Cruise Control Speed Planning Using Fleet Wind Distribution
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Solution Overview
Problem
Existing cruise control systems struggle with inaccurate wind forecasts, which are difficult to create due to the complex interaction of wind with diverse landscapes, leading to inefficiencies in energy consumption.
Innovation Solution
A method that utilizes statistical wind distribution derived from a fleet of vehicles with wind sensors, sharing data with an off-board server to create a wind map, allowing for precise adjustment of vehicle speed to optimize energy consumption without relying on weather forecasts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If wind forecasts are used to optimize cruise control, then energy consumption can be reduced, but the accuracy deteriorates due to high errors in wind forecasts especially in regions with diverse landscapes
Solution Approach 1:
The system continuously measures actual wind conditions using onboard sensors and uses this feedback to adjust cruise control decisions in real-time, replacing inaccurate open-loop wind forecasts with closed-loop feedback-based control
Solution Approach 2:
Each vehicle independently measures its own wind conditions using onboard sensors rather than relying on external forecast services, making the system self-sufficient and accurate for its specific location and conditions
2Measurement precision
If wind sensors are installed on vehicles to measure local wind conditions, then wind measurement accuracy improves, but device complexity increases
Solution Approach 1:
The wind sensor is integrated into the existing cruise control system, allowing it to serve multiple functions: measuring wind conditions for energy optimization, providing data for fleet-wide statistical models, and enabling real-time speed adjustments without requiring separate dedicated systems
Solution Approach 2:
The patent combines individual vehicle wind measurements with fleet-wide statistical wind distribution data, merging local real-time measurements with aggregate historical data to create a comprehensive control strategy that leverages both specific and general information
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables energy-optimized vehicle speed adjustment by dynamically increasing or decreasing speed based on real-time wind conditions, reducing energy consumption and maintaining a desired average speed.
Implementation Method 1
the current local wind conditions (wind speed and direction) are ascertained with the aid of wind sensors
Implementation Method 2
The energy consumed to overcome air resistance is proportional to the square of the speed
Data Source
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AI summary
The invention relates to a method for the energy-optimised specifying of a current vehicle speed for a selected desired average speed (|vv|) of a planned driving route, while taking a wind distribution (P) along the driving route into consideration. The method according to the invention is characterised in that the wind distribution is provided by a vehicle-external server (15) in the form of wind values for multiple consecutive positions along or in the local region of the planned driving route, wherein local wind values are based on measurement values that are detected by a plurality of vehicles of a vehicle fleet (11) by means of wind sensors (12) and shared with the vehicle-external server (15).