State of Charge Estimation Based on Microscopic Driving Parameters for Electric Vehicle's Battery

Enjian Yao, Meiying Wang, Yuanyuan Song and Yang Yang

Mathematical Problems in Engineering, 2013, vol. 2013, 1-6

Abstract:

Recently, battery-powered electric vehicle (EV) has received wide attention due to less pollution during use, low noise, and high energy efficiency and is highly expected to improve urban air quality and then mitigate energy and environmental pressure. However, the widespread use of EV is still hindered by limited battery capacity and relatively short cruising range. This paper aims to propose a state of charge (SOC) estimation method for EV’s battery necessary for route planning and dynamic route guidance, which can help EV drivers to search for the optimal energy-efficient routes and to reduce the risk of running out of electricity before arriving at the destination or charging station. Firstly, by analyzing the variation characteristics of power consumption rate with initial SOC and microscopic driving parameters (instantaneous speed and acceleration), a set of energy consumption rate models are established according to different operation modes. Then, the SOC estimation model is proposed based on the presented EV power consumption model. Finally, by comparing the estimated SOC with the measured SOC, the proposed SOC estimation method is proved to be highly accurate and effective, which can be well used in EV route planning and navigation systems.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:946747

DOI: 10.1155/2013/946747

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