Heavy-Duty Vehicle Motion Control Using Predictive Environment Sensing
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Solution Overview
Problem
Existing vehicle motion management systems for heavy-duty vehicles rely heavily on feedback-based control, which can lead to significant discrepancies between desired and actual vehicle states due to environmental changes, resulting in inefficient component wear and reduced stability.
Innovation Solution
Implementing a control unit that utilizes environment sensors to predict the impact of ambient conditions on vehicle motion and coordinates motion support devices (MSDs) to compensate for these changes before they occur, using feedforward control to minimize discrepancies and optimize actuation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If feedback-based MSD control is used to reduce discrepancy between estimated and desired vehicle state, then the discrepancy is reduced, but the response is delayed because control actions are taken only after the discrepancy already exists
Solution Approach 1:
The control unit performs preliminary actions by predicting future vehicle states and environmental impacts before they occur. Environment sensors detect upcoming conditions (road surface changes, wind, gradients), and the control unit pre-adjusts MSD settings to compensate for these predicted changes, rather than reacting after discrepancies arise. This eliminates the time loss inherent in traditional feedback control.
Solution Approach 2:
The system applies preliminary anti-action by anticipating environmental disturbances and applying counteracting control actions in advance. For example, if increased rolling resistance is predicted ahead, the control unit adjusts propulsion force beforehand to counteract the upcoming resistance, preventing the discrepancy from forming in the first place.
2Speed
If stronger MSD actuation is applied to quickly correct vehicle state discrepancies, then the correction speed increases, but component wear increases
Solution Approach 1:
By taking preliminary control actions based on predicted environmental changes, the system prevents large discrepancies from forming, thereby avoiding the need for strong corrective actuation. The MSDs make gradual adjustments in advance, maintaining correction effectiveness while minimizing wear.
Solution Approach 2:
The system applies partial action by making small, progressive MSD adjustments based on predicted environmental impacts, rather than applying full corrective force only when discrepancies become large. This distributed partial action achieves the same correction goal with significantly reduced component stress and wear.
3Stability of the object's composition
If environment sensors and prediction systems are added to enable predictive control, then vehicle motion smoothness and stability improve, but device complexity increases
Solution Approach 1:
The control unit leverages existing environment sensors (camera, radar, LIDAR, anemometers) that serve multiple functions in the vehicle system, integrating them into the predictive control framework. This multi-functional approach enables predictive capabilities without adding dedicated single-purpose sensors, thereby limiting the increase in overall system complexity.
Solution Approach 2:
The system implements a feedback loop where environment sensor data is continuously processed, vehicle state is monitored, and control actions are adjusted based on the difference between predicted and actual states. This feedback mechanism refines prediction accuracy over time and optimizes control performance without requiring overly complex algorithms.
Data Source
AI summary
A control unit for controlling a heavy-duty vehicle, the control unit being arranged to receive ambient environment data from one or more environment sensors on the heavy-duty vehicle, and to predict an impact of the ambient environment on the motion of the heavy-duty vehicle, wherein the control unit is arranged to coordinate control of one or more motion support devices, MSDs, on the heavy-duty vehicle to compensate for the predicted impact of the ambient environment on the motion of the heavy-duty vehicle.