Shared Vehicle Dispatch Using Driver Grades and Battery SOH
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Solution Overview
Problem
The aging rate of batteries in shared electric vehicles varies significantly due to different driving habits of users, leading to inefficient battery management and potential errors in estimating driving range.
Innovation Solution
A shared vehicle dispatch system that learns user driving patterns, assigns driver grades based on these patterns, and matches vehicles with batteries of varying State of Health (SOH) to these grades, ensuring that vehicles with higher SOH are dispatched to users with less efficient driving habits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If shared vehicles are dispatched without considering driver driving patterns, then dispatch operation is simple, but battery aging rate varies significantly
Solution Approach 1:
The system performs preliminary learning of driver driving patterns and classification into driver grades before vehicle dispatch. The vehicle controller continuously learns operational data (acceleration, deceleration, speed, SOC consumption) and the operation server classifies drivers into grades (e.g., grade 1 for aggressive drivers, grade 2 for moderate drivers). This preliminary classification enables optimized vehicle-battery matching in subsequent dispatch operations, reducing battery aging variations without complicating the actual dispatch process.
Solution Approach 2:
The system changes the dispatch parameter from simple vehicle availability to a composite parameter including driver grade and battery SOH (State of Health). By introducing driver grade classification based on learning driving pattern information, the dispatch decision incorporates multiple parameters (driver grade, battery SOH, SOC) to optimize battery aging management. This parameter expansion resolves the contradiction by making dispatch sufficiently sophisticated to manage aging while maintaining operational efficiency.
2Speed
If vehicles are dispatched without considering battery health status, then dispatch process is fast, but driving range estimation becomes inaccurate
Solution Approach 1:
The system implements feedback loops where the vehicle controller continuously monitors battery status (SOC, SOH) and operational data, transmits this information to the operation server, and receives dispatch decisions based on current battery health. The operation server updates driver grades and matches vehicles considering real-time battery status. This feedback mechanism ensures driving range estimation accuracy by continuously incorporating battery health data into dispatch decisions without significantly slowing down the process.
Solution Approach 2:
The operation server performs preliminary assessment of battery health status and driver grade matching before final dispatch confirmation. By pre-evaluating the compatibility between driver behavior patterns and battery health status, the system prepares optimized dispatch decisions in advance, ensuring accurate driving range estimation while maintaining fast dispatch processing through efficient pre-computation.
3Productivity
If aggressive drivers use vehicles with healthy batteries, then driving performance is maximized, but battery aging accelerates
Solution Approach 1:
The system applies local quality by matching specific vehicle-battery combinations to specific driver grades. Instead of uniform dispatch, the operation server creates localized optimizations where aggressive drivers (grade 1) are assigned vehicles with batteries having higher initial SOH or newer batteries, while moderate drivers (grade 2) receive vehicles with batteries having lower SOH. This localized matching strategy allows aggressive driving performance while managing battery aging rates through differentiated allocation.
Solution Approach 2:
The system changes the dispatch parameter to include both driver grade and battery SOH as matching criteria. By introducing the SOH parameter into the dispatch decision-making process, the system can optimize the allocation of battery health resources across different driver types. Aggressive drivers receive appropriately matched batteries that can handle their driving style, while the overall fleet battery lifespan is extended through strategic allocation based on learned driving patterns.
Data Source
AI summary
A shared vehicle dispatch system dispatches shared vehicles based on driver grades classified by learning user driving patterns, and a shared vehicle dispatch method uses the shared vehicle dispatch system. The shared vehicle dispatch system includes a shared vehicle having a vehicle controller configured to learn driving pattern information of a user, a user terminal, operated by the user, equipped with a dedicated application installed for requesting the dispatch of the shared vehicle, and an operation server communicating with the shared vehicle to receive the learned driving pattern information, where the operation server may determine a driver grade for the user who operated the shared vehicle based on the received driving pattern information.