电动汽车动力电池SOC预测技术研究

电动汽车的电池管理系统需要一个精确和可靠的电池荷电状态 (SOC)预测器。由于铅酸蓄电池真实的SOC受许多因素如电池温度、充放电次数、电池老化等因素的影响 ,传统的SOC预测技术很难达到理想的效果。描述了一种闭环模糊推理方法在铅酸蓄电池SOC预测技术方面的应用。其中 ,闭环反馈环节采用了一个经验公式来调节铅酸蓄电池SOC的预测值。重新定义了一种容易从放电曲线中获得的电池内阻 ,利用这个电池内阻值可以很容易地把不同工况下的电池端电压等效到一个固定工况下的端电压 ,从而可以简化模糊规则的设计。经仿真证明这种方法能够获得蓄电池精确和可靠的SOC预测值

Research on estimation technology of traction-battery SOC for electric vehicle

Accurate and reliable state of charge (SOC) estimation for battery is necessary for the battery mana gement system in electric vehicles. Since the actual SOC of lead acid battery is influenced by many factors,such as temperature,cycle of discharge and aging of battery, it is difficult to obtain ideal results by traditional methods. The application of fuzzy inference method with closed loop control for the SOC estimation of lead acid battery was described. The closed loop feedback adopted an empirical equation to adjust the estimation value of SOC for lead acid battery. A new internal resistance, which could be obtained simply from the discharge curves of battery,was also redefined. Battery voltage at different conditions could be equivalent to the voltage at a certain condition by means of the new internal resistance. Therefore, the design of fuzzy regulation could the simplified. The computer simulation proved that accurate and reliable battery SOC estimation of battery could be obtained by adopting the new method.