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SOC Estimation Based Combined Model For Vehicle Batteries

机译:基于SOC估计车辆电池组合模型

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Batteries play an essential role in electric vehicles, In order to achieve an optimum operation of systems with batteries it is necessary to estimate accurate of the state of charge (SOC). In this paper a combined model for SOC estimation in Vehicle Batteries, based on extended Kalman filter (EKF) is presented. The influence of the environmental temperature and charge-discharge rate are considered in the combined model, which makes it suitable for the acute change of current in driving. The effectiveness of the proposed method is verified using an Extensive experiment. This approach has strong capacity of resisting disturbance and will be implemented easily by hardware for an online SOC estimation.
机译:电池在电动车辆中发挥着重要作用,以实现具有电池的系统的最佳运行,有必要估计充电状态(SOC)的准确性。 本文介绍了基于扩展卡尔曼滤波器(EKF)的车辆电池SOC估计的组合模型。 在组合模型中考虑了环境温度和充放电速率的影响,这使得适用于驱动时电流的急性变化。 使用广泛的实验验证了所提出的方法的有效性。 这种方法具有很强的抵抗障碍能力,并将通过硬件来轻松实现在线SoC估计。

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