With the continuous development of Evs (electric vehicles) and new energy, smart BESS (battery energy storage system) charging stations came into being, and the EV battery testing technology is particularly important.
EV power battery testing has three main elements, namely SOC, SOH and battery life prediction. The relationship between capacity loss L cal per d, the SOC and the temperature of the battery is shown for different temperatures in Fig. 1. As the temperature increases, the SOC gradually increases at the same reaction rate.
In the context of the vigorous development of big data, battery testing systems need big data technology to carry out battery safety protection and early warning while making an accurate assessment of battery health and life. As shown in Fig. 6, the system obtains the basic parameters through the online monitoring terminal.
To the best of the authors’ knowledge, the contributions of this article are as follows: A complete solution for the whole life cycle online inspection and fault detection of EV batteries is proposed, using the SOC, SOH algorithm and drive method for special scenario application described in the paper.
The main contents of EV battery testing are SOC, SOH and battery remaining life prediction. For SOC, currently, the major manufacturers mainly apply the current integration method. For SOH, currently, the major manufacturers mainly apply the voltage curve fitting method.
Power battery is still one of the key issues that restrict the development of the EV industry . Improving the stability of the vehicle can not only reduce the accident rate of the vehicle, reduce casualties and economic losses, but also improve the traffic conditions and people’s living standards.
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