【Applied Energy 最新原创论文】电池容量衰减最小化的电动汽车最优电池热管理

AEii国际应用能源 · 公众号 · · 2023-11-14 18:30

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原文信息：

Optimal battery thermal management for electric vehicles with battery degradation minimization

原文链接：

https://www.sciencedirect.com/science/article/pii/S030626192301454X

Highlights

• A precise BTMS model for EV under diverse operation conditions is first proposed.

• Battery capacity degradation and cooling energy is minimized by dynamic programming.

• An online near-optimal battery cooling strategy is proposed from dynamic programming.

• Using regenerative energy for cooling can dramatically reduce battery degradation.

• Improved driving economy and battery life gained from the proposed cooling method.

摘要

电池热管理系统的控制对电动汽车在炎热天气下的热安全、能源效率和寿命至关重要。为了解决电池冷却的优化问题，本文采用动态规划设计了一种在线的基于规则的冷却策略。首先，建立了磷酸铁锂电池的电-热-老化模型以及面向控制的车载电池热管理系统模型，后者在不同车速和环境温度下进行了验证。然后，在动态规划框架中，通过最小化电池老化成本和制冷能耗成本的目标函数，获取最优压缩机功率。从动态规划结果中提取“快速制冷、慢速制冷和保温”三条规则，提出了一个近似最优的基于规则的冷却策略用于在线执行，该策略尽可能使用回馈制动功率冷却电池组。仿真结果表明，所提出的在线策略可以在不同工况下显著改善行驶经济性和降低电池容量衰减，与离线动态规划的衰减结果差异仅为2.18%。最后，给出了不同实际情况下的电池冷却建议。

更多关于" battery thermal management "的研究请见：

https://www.sciencedirect.com/search?qs=battery%20thermal%20management&pub=Applied%20Energy&cid=271429.

Abstr act

The control of a battery thermal management system (BTMS) is essential for the thermal safety, energy efficiency, and durability of electric vehicles (EVs) in hot weather. To address the battery cooling optimization problem, this paper utilizes dynamic programming (DP) to develop an online rule-based control strategy. Firstly, an electrical–thermal-aging model of the LiFePO4 battery pack is established. A control-oriented onboard BTMS model is proposed and verified under different speed profiles and temperatures. Then in the DP framework, a cost function consisting of battery aging cost and cooling-induced electricity cost is minimized to obtain the optimal compressor power. By exacting three rules ”fast cooling, slow cooling, and temperature-maintaining” from the DP result, a near-optimal rule-based cooling strategy, which uses as much regenerative energy as possible to cool the battery pack, is proposed for online execution. Simulation results show that the proposed online strategy can dramatically improve the driving economy and reduce battery degradation under diverse operation conditions, achieving less than a 2.18% difference in battery loss compared to the offline DP. Recommendations regarding battery cooling under different real-world cases are finally provided.

Keywords

Battery thermal management system ‍

Battery degradation ‍

Electric vehicles ‍

Eco-cooling ‍

Dynamic programming ‍

Economy analysis ‍

Graphics

Fig. 1. Battery energy storage system, battery thermal management system, and traction load of the electric vehicle.

Fig. 2. Coupling relationship between battery electrical, thermal, and aging models.

Fig. 4. Model fitted coefficients of the BTMS model

Fig. 8. Offline DP results of compressor power, battery heating/cooling rate, and temperature under 55 SC03 driving cycles.

【Applied Energy 最新原创论文】电池容量衰减最小化的电动汽车最优电池热管理

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