Power battery system residual available life prediction method based on relevance vector machine and particle filter
A correlation vector machine and power battery technology, applied in the direction of measuring electricity, measuring electrical variables, measuring devices, etc., can solve the problem that the RUL prediction value deviates from the real value, etc.
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[0057] Combine below figure 1 To further explain the method provided by the present invention, it specifically includes the following steps:
[0058] Step 1: Obtain online capacity degradation data of the power battery system;
[0059] Step 2: Use a correlation vector machine to extract the feature vector of the capacity decline data;
[0060] Step 3: Use nonlinear least squares regression to fit the power battery aging model;
[0061] Step 4: Construct a state space equation describing the aging of the power battery;
[0062] Step five: predict the remaining usable life of the power battery system based on the particle filter theory.
[0063] In a preferred embodiment of the present application, the step one specifically includes: online obtaining the power battery capacity measurement value y=(y 1 ,y 2 ,...,Y N ) T And the corresponding number of charge and discharge cycles k=(1,2,...,N) T . Where y 1 ,y 2 ,...,Y N Represents the measured value of power battery capacity when the numb...
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