Battery Range Prediction for Faster EV Battery Swaps
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Solution Overview
Problem
Conventional techniques for sharing electric moving bodies, such as electric motorcycles and bicycles, do not account for batteries being lent out during charging, leading to insufficient availability when demand is concentrated, requiring users to wait until batteries are fully charged, which slows down replacement processes.
Innovation Solution
An information processing method that calculates and outputs a travelable range for an electric moving body based on the remaining power of a battery at a charging spot, allowing users to determine if the battery can be used, and providing map information to navigate to charging spots and destinations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the system waits for batteries to be fully charged before lending them out, then the battery charge completeness is improved, but the battery availability and replacement speed deteriorate
Solution Approach 1:
The system performs preliminary charging actions on batteries and calculates their projected remaining power at expected delivery times in advance. By pre-calculating travelable ranges based on current charge levels and charging speeds, the system prepares battery availability information before actual delivery, enabling users to make informed decisions without waiting for full charging completion.
Solution Approach 2:
The system dynamically updates the remaining power information and travelable range calculations as charging progresses and delivery times approach. The travelable range is not a fixed value but dynamically adjusts based on real-time charging status, battery capacity, and expected delivery time, allowing flexible optimization between charge completeness and availability.
2Reliability
If the system provides only fully charged batteries, then the reliability of battery performance is improved, but the quantity of available batteries for immediate use deteriorates
Solution Approach 1:
The system changes the evaluation parameter from binary (fully charged/not charged) to continuous (remaining power percentage at delivery time). By calculating projected remaining power levels and corresponding travelable ranges, the system transforms the battery availability assessment into a multi-parameter decision framework that considers charge level, charging speed, and delivery timing, thereby expanding the pool of usable batteries.
3Measurement precision
If the system calculates travelable range based on real-time remaining power information, then the information accuracy for users is improved, but the computational complexity increases
Solution Approach 1:
The system introduces an intermediary calculation layer that bridges current battery status and future delivery conditions. By using the charging speed as a mediator parameter, the system linearly projects remaining power at delivery time based on current charge levels and expected charging duration, simplifying the calculation while maintaining reasonable accuracy for user decision-making.
Data Source
AI summary
A server acquires remaining power information indicating a remaining power amount of a battery being charged at a charging spot and time information indicating a time required for a moving body to receive the battery at the charging spot, calculates a travelable range in which the moving body is travelable from the charging spot with the remaining power amount of the battery at a time of reception of the battery at the charging spot, based on the remaining power information and the time information, and outputs range information indicating the travelable range.