Test Vehicle Speed Control Using Dual Accelerator Maps
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Solution Overview
Problem
Existing automatic driving systems require pre-learning for each vehicle to create a running performance map, which takes about 20 to 40 minutes and hinders test efficiency.
Innovation Solution
An automatic test object driving device using a first and second accelerator/decelerator map to determine and correct accelerator/decelerator amounts based on command vehicle speed, employing feedforward and feedback control to drive test vehicles without pre-learning, with map update mechanisms to refine performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If pre-learning is performed to obtain a running performance map for each test vehicle, then the automatic driving system can accurately control the vehicle speed, but the test efficiency is reduced due to the time-consuming pre-learning process (20 to 40 minutes per vehicle)
Solution Approach 1:
The system performs preliminary acquisition of accelerator maps and decelerator maps for multiple vehicle models in advance. These pre-acquired maps are stored and can be directly applied during testing without requiring time-consuming pre-learning for each individual vehicle, thus eliminating the 20-40 minute pre-learning wait time while maintaining control accuracy.
Solution Approach 2:
Instead of creating a unique running performance map for each test vehicle through pre-learning, the system uses copied accelerator maps and decelerator maps that have been previously acquired for different vehicle models. The appropriate pre-acquired map is selected and applied based on the test vehicle's characteristics, avoiding redundant pre-learning processes.
2Device complexity
If a single accelerator map is used for all vehicle models, then the system complexity is reduced, but the adaptability to different vehicle characteristics is insufficient
Solution Approach 1:
The system maintains a collection of accelerator maps and decelerator maps that can be universally applied across multiple different vehicle models. Each map is designed to be compatible with specific vehicle model categories, allowing the same map to serve multiple vehicle types without requiring custom pre-learning for each model, thus achieving both simplicity and adaptability.
Solution Approach 2:
The system adapts to different vehicle characteristics by selecting appropriate pre-acquired maps based on vehicle parameters such as vehicle weight, engine type, and transmission characteristics. The stored maps contain parameter variations that allow the system to match the test vehicle's characteristics and apply the most suitable control map without increasing system complexity.
Data Source
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AI summary
The present invention is intended to make it possible to automatically drive a test object without performing pre-learning for a running performance map for each vehicle. There is provided an automatic test object driving device 100 that automatically drives a test vehicle V based on a command vehicle speed, and that includes a driving actuator for performing driving operation of the test vehicle V, and a driving control unit 3 for controlling the driving actuator. The driving control unit 3 includes a first accelerator map 10A and a second accelerator map 10B each of which indicates a relationship among a vehicle-speed-related value, an acceleration-related value, and an accelerator-depression-amount-related value. The driving control unit 3 uses the first accelerator map 10A to determine an accelerator depression amount corresponding to the command vehicle speed, and uses the second accelerator map 10B to correct the accelerator depression amount by feeding back a vehicle speed and an acceleration of the test vehicle V.