A Fault Diagnosis and Estimation Method for Electric Scooter Based on Bond Graph Model

Abstract

The invention relates to an electric scooter fault diagnosis method, in particular to an electric scooter fault diagnosis and estimation method based on a bond graph model. Firstly, the model is established for an electric scooter, so that the bond graph model of the electric scooter is obtained, a redundant relationship is analyzed according to the bond graph model of the electric scooter, a residual error is generated according to the analyzed redundant relationship, a fault characteristic matrix is obtained, the parameter values of the bond graph model of the electric scooter are changed, whether the residual error exceeds a set threshold value or not is judged, if the residual error exceeds the set threshold value, an electric scooter system generates a fault, coherent vectors and thefault characteristic matrix are compared, a possible fault set is obtained, elements in the fault set and system original state variables are jointly estimated through an unscented Kalman filter method, and the actual fault of the electric scooter system is obtained. Fault parameters can be accurate to specific numerical values through fault identification, and a fault source can be diagnosed andisolated accurately in time.

Description

technical field [0001] The invention relates to a fault diagnosis method for an electric scooter, in particular to a fault diagnosis and estimation method for an electric scooter based on a bonding graph model. Background technique [0002] In recent years, with the development of means of transportation and the improvement of people's awareness of environmental protection, electric vehicles are widely popular and loved as a light and clean means of transportation. How to diagnose the faults of electric scooter, facilitate people to travel and reduce traffic accidents has become a concern of many people. [0003] At present, there are qualitative methods and quantitative methods for fault diagnosis. Among them, quantitative methods are divided into data-driven methods and model-based methods. Data-driven methods require sufficient and complete data for posterior analysis. , the requirements are very strict, and the fault diagnosis is not timely, and the fault source judgmen...

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Problems solved by technology

[0003] At present, there are qualitative methods and quantitative methods for fault diagnosis. Among them, quantitative methods are divided into data-driven methods and model-based methods. Data-driven methods require sufficient and complete data for posterior analysis. , the requirements are very strict, and the fault diagnosis is not timely, and the fault source judgment is not accurate

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