Vehicle Parameter Sets Using Sensor Data for Load and Terrain Adaptation
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Solution Overview
Problem
Existing vehicle configuration settings are not optimized for specific conditions, leading to reduced efficiency and increased wear on components, which can significantly increase operational costs for enterprises with large fleets.
Innovation Solution
A configuration management system that selectively provides parameter sets to vehicles based on predicted or sensed conditions, allowing for supervised or autonomous selection of optimal settings for different sub-fleets and operational components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single configuration setting is used for all vehicles regardless of conditions, then device complexity is reduced, but vehicle efficiency and component durability deteriorate
Solution Approach 1:
The system dynamically adjusts configuration settings based on real-time sensor data and predicted vehicle conditions. Instead of using a static configuration for all vehicles, the system continuously adapts parameters such as engine management, transmission control, and braking systems to match current operating conditions including temperature, altitude, load, and terrain, thereby optimizing efficiency without requiring complex manual reconfiguration
Solution Approach 2:
The vehicle system automatically selects and applies optimal configuration settings based on sensor data and predictive algorithms. The configuration management system autonomously determines the best settings for specific conditions and applies them without requiring manual intervention from operators or complex user interaction, enabling self-optimization while maintaining operational simplicity
2Reliability
If configuration settings are optimized for specific conditions, then component wear is reduced, but the system complexity increases
Solution Approach 1:
The system uses sensor data and predictive algorithms to anticipate future vehicle conditions and pre-adjust configuration settings before actual wear or inefficiency occurs. By predicting conditions such as upcoming terrain changes, temperature variations, or load shifts, the system proactively optimizes parameters to prevent excessive component wear and maintain reliability, rather than reacting after problems arise
Solution Approach 2:
The configuration management system continuously monitors sensor data from the vehicle and uses this feedback to automatically adjust configuration settings. The system compares actual vehicle performance and environmental conditions against optimal parameters, then dynamically modifies settings to maintain component durability and efficiency, creating a closed-loop control system that adapts to changing conditions without manual intervention
Data Source
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AI summary
In some examples, a controller receives measurement data from a sensor on a vehicle, determines, based on the measurement data, a condition of usage of the vehicle, and selects a parameter set from among a plurality of parameter sets based on the determined condition of usage of the vehicle, the plurality of parameter sets corresponding to different conditions of usage of the vehicle, where each parameter set of the plurality of parameter sets includes one or more parameters that control adjustment of one or more respective adjustable elements of the vehicle. The controller causes application of the selected parameter set on the vehicle.