BEV Torque Control Using Virtual Vehicle Travel Resistance
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Solution Overview
Problem
Existing battery electric vehicles (BEVs) struggle to accurately reproduce the driving feel of virtual vehicles, leading to a suboptimal driver experience due to the lack of consideration for travel resistance differences between the BEV and the virtual vehicle.
Innovation Solution
The BEV includes processors that calculate target torque based on the travel resistance of a virtual vehicle, controlling the electric motor to simulate the behavior of the virtual vehicle, thereby enhancing the driving feel by accounting for both powertrain and resistance differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the driving force of a virtual vehicle is reproduced by controlling torque of the electric motor without considering travel resistance differences, then the basic driving feel can be reproduced, but the accuracy of reproducing the virtual vehicle's driving characteristics deteriorates
Solution Approach 1:
The control device pre-acquires travel resistance information for multiple virtual vehicles and stores it in memory. When a virtual vehicle is selected, the corresponding travel resistance data is already available for immediate use in torque calculations, eliminating the need for real-time measurement or complex on-demand computation.
Solution Approach 2:
The control device introduces travel resistance as an intermediary parameter that mediates between the electric motor's torque output and the virtual vehicle's driving characteristics. By incorporating this intermediate factor, the system accurately translates motor torque into virtual vehicle behavior that reflects both powertrain and resistance differences.
2Ease of operation
If the torque of the electric motor is controlled solely based on target torque calculation without travel resistance consideration, then the control process is simple, but the driver satisfaction deteriorates due to inaccurate driving feel reproduction
Solution Approach 1:
Travel resistance values for various virtual vehicles are pre-calculated and stored in the control device's memory. During operation, the system simply retrieves the appropriate value based on the selected virtual vehicle, maintaining fast response times while incorporating comprehensive resistance data into the torque control calculation.
Solution Approach 2:
The control device adjusts the torque control parameter by incorporating travel resistance as an additional variable. The target torque is calculated by combining the virtual vehicle's powertrain characteristics with its specific travel resistance, dynamically changing the control parameter to match different virtual vehicle profiles while maintaining efficient processing.
Data Source
AI summary
The present disclosure relates to battery electric vehicles including an electric motor as a driving source. Battery electric vehicle comprises one or more processors that control the electric motor to reproduce the behavior of the virtual vehicles that differ from battery electric vehicle. The one or more processors calculate the target torque based on the travel resistance of the virtual vehicle, and control the torque of the electric motor based on the target torque.