Adaptive Nonlinear Model Predictive Cruise Control
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Solution Overview
Problem
Existing cruise control systems experience large swings in torque demand when maintaining vehicle speed, leading to increased fuel consumption and driver discomfort, as they rely on reactionary PID algorithms and operate primarily in higher gears.
Innovation Solution
The implementation of an adaptive nonlinear model predictive cruise control system that adjusts torque control strategies based on real-time vehicle and fuel consumption models, incorporating a priori road grade information and allowing for pulse and glide torque outputs to optimize fuel economy, and selectively shifting the transmission into neutral to reduce fuel consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If PID algorithm is used to maintain vehicle speed in cruise control mode, then vehicle speed can be maintained within desired range, but large torque swings occur leading to increased fuel consumption
Solution Approach 1:
The model predictive controller uses a priori road grade information to predict future vehicle speed and proactively adjusts torque demand before speed deviations occur. This predictive approach eliminates the reactionary nature of PID control, preventing large torque swings by preparing appropriate torque adjustments in advance based on anticipated road conditions.
Solution Approach 2:
The controller dynamically adapts the vehicle model parameters in real-time to match actual vehicle operating conditions. By continuously updating the model to reflect current vehicle state, the controller optimizes torque trajectories dynamically, reducing unnecessary torque variations while maintaining speed stability under changing conditions.
2Productivity
If PID algorithm makes large torque adjustments to correct speed errors, then vehicle speed returns to desired range faster, but driver comfort is disturbed
Solution Approach 1:
By predicting future speed deviations based on road grade information, the controller makes gradual, pre-planned torque adjustments rather than abrupt reactive corrections. This smoothing of torque trajectories maintains speed control effectiveness while eliminating sudden torque changes that disturb driver comfort.
Solution Approach 2:
The controller optimizes torque trajectories by adjusting control parameters to minimize torque variations while achieving speed control objectives. This parameter optimization allows speed correction to occur through smooth, progressive torque adjustments rather than large sudden changes, maintaining both productivity and comfort.
Data Source
AI summary
Methods and systems are presented for improving performance of a vehicle operating in a cruise control mode where a controller adjusts torque output from a vehicle to maintain vehicle speed within a desired range. The methods and systems include adapting a vehicle dynamics model and a vehicle fuel consumption model that provide input to nonlinear model predictive controller.