Electric vehicle fault diagnosis method based on dynamic threshold model

Abstract

The invention provides an electric vehicle fault diagnosis method based on a dynamic threshold model, and the method is used for the fault diagnosis of a battery system in an electric vehicle, and improves the threshold model building and parameter identification algorithms. A circuit basic characteristic test experiment is conducted at different temperatures, and the parameters of an equivalent circuit model are obtained; An OCV-SOC-Q three-dimensional response surface model is established; and model parameter identification is conducted by adopting a recursive least square method with forgetting factors, and a dynamic threshold model about R0 and tau is established. In the actual fault diagnosis process, parameters and states are identified by using a double extended Kalman filtering algorithm to obtain battery R0, tau, capacity and SOC; a parameter reference value is determined by adopting a temperature interpolation method; a parameter threshold is determined; a residual error is generated; and whether the battery has a fault or not is judged by comparing the residual error with a threshold value. According to the method, the fault diagnosis rate is high, and the problems of untimely detection, false alarm and missed alarm can be avoided.

Description

technical field [0001] The invention mainly relates to the technical field related to new energy vehicle systems, in particular to a fault diagnosis method for electric vehicles based on a dynamic threshold model. Background technique [0002] The current electric vehicle technology is developing very rapidly and is in the rising stage of market promotion. As a new type of vehicle, electric vehicles have more serious problems in terms of vehicle safety and parts quality than traditional vehicles. As the core component of electric vehicles, the battery's fault status and operating life directly affect the function and safety of the vehicle, and it is also a matter of great concern to manufacturers and 4S stores. [0003] The fault diagnosis of the power battery system is one of the core functions of the battery management system. The commonly used fault diagnosis method for the battery system is a model-based method. This method is divided into two steps: residual error gene...

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Problems solved by technology

[0004] 1) In the process of residual error generation, although the estimated value of the parameter is easy to determine, the corresponding reference value is usually a fixed value. In fact, the reference value corresponding to the estimated value of the residual error of the battery at a certain temperature should also be the corresponding temperature If the value is lower, ignoring the influence of temperature will easily cause the generated residual error to be too large or too small, which will affect the accuracy of fault diagnosis;

[0005] 2) In the residual evaluation process, the fault threshold is usually a fixed value, and the battery residual is affected by temperature, aging and battery state of charge (SOC). If the influence of SOC, temperature and aging on the residual is ignored However, the use of fixed thresholds for residual evaluation may easily lead to excessively high fault false alarm rates and missed alarm rates.

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