Predictive Cruise Control Horizon Speed Management
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Solution Overview
Problem
Conventional cruise control systems are inefficient in hilly terrain, leading to excessive fuel consumption as they maintain a constant speed, which results in unnecessary acceleration and braking, whereas varying speed based on terrain can optimize fuel usage.
Innovation Solution
A method and module that determine a horizon of route segments with gradient characteristics, calculate threshold values, and adjust entry speeds to maintain a speed range, allowing for speed corrections on steep upgrades and downgrades to optimize fuel efficiency by utilizing kinetic energy and avoiding unnecessary acceleration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Stability of the object's composition
If conventional cruise control maintains constant speed in hilly terrain, then speed stability is improved, but fuel consumption increases due to unnecessary acceleration and braking
Solution Approach 1:
The system dynamically adjusts the vehicle speed based on predicted terrain conditions (upgrades and downgrades) rather than maintaining a constant speed. The cruise control adapts its speed profile in real-time according to the horizon data, allowing speed variations that optimize fuel consumption while navigating hilly terrain.
Solution Approach 2:
The system uses map data and GPS to predict upcoming terrain features (upgrades and downgrades) in advance. By knowing the horizon ahead, the cruise control can proactively adjust speed before encountering steep sections, accelerating before upgrades to maintain momentum and coasting through downgrades to recover energy, rather than reacting to terrain changes after they occur.
2Use of energy by moving object
If the system accelerates before upgrades and coasts through downgrades, then fuel consumption is reduced, but speed control complexity increases
Solution Approach 1:
The system introduces an intermediary layer between the driver's speed request and the actual vehicle control. This intermediary module processes the requested speed, predicts upcoming terrain features using map and GPS data, and generates optimized speed setpoints that account for future upgrades and downgrades. This intermediary layer handles the complexity of predictive control while presenting a simple interface to the driver.
Solution Approach 2:
The system continuously monitors actual vehicle speed, position, and terrain conditions, comparing them against the predicted horizon and desired speed profile. This feedback loop allows the cruise control to make real-time adjustments to maintain optimal speed, correcting deviations caused by varying road gradients, vehicle load, or driver inputs while learning from actual performance.
3Ease of operation
If the vehicle maintains set speed through braking on downgrades, then speed control is simplified, but energy is wasted and fuel efficiency decreases
Solution Approach 1:
The system converts the previously harmful effect of gravity-induced acceleration on downgrades into a beneficial energy recovery opportunity. By anticipating downgrades through horizon prediction, the cruise control allows the vehicle to coast and naturally decelerate under gravity, converting gravitational potential energy into kinetic energy that can be used for subsequent upgrades, rather than braking to dissipate this energy as heat.
4Use of energy by moving object
If the system uses map data and GPS for horizon prediction, then fuel efficiency is improved, but device complexity and computational requirements increase
Solution Approach 1:
The system leverages existing multi-functional components already present in modern vehicles, particularly GPS receivers and digital map databases used for navigation and routing. By repurposing these existing systems for predictive cruise control, the invention avoids adding dedicated hardware for horizon prediction, instead utilizing the universal positioning and mapping infrastructure already integrated into the vehicle's infotainment or navigation system.
Data Source
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Figure 2(A)~2(F)
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AI summary
The invention relates to a method for regulating a vehicle's speed. The method comprises the steps of: determining a horizon by means of position data and map data of an itinerary made up of route segments with length and gradient characteristics for each segment; calculating threshold values for the gradient of segments according to one or more vehicle-specific values, which threshold values serve as boundaries for assigning segments to various categories; comparing the gradient of each segment with the threshold values and placing each segment within the horizon in a category according to the results of the comparisons; and, for each segment within the horizon which is in a category indicating a steep upgrade or a steep downgrade, the method comprises: calculating the vehicle's final speed vend after the end of the segment, based inter alia on the entry speed vi to said segment; and determining the entry speed vi for said segment based on the calculated final speed vend for the segment, which determination is defined by rules for said segment's category, so that the vehicle's final speed vend is within the range defined by vmax and vmin for the vehicle's current reference speed vset, on the supposition that Vi is determined within the same range; and regulating the vehicle's speed according to speed set-point values vref based on the entry speeds vi to each segment.