| Global energy and environment issue drive electric vehicle as the trend of futurevehicle. Battery’s safety and efficiency is a key technology, which depends on theestimation of battery state of charge （SOC） and state of health （SOH）. This thesisstudied the degradation of spinel lithium manganese oxide （LiMn2O4） throughexperiment, established degradation model, and developed a method to estimateSOH and SOC simultaneously.Multiple factors affect battery’s degradation. According to known agingmechanism, the thesis chose three core factors （temperature, voltage and current）,designed and conducted aging experiments, and analyzed how capacity, impedance andcolumbic efficiency change along degradation.Based on temperature and time’s influence on degradation, the thesis establisheddegradation model, analyzed how model parameters change with current and voltage,built capacity decrease model, impedance increase model and relationship modelbetween capacity and impedance by fitting, which realized estimating battery’s capacityand impedance based on its working history.Based on kalman filter, by using Ah counting as battery’s state equation,equivalent circuit model as battery’s measurement equation, the thesis proposed analgorithm for SOC estimation with error less than6%and insensitiveness toward initialerror. By using capacity decrease model as state equation, the relation model betweenimpedance and capacity as measurement equation, the thesis developed an algorithm forSOH estimation with error less than8%and insensitiveness to initial error.According to the changing period, the thesis assorted battery’s state variables intotwo categories, one called real-time state variable like temperature, current and voltageand the other called performance variable like usable capacity and impedance, anddefined timeline for each category. Then the thesis established a parallel SOC and SOHestimation algorithm based on kalman filter with error less than5%. |
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