Hybrid EV Torque Learning Across Engine Load Regions
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Solution Overview
Problem
Hybrid electric vehicles experience errors in engine torque control due to discrepancies between command torque and actual torque, leading to inaccuracies in power management.
Innovation Solution
A hybrid electric vehicle system with two motors connected to the engine, where one motor is always connected and the other is selectively connected, learns the actual engine torque through both motors and compensates the engine modeling torque based on this actual torque to reduce errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If engine torque control is performed based on command torque, then power control is simplified, but errors occur between command torque and actual torque leading to degradation of control accuracy
Solution Approach 1:
The patent implements feedback by measuring the actual torque output of the engine and using this measured value to correct the command torque. The controller continuously monitors the discrepancy between commanded and actual torque, and adjusts future torque commands based on this feedback loop, thereby improving control accuracy without complicating the overall power control system.
Solution Approach 2:
The patent replaces direct mechanical torque measurement with an electrical/electronic measurement system. Instead of using complex mechanical torque sensors, the system uses electrical signals from the motor and controller to calculate and determine actual engine torque, substituting mechanical measurement with electronic computation to maintain simplicity while improving accuracy.
2Device complexity
If a single motor is used for torque learning, then device complexity is reduced, but torque learning accuracy and adaptability across different engine load regions deteriorates
Solution Approach 1:
The patent segments the torque learning process into different engine load regions (low load region and high load region). Each region uses a specific motor configuration optimized for that load range: the first motor for low load and the second motor for high load. This segmentation allows accurate torque learning across the entire operating range while managing device complexity through selective activation.
Solution Approach 2:
The patent dynamically switches between different motor configurations based on the current engine load region. The controller determines which motor to use for torque learning based on real-time operating conditions, making the system adaptive and flexible. This dynamic approach enables accurate torque measurement across varying loads without requiring both motors to be permanently connected.
Data Source
AI summary
Proposed are a hybrid electric vehicle and a power control method for the hybrid electric vehicle. The power control method includes: determining an engine load region of the vehicle, learning an actual torque of an engine based on the amount of power generated by at least one motor corresponding to the engine load region among a plurality of motors provided in the hybrid electric vehicle, and compensating engine modeling torque based on the actual torque of the engine learned through the motor.