Power battery management system is a very important part in electric vehicle. Currently, power battery management system is only monitor and control of the power batteries group voltage. This may cause a single battery overcharge and over-discharge, thus affecting cycle life of the power battery. In this paper, for each cell in the batteries group is monitored and controlled to prevent any battery overcharge and over-discharge. Hardware and software of power battery management system has been designed. Experimental results show that power battery management system can accurately monitor the power batteries, thereby ensuring the safety of the power batteries and prolonging the cycle life of the power batteries group.

No abstract

No abstract

State of Charge (SOC) determination is an increasingly important issue in battery energy storage system. Precise knowledge of SOC allows the controller to confidently use the battery pack's full operating range without fear of over-or under-charging cells. Taking into account of some transformed parameters like voltage and current, this paper describes a novel adaptive online approach to determinate SOC for lead-acid batteries by combining modified PID controller with RBFNN based terminal voltage evaluation model, which is used to simulate battery's behavior while it is under load. Results of lab tests on physical cells, compared with model prediction, are presented. Results show that the ANN based terminal voltage evaluation model simulates battery system with great accuracy, and the prediction value of SOC simultaneously converges to the real value quickly within the error of 1% ± as time goes on.