power control method based on dynamic programming is designed

and both the backward recursive solution process and the forward state transition process are presented. Finally

case studies are conducted under initial SOC levels of 20%

50%

and 80%. The experimental results show that the proposed strategy reduces battery capacity degradation by 68.23% at the expense of a 29.99% reduction in revenue

thereby demonstrating its significant advantages in effectively balancing V2G economic benefits and battery lifetime while delaying battery degradation.

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references

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