Inverter Cooling Loop Flow Estimation Without System Calibration
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Solution Overview
Problem
Current coolant flow rate estimation methods for electric vehicle powertrains require separate data calibration for different thermal management systems, leading to time-consuming and impractical processes, affecting the accuracy of online temperature estimation and vehicle safety.
Innovation Solution
A method for estimating coolant flow rate in real-time within the powertrain, using a controller to determine rotation speeds and flow rates based on temperatures and power losses at specific positions in the cooling loop, eliminating the need for external calibration data and improving accuracy by adjusting for varying heat dissipation conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If separate data calibration is performed for different thermal management systems, then measurement precision of coolant flow rate is improved, but loss of time increases and ease of operation deteriorates
Solution Approach 1:
The system uses the powertrain's own operating parameters (motor phase current, inverter power loss, coolant temperatures) to calculate coolant flow rate without requiring external calibration data. The controller computes flow rate based on heat dissipation principles using readily available sensor data from the powertrain itself, making the system self-sufficient and eliminating time-consuming calibration processes.
Solution Approach 2:
The patent replaces the traditional mechanical/calibration-based flow rate measurement system with a thermal calculation system. Instead of using calibrated correspondence tables from thermal management systems, the controller calculates flow rate by substituting thermal parameters (power loss, temperature difference, heat capacity) into a heat dissipation equation, eliminating the need for empirical calibration.
2Measurement precision
If separate data calibration is performed for different thermal management systems, then measurement precision of coolant flow rate is improved, but ease of operation deteriorates
Solution Approach 1:
The system uses the powertrain's own operating parameters (motor phase current, inverter power loss, coolant temperatures) to calculate coolant flow rate without requiring external calibration data. The controller computes flow rate based on heat dissipation principles using readily available sensor data from the powertrain itself, making the system self-sufficient and eliminating time-consuming calibration processes.
Solution Approach 2:
The patent replaces the traditional mechanical/calibration-based flow rate measurement system with a thermal calculation system. Instead of using calibrated correspondence tables from thermal management systems, the controller calculates flow rate by substituting thermal parameters (power loss, temperature difference, heat capacity) into a heat dissipation equation, eliminating the need for empirical calibration.
3Productivity
If coolant flow rate is estimated using temperature sensor data and pump rotation speed, then productivity is improved, but measurement precision deteriorates due to model-specific calibration requirements
Solution Approach 1:
The system uses the powertrain's own operating parameters (motor phase current, inverter power loss, coolant temperatures) to calculate coolant flow rate without requiring external calibration data. The controller computes flow rate based on heat dissipation principles using readily available sensor data from the powertrain itself, making the system self-sufficient and eliminating time-consuming calibration processes.
Solution Approach 2:
The patent changes the parameters used for flow rate estimation from pump rotation speed and coolant temperature (which require calibration) to inverter power loss and temperature difference across the inverter (which can be directly calculated from electrical parameters and thermal measurements). This parameter substitution eliminates the need for model-specific calibration while maintaining real-time estimation capability.
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 reduces calibration time and improves practicability by allowing real-time coolant flow rate estimation directly within the powertrain, enhancing the accuracy of temperature control and vehicle safety without requiring model-specific data, and mitigates errors in temperature detection.
Implementation Method 1
Coolant in the first cooling loop is configured to cool the inverter
Implementation Method 2
Coolant in the first cooling loop is configured to cool the inverter; electronic pump is configured to drive the coolant to circulate in the first cooling loop
Implementation Method 3
electronic pump is configured to drive the coolant to circulate in the first cooling loop
Data Source
Figure 1
Figure 2~3
Figure 4~5
AI summary
This application provides a powertrain, a coolant flow rate estimation method, and an electric vehicle, and relates to the field of motor cooling technologies. Coolant in a first cooling loop of the powertrain is configured to cool an inverter. An electronic pump drives the coolant to circulate in the first cooling loop. When a phase current of a motor is greater than or equal to a preset current value, a controller determines a rotation speed of the electronic pump at a first moment as a first rotation speed, and determines a coolant flow rate at the first moment based on a temperature at a first position in the first cooling loop, a temperature at a second position in the inverter, and a power loss of the inverter. When the phase current of the motor is less than the preset current value, the controller determines a rotation speed of the electronic pump at a second moment as a second rotation speed, and determines a coolant flow rate at the second moment based on the first rotation speed, the coolant flow rate at the first moment, and the second rotation speed. In the solution of this application, data does not need to be separately calibrated for different thermal management systems. This reduces time consumed by data calibration and improves practicability.