Application Error Analysis of SOC Estimation of Pure Electric Vehicles Based on Kalman Signal Big Data Algorithm

Zhaona Lu,Chuanxing Wang,Guoqing Li,Junlong Wang

doi:10.1155/2021/4991332

Zhaona Lu, Chuanxing Wang + Show 2 more

Open Access

https://doi.org/10.1155/2021/4991332

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Abstract

The state of charge estimation of a pure electric vehicle power battery pack is one of the important contents of the battery management system. Improving the estimation accuracy of the battery pack’s SOC is conducive to giving full play to its performance and preventing overcharge and discharge of a single battery. At present, the open-circuit voltage ampere-hour integral method is traditionally used to estimate the SOC value of the battery pack; however, this estimation method is not accurate enough to correct the initial value of SOC and cannot solve the problem of current time integration error between this correction and the next correction. As for the battery performance and characteristics of electric vehicles, it is pointed out that the size of the model value will affect the estimation accuracy of the Kalman signal value. Based on the analysis of the factors to be referred to in the calculation and estimation of SOC by Kalman for pure electric vehicles, the scheme is improved considering the change of battery model value, and the Kalman scheme is proposed. The feasibility and accuracy of the scheme are proved by several battery simulation experiments.

Highlights

Rising environmental awareness and rising oil prices have brought electric cars. e era, along with the electric vehicle technology requirements, is gradually increasing
Battery is the main energy source of electric vehicles, and the battery storage dynamic is the process that the vehicle can run in order to prevent excessive discharge and overcharging of the battery. erefore, it is required that the SOC of electric vehicles can accurately estimate the battery life [1,2,3]
E increasingly widespread adoption of pure electric vehicles, the battery standby time, and the movement mode of battery pack replacement have upset the mode of SOC automatic verification

Summary

Introduction

Rising environmental awareness and rising oil prices have brought electric cars. e era, along with the electric vehicle technology requirements, is gradually increasing. Erefore, it is required that the SOC of electric vehicles can accurately estimate the battery life [1,2,3]. E constant discharge characteristic of battery is used to calculate SOC. In this way, the model parameters should be relatively stable; otherwise, it is difficult to calculate the battery consumption state of electric vehicles. The stable open-circuit voltage is the voltage at the normal end after the battery is cooled for a certain period of time. As the background, the open-circuit voltage (OCV) and the SOC motion mode as the background, and the battery terminal voltage as the numerical calculation method, which greatly improves the calculation accuracy of the battery’s SOC

Running Condition of Pure Electric Vehicle

Kalman Signal Big Data Algorithm

Experiment and Result Analysis

Findings

Conclusions