Vehicle Weight Classification for Payload-Aware Route Optimization
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Solution Overview
Problem
Current systems for improving vehicle energy efficiency do not effectively address the unique factors affecting electric vehicles, which are different from those affecting internal combustion engine vehicles, necessitating a new approach to optimize energy conservation in electric vehicles.
Innovation Solution
A system and method that dynamically classify changes in vehicle weight by monitoring weight changes using sensors and categorizing them as occupant or cargo weight changes, enabling optimized route planning and user feedback through a human-machine interface to enhance energy efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If current systems for improving vehicle energy efficiency (VVT, GDI, cylinder deactivation) are used, then fuel efficiency of internal combustion engine vehicles is improved, but these systems do not effectively address the unique factors affecting electric vehicles
Solution Approach 1:
The system changes the operational parameters by transitioning from engine-centric efficiency improvements (VVT, GDI) to electric vehicle-specific parameters including real-time weight monitoring, route optimization based on payload, and energy consumption tracking. This allows the system to adapt efficiency improvements to the unique characteristics of electric vehicles.
Solution Approach 2:
The control system is designed to be universal by incorporating multiple functions: monitoring vehicle weight, determining weight changes, comparing against thresholds, categorizing weight changes as occupant or cargo, optimizing routes, and providing user notifications. This multi-functional system can serve both traditional and electric vehicles, addressing the adaptability requirement.
2Use of energy by moving object
If vehicle weight is monitored and route optimization is provided, then energy efficiency is improved and range is extended, but system complexity increases
Solution Approach 1:
The control system integrates multiple functions into a single universal platform: weight monitoring, weight change detection, threshold comparison, weight change categorization, route optimization, and user notification. This consolidation reduces overall system complexity compared to having separate systems for each function.
Solution Approach 2:
The system uses existing vehicle infrastructure (sensors, communication systems, HMI) to perform weight monitoring and route optimization functions. By leveraging already-present components, the system avoids adding significant complexity while achieving energy efficiency improvements.
3Duration of action of moving object
If real-time weight monitoring and route optimization are implemented, then vehicle range is extended, but measurement and detection difficulty increases
Solution Approach 1:
The system replaces complex mechanical weight measurement systems with electronic sensing and computational methods. By using sensors to detect weight changes and processing this data through algorithms that compare readings against thresholds, the system simplifies the detection process while improving accuracy and enabling real-time monitoring.
Data Source
AI summary
A method for classifying a weight of a vehicle includes determining a system enablement state of the vehicle load detection and classification system, monitoring a vehicle weight, determining a change in the vehicle weight, comparing the change in the vehicle weight to a first predefined weight change threshold, and categorizing the change in the vehicle weight in response to determining that the change in the vehicle weight exceeds the first predefined weight change threshold. The method also includes determining if a weight has been left in the vehicle after key-off and determining if a weight has been placed in a cargo compartment of the vehicle which exceeds the weight rating of the cargo compartment. The method also includes optimizing a route to a destination based at least on the change in the vehicle weight and displaying the optimized route to the destination using a human machine interface of the vehicle.