Online battery temperature prediction is beneficial when it comes to taking effective heating and cooling actions in advance to realize better thermal management. First, this paper derives a simple thermal managing equation, i.e., a lightweight temperature prediction approach based on basic electrical and thermal laws from an equivalent circuit model. Then, to improve adaptability to complex conditions, some previously neglected thermal processes like heat conduction hysteresis and heat radiation are taken into consideration to achieve more realistic effects. In particular, the considerable reversible heat during alternating charging and discharging due to the electrochemical reactions of solid–liquid phase transitions is also modeled as a dependent variable in terms of real-time ohmic heat. A series of experiments is conducted under various loads and ambient conditions. The obtained results show that the proposed temperature prediction method can follow real temperature trajectories with an accumulated error of only 2.1 °C after an hour running.

在线电池温度预测有助于提前采取有效的加热和冷却措施以实现更好的热管理。首先，本文推导了一个简单的热管理方程，即基于等效电路模型的基本电气和热定律的轻量级温度预测方法。然后，为了提高对复杂条件的适应性，考虑到一些以前被忽视的热过程，如热传导滞后和热辐射，以达到更逼真的效果。特别是，由于固液相变的电化学反应，在交替充电和放电过程中产生的大量可逆热也被建模为实时欧姆热的因变量。在各种负载和环境条件下进行了一系列实验。所得结果表明，所提出的温度预测方法可以遵循真实的温度轨迹，运行一小时后累积误差仅为2.1°C。