Estimation of SOC and SOH for Li-ion battery by multi-verse optimization
Estimating the state of charge(SOC)and state of health(SOH)of the battery is one of the most complex tasks in Li-ion battery management.Currently,for the estimation of SOC and SOH,there are issues such as large tracking value error,large noise error and large computation,multi-verse optimization(MVO)algorithm are introduced,the fit of the model is up to 95.3%against the actual output voltage of the battery.The stable estimation of SOC is obtained through 14 iterations,which improves the stability of SOH estimation by 119%and reduces the computational space requirement by 78%compared with the traditional cycle number method.
algorithmstate estimationmulti-verse optimization(MVO)state of charge(SOC)state of health(SOH)energy storage
万方数据
维普
