Predictive Vehicle Control Using Power Tolerance Bands
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Solution Overview
Problem
Existing driver models for vehicle control, optimized for current vehicle speed requirements, lead to frequent acceleration and deceleration processes, resulting in increased fuel consumption and pollutant emissions, which do not accurately reflect human driving behavior.
Innovation Solution
A method that determines a target performance curve with a tolerance band and an expected characteristic curve, releasing control commands only when the vehicle's performance intersects the tolerance band's limits within a prediction window, allowing for more efficient fuel and pollutant management by reducing unnecessary acceleration and braking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If driver model controls vehicle based solely on current vehicle speed requirement, then vehicle speed control is simple and responsive, but frequent acceleration and deceleration occur leading to increased fuel consumption and pollutant emissions
Solution Approach 1:
The driver model performs preliminary actions by anticipating future speed requirements and proactively adjusting vehicle settings before deviations occur. The model determines expected characteristic curves for future time points and adjusts acceleration/deceleration in advance to stay within tolerance bands, rather than reacting only to current deviations.
Solution Approach 2:
The system implements feedback by continuously monitoring the difference between expected characteristic curves and target curves, and adjusting vehicle control commands based on this feedback. The driver model uses the calculated differences and tolerance band information to modulate acceleration and deceleration commands, creating a closed-loop control system.
2Device complexity
If driver model controls vehicle based solely on current vehicle speed requirement, then control system is simple to implement, but vehicle operation does not reflect human driver behavior
Solution Approach 1:
The driver model anticipates future speed requirements by determining expected characteristic curves for multiple future time points based on current vehicle settings. This preliminary action allows the model to plan acceleration and deceleration sequences that mimic human driving patterns, rather than reacting only to current deviations.
Solution Approach 2:
The control system dynamically adjusts vehicle settings by modulating acceleration and deceleration commands based on real-time calculations of expected characteristic curves and tolerance bands. The system adapts its control strategy continuously, changing acceleration rates and timing to maintain optimal operation within tolerance bands.
3Manufacturing precision
If driver model makes frequent control adjustments to meet speed requirements, then vehicle speed follows target curve closely, but fuel efficiency and pollutant emissions increase
Solution Approach 1:
The system changes operational parameters by introducing tolerance bands around the target power curve and adjusting vehicle settings to operate within these bands. Instead of maintaining exact target speed at all times, the system allows controlled deviations within tolerance limits, reducing frequent adjustments while maintaining acceptable performance.
Solution Approach 2:
The driver model performs preliminary adjustments to vehicle settings based on anticipated future conditions. By determining expected characteristic curves for future time points and adjusting acceleration/deceleration in advance, the model maintains speed within tolerance bands without requiring frequent reactive adjustments, thereby reducing fuel consumption and emissions.
Data Source
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AI summary
The present invention relates to an apparatus having at least one computing unit, which is configured to ascertain a specified target power profile curve (213) for a vehicle, to determine a tolerance band (211) for the target power profile curve (213), wherein the tolerance band (211) is restricted by an upper limit line (215) and a lower limit line (217), to determine an expectation characteristic curve (219) for a power of the vehicle to be expected in the future by extrapolating a power development of the vehicle at a current adjustment of the vehicle for a specified temporal prediction window (229), and to enable a control command (315, 319) to be provided by the driver model in order to modify the adjustment of the vehicle in the event that the expectation characteristic curve (219) intersects at least one of the upper limit line (215) and the lower limit line (217) of the tolerance band (211) within the temporal prediction window (229).