Motor Temperature Prediction via Node Decomposition
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for determining motor temperature in electric motors are either inaccurate due to simple lumped parameter thermal network models or computationally expensive finite element analysis, and are limited by the number of temperature sensors that can be placed, making it difficult to measure rotor temperature effectively.
Innovation Solution
A method and apparatus that decompose motor components into multiple nodes to calculate electromagnetic loss and thermal resistance, allowing for accurate determination of motor temperature without the need for extensive sensor placement, using a processor and memory to execute instructions for electromagnetic loss calculation and thermal resistance determination.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If temperature sensors are placed inside the motor to measure temperature, then temperature measurement capability is improved, but device complexity and cost increase due to limited space and sensor placement constraints
Solution Approach 1:
The patent replaces physical temperature sensors with a computational model-based temperature prediction system. The motor is divided into multiple nodes, and temperature is calculated using electromagnetic loss and thermal resistance models, eliminating the need for physical sensor installation while achieving accurate temperature measurement.
Solution Approach 2:
The patent creates a virtual thermal model that copies the thermal behavior of the motor. By dividing the motor into multiple nodes and calculating thermal resistance between them, the system creates a computational representation of the motor's thermal characteristics, allowing temperature prediction without physical sensors.
2Device complexity
If simple lumped parameter thermal network models are used to determine motor temperature, then device complexity is reduced, but measurement precision deteriorates due to inaccurate temperature prediction
Solution Approach 1:
The patent segments the motor into multiple discrete nodes (e.g., stator core, stator winding, rotor core, rotor winding, permanent magnet) rather than treating it as a single lumped parameter. This segmentation allows for more accurate temperature prediction at different locations while maintaining computational efficiency through a structured thermal resistance network.
Solution Approach 2:
The patent assigns different thermal properties and electromagnetic loss characteristics to each node based on its local characteristics. Each node has its own thermal resistance connections to adjacent nodes, allowing the model to capture local temperature variations and heat transfer paths accurately without requiring complex overall modeling.
3Measurement precision
If finite element analysis is used to determine motor temperature, then measurement precision is improved, but productivity decreases due to high computational cost and time consumption
Solution Approach 1:
The patent uses segmentation to divide the motor into a manageable number of discrete nodes with defined thermal resistance connections. This approach captures the essential thermal behavior and heat transfer paths while avoiding the computational complexity of full finite element analysis, enabling fast temperature prediction suitable for real-time control applications.
Solution Approach 2:
The patent changes the modeling approach from continuous field analysis (finite element) to discrete node-based thermal resistance network. This parameter change simplifies the mathematical computations while retaining the ability to predict temperature accurately by focusing on key thermal paths and heat generation zones.
4Measurement precision
If multiple temperature sensors are placed to measure different motor component temperatures, then measurement precision is improved, but manufacturing cost increases due to sensor and installation costs
Solution Approach 1:
The patent replaces multiple physical temperature sensors with a computational model that calculates temperatures of different motor components. This substitution eliminates sensor installation costs, reduces manufacturing complexity, and provides temperature data for all critical components simultaneously through the thermal resistance network model.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach provides an accurate and fast prediction of motor temperature, enabling real-time monitoring and preventing overheating issues such as magnet demagnetization and insulation failure, while reducing the need for physical temperature sensors and potentially increasing vehicle performance.
Implementation Method 1
an electromagnetic loss of each node in ξ nodes acquired by decomposing components of a motor is obtained
Implementation Method 2
electromagnetic loss of each node
Implementation Method 3
a thermal resistance between every two nodes in the ξ nodes is obtained
Data Source
AI summary
Provided are a method and apparatus for determining motor temperature, and a storage medium. The method includes: obtaining an electromagnetic loss of each node in ξ nodes acquired by decomposing components of a motor, wherein the ξ is a natural number greater than 1, and at least one component in the components of the motor is decomposed into multiple nodes in the ξ nodes; obtaining a thermal resistance between every two nodes in the ξ nodes; and determining a temperature of the motor based on the electromagnetic loss of the each node in the ξ nodes and the thermal resistance between the every two nodes in the ξ nodes.