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基于工况特性的电动汽车蓄电池组SOC与SOH在线智能识别与评价方法研究 被引量:7

Study on Online Intelligent Recognition and Evaluation Method of SOC and SOH Of Battery Pack for Electric Vehicle Based on Driving Cycle Characteristice
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摘要 蓄电池组SOC和SOH是电动汽车电池管理和能量管理的关键参数,受单体电池特性、蓄电池组一致性和均衡技术等因素影响,不易建立准确计算模型。基于电动汽车日常行驶工况统计特性提出一种改进的Ah积分法计算蓄电池组SOC和SOH,该方法采用工况容量与等效工况电流根据Peukert方程实现稳态容量修正,同时采用模糊逻辑实现放电率波动对容量的动态修正;提出采用单体统计特性建立状态评价矩阵表征蓄电池组状态的全面评价方法;最后通过对比仿真计算分析验证了所提方法的合理性和实用性。 SOC(state of charge) and SOH(state of health) of battery pack are the key parameters for the battery and energy management system of electric vehicles.And a precise calculation model is difficult to be built for their many influencing factors such as the battery cell characteristics,consistency of the battery pack and equalization technology etc.Based on the real driving cycle statistical data of the electric vehicles about battery pack output,an improved Ah integral method is proposed to calculate the SOC and SOH of battery pack,which adopts the cycle capacity and equivalent cycle current in the Peukert equation to achieve homeostatic capacity correction.Meanwhile fuzzy logic is adopted to achieve the dynamic capacity correction for discharge rate fluctuations. A more comprehensive method for state evaluation of battery pack is proposed by using SOC and SOH distribution array of battery cells.Ultimately,the rationality and practicality is verified by simulation calculation.
出处 《测控技术》 CSCD 北大核心 2013年第4期100-104,110,共6页 Measurement & Control Technology
基金 国家自然科学基金资助项目(51005113)
关键词 电动汽车 蓄电池组SOC与SOH 工况特性 Peukert方程 模糊算法 electric vehicles SOC and SOH of battery pack driving cycle characteristics Peukert equation fuzzy algorithms
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