Accurate parameter identification of a lithium-ion battery is a critical basis in the battery management systems. Based on the analysis of the second-orderRCequivalent circuit model, the parameter identification proce...
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Accurate parameter identification of a lithium-ion battery is a critical basis in the battery management systems. Based on the analysis of the second-orderRCequivalent circuit model, the parameter identification process using the recursive least squares (rls) algorithm is discussed firstly. The reason for the rlsalgorithm affecting the accuracy and rapidity of model parameter identification is pointed out. And an improved rls algorithm is proposed, an inner loop with the estimated parameter vector updated multiple times is inserted into the conventional rlsalgorithm, so that the identification results are improved. The test platform of a single lithium-ion battery is built. The experimental results show that the improved rls algorithm has better tracking ability, smaller prediction error and has a moderate computational burden compared with the conventional rlsalgorithm and a variable forgetting factor rlsalgorithm.
In order to eliminate the sensor's dynamic error, a method that improved recursive least squares method is proposed. Gradient descent method is used to generate the initial value of the filter parameters, then the...
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ISBN:
(纸本)9781467355605
In order to eliminate the sensor's dynamic error, a method that improved recursive least squares method is proposed. Gradient descent method is used to generate the initial value of the filter parameters, then the recursive least squares method (rls) algorithm is used to optimize the parameters. The algorithm is tested and verified on the matlab platform. The time-domain response and frequency domain response of the sensor are analyzed before and after compensation. The piezoelectric sensor CY_YD-205 is compensated. Engineering experiments show that the compensation filter designed by the improved recursive least squares algorithm can improve the dynamic characteristics of the sensor system.
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