Electric Drive Sensor Fault Identification With Low-Cost Sensors
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Solution Overview
Problem
Existing electric drive systems face challenges in accurately detecting and identifying sensor faults, particularly in new energy vehicles, where high-accuracy sensors are costly and difficult to calibrate, affecting torque ripple and efficiency.
Innovation Solution
A method involving data collection from sensors, inputting data into a machine learning-based sensor fault mode identification model, and using a vehicle network monitoring system to determine fault modes and types, with the option to update the model and run compensation algorithms to correct sensor inaccuracies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-accuracy sensors are used, then measurement precision is improved, but cost increases
Solution Approach 1:
The patent applies this principle by using low-cost sensors instead of expensive high-precision sensors, and compensating for their inaccuracies through software algorithms and machine learning models that process sensor data to achieve accurate fault detection and system control
Solution Approach 2:
The patent changes the measurement parameters by using multiple sensors to collect diverse data (current, voltage, temperature, position) and processing these parameters through machine learning models to compensate for individual sensor inaccuracies and achieve overall high measurement precision
2Ease of manufacture
If low-cost sensors are used, then cost is reduced, but measurement precision deteriorates
Solution Approach 1:
The patent uses inexpensive sensors and compensates for their lower precision through data fusion from multiple sensors and machine learning-based fault mode identification models that can detect and correct measurement errors
Solution Approach 2:
The patent introduces machine learning models and data processing algorithms as intermediaries between the low-cost sensors and the control system, which process and interpret sensor data to achieve accurate fault detection despite individual sensor inaccuracies
3Reliability
If sensor fault detection capability is improved, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent makes the existing sensor data serve multiple functions: both for normal control operations and for fault detection and identification, eliminating the need for separate dedicated fault detection hardware and reducing overall system complexity
Solution Approach 2:
The system uses its own existing sensor data and processing capabilities to perform self-diagnosis and fault detection, without requiring external monitoring equipment or additional complex diagnostic subsystems
Data Source
AI summary
A method for monitoring and identifying sensor faults in an electric drive system of a vehicle includes collecting corresponding data using sensors in the electric drive system, inputting the collected data to an already-established sensor fault mode identification model, and determining whether a fault mode exists and a fault mode type based on the collected data using the sensor fault mode identification model. The method quickly determines the fault mode caused by a sensor fault in the electric drive system, and the fault mode type of the sensor fault.