The invention belongs to the technical field of battery energy consumption control, and solves the problems that the state of charge of a new energy battery vehicle is inconvenient to estimate and the energy utilization efficiency is low. The invention provides a lithium ion battery state-of-charge estimation and equalization control method, which comprises the following steps: establishing a battery equivalent circuit model, and introducing a state variable battery state-of-charge; establishing a battery state-of-charge estimation model based on the BP neural network, and outputting an estimated value of the battery state-of-charge; establishing an optimized particle swarm algorithm based on a battery energy path, and searching an optimal path of battery energy transmission based on an inertia weight adjustment strategy of a fitness function value; and the current output is controlled through the fuzzy controller to obtain the optimal equalizing current. According to the invention, the BP neural network is used to estimate the state of charge of the battery, the battery energy control path is optimized by improving the particle swarm optimization, the equalizing current is adjusted by using the fuzzy control algorithm, the energy utilization rate of the new energy battery vehicle can be improved, and the problem of battery inconsistency is improved.
本发明属于电池能耗控制技术领域,解决了新能源电池车辆荷电状态估算不便,且能量的利用效率低的问题。提供了一种锂离子电池荷电状态估算与均衡控制方法,建立电池等效电路模型,并引入状态变量电池荷电状态;建立基于BP神经网络的电池荷电状态估算模型,输出电池荷电状态的估算值;建立基于电池能量路径的优化的粒子群算法,基于适应度函数值的惯性权重调整策略,寻找电池能量传递的最优路径;通过模糊控制器对电流输出进行控制,得到最优的均衡电流。本发明利用BP神经网络估算电池荷电状态,并通过改进粒子群算法优化电池能量控制路径,利用模糊控制算法调节均衡电流大小,能够提高新能源电池车辆能量利用率,同时改善电池不一致性的问题。
Lithium ion battery charge state estimation and equalization control method
一种锂离子电池荷电状态估算与均衡控制方法
2024-04-02
Patent
Electronic Resource
Chinese
European Patent Office | 2023
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