Dynamic EV Battery User Assignment for Degradation Control
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Solution Overview
Problem
Conventional battery systems for electric vehicles face challenges such as high capital costs, degradation in charging/discharging performance over time, and variability in energy storage capacity, necessitating improved monitoring and utilization optimization.
Innovation Solution
A method and system utilizing battery monitoring sensors to collect data on electric vehicle usage, determining usage metrics and user impact metrics to dynamically pair users with vehicles, thereby counteracting battery degradation and optimizing battery life and performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple users share electric vehicles, then battery utilization efficiency improves, but battery degradation variability increases
Solution Approach 1:
The system dynamically assigns users to vehicles based on real-time battery state and user driving behavior profiles. The assignment is not static but continuously adjusted to optimize battery utilization while managing degradation risks through adaptive reassignment strategies.
Solution Approach 2:
The system implements continuous monitoring of battery metrics and user impact metrics, using this feedback to inform assignment decisions. The feedback loop enables the system to learn from actual battery degradation patterns and refine assignment strategies to balance utilization efficiency with battery health preservation.
2Productivity
If aggressive driving behavior is permitted, then vehicle productivity increases, but battery degradation accelerates
Solution Approach 1:
The system changes the operational parameters by which vehicles are used based on battery state and user behavior. Aggressive drivers may be assigned to vehicles with higher state of charge buffers or during periods when the battery is in a more robust state, effectively modulating the intensity and timing of high-stress usage to extend battery life while maintaining overall productivity.
Solution Approach 2:
The system performs preliminary assessment of user driving behavior and battery state before making assignments. By evaluating user impact metrics in advance and pre-positioning users with appropriate vehicles, the system prevents excessive degradation before it occurs while still allowing productive usage.
3Duration of action of stationary object
If battery monitoring and dynamic assignment systems are implemented, then battery life is extended, but system complexity increases
Solution Approach 1:
The monitoring system serves multiple functions simultaneously: it tracks battery state for health management, collects user behavior data for assignment optimization, and provides the information needed for utilization efficiency analysis. This multi-functionality reduces the need for separate specialized systems, thereby limiting the increase in overall system complexity.
Solution Approach 2:
The system enables battery health management and optimization without requiring intensive external intervention. Through automated monitoring, analysis, and assignment decisions, the system serves itself in managing battery life, reducing the operational burden and complexity of manual battery management processes.
Data Source
AI summary
Methods and systems for monitoring and optimizing utilization of batteries for electric vehicles are described. Data of battery usage of electric vehicles are monitored using battery monitoring sensors at the electric vehicles for a plurality of users who share use of electric vehicles. Battery usage metrics are determined for the batteries of the electric vehicles based on the data of battery usage and determining user impact metrics based on measured quantities relating to driving of the electric vehicles for the plurality of users, the user impact metrics being indicative of degrees of driving severity placed on the vehicles associated with use habits of particular users. The battery usage metrics and the user impact metrics for the plurality of users are analyzed at a computer processing system to determine a particular user to assign to a particular electric vehicle in a given time period to counteract battery degradation of the battery in a particular electric vehicle, and a particular user is paired with the particular electric vehicle.