Heavy-Duty Vehicle Control Envelope for Motion Limit Prediction
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Solution Overview
Problem
Heavy-duty vehicles face challenges in maintaining safe and efficient motion due to uncertainties in sensor data and predictive modeling, leading to risks of undesired events like under/over-steering, skid, jack-knifing, and trailer swing, especially when driver inputs exceed vehicle performance limits.
Innovation Solution
A method for controlling heavy-duty vehicle motion that estimates the current and future vehicle state, accounting for uncertainty, and defines a vehicle control envelope to limit motion capabilities when the future state exceeds safety thresholds, using predictive modeling and motion support devices to apply corrective actions such as braking and steering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If driver control inputs are allowed without limitation, then ease of operation is improved, but the risk of excessive control inputs causing vehicle instability increases
Solution Approach 1:
The control system performs preliminary assessment of driver control inputs against predicted vehicle states and control envelopes before executing the commands. If an input is predicted to cause instability, the system pre-processes or limits the command before it reaches the actuators, preventing unstable behavior before it occurs
Solution Approach 2:
The control system acts as an intermediary between the driver and the vehicle actuators. It receives driver inputs, processes them through the predictive model and control envelope checks, and then delivers modified commands to the motion support devices, mediating between driver intent and vehicle response to ensure stability
2Reliability
If the actuator speed control loop is shifted to motion support devices, then disturbance rejection is improved, but device complexity increases
Solution Approach 1:
The control system is segmented into distinct functional layers: a high-level control unit that handles strategic decisions and a lower-level motion support device that handles tactical execution including speed control. This segmentation distributes complexity across multiple independent control modules, each with specialized functions
Data Source
AI summary
A method for controlling motion of a heavy-duty vehicle includes estimating a current vehicle state comprising at least velocity and acceleration, wherein the estimated current state is associated with a current state uncertainty, estimating a future vehicle state based on the current vehicle state, and on a predictive motion model of the vehicle, wherein the future vehicle state is associated with a future vehicle state uncertainty, defining a vehicle control envelope representing an operational limit of the vehicle, wherein the vehicle control envelope defines a range of vehicle states, comparing the estimated future vehicle state, and the associated future vehicle state uncertainty, to the vehicle control envelope, and, if a probability that the future vehicle state breaches the control envelope is above a configured threshold value, limiting a motion capability of the vehicle.