基于气液动力学热耦合模型的动力电池SOC估算

State of Charge Estimation of Power Batteries Based on the Gas-liquid Dynamics Thermal Coupling Model

电池解析模型通常在准确估算电池在线荷电状态(State of charge,SOC)方面起到关键作用。分析气液动力学与电学的物理相似性原理,研究气体分子与锂离子之间扩散/平衡的内在联系、气液系统与锂离子电池之间的观测量滞后状态量的等效机制,改进气液动力学与电学之间的参数映射关系,建立直接耦合温度特性的气液动力学电池模型。依据电池工作中的温度场分布特性与能量守恒原理,构建气液动力学-热耦合模型,基于该模型与扩展卡尔曼滤波算法设计高效的锂离子电池在线SOC估算方法。以内置温度传感器的锂离子动力电池为研究对象,在多种恒流与动态测试工况下电池内部最高温度估计误差小于1.2K,在线SOC估计误差低于1.8%。提出的在线SOC估算方法具有良好的估计精度,以及较强抵抗初值输入误差的能力。

The analytical model usually plays a key role in accurately estimating the online state of charge(SOC)of the battery.The physical similarity principle between gas-liquid dynamics and electricity is analyzed.The internal relationship of the diffusion/equilibrium between gas molecules and lithium ions,and the mechanism of the observation quantity lagging behind state quantity between the gas-liquid system and lithium-ion batteries are studied.The parameter mapping relationship between gas-liquid dynamics and electricity is improved.A gas-liquid dynamics battery model directly coupled with temperature characteristics is established.According to the distribution characteristics of the temperature field and the principle of energy conservation during the operation of the battery,a gas-liquid dynamics thermal coupling model is constructed.Based on this model and extended Kalman filter algorithm,an efficient online SOC estimation method for lithium-ion batteries is designed.Taking the lithium-ion power battery with a built-in temperature sensor as the research object,under various constant current and dynamic test conditions,the maximum estimation errors of the internal temperature and online SOC of the battery are less than 1.2 K and 1.8%,respectively.The proposed online SOC estimation method has a good accuracy and a strong ability to resist the initial value error.