EV Charging Station Control Updates Based on Battery SOH
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Solution Overview
Problem
Existing battery management systems fail to efficiently monitor and update charging/discharging control logic based on battery degradation, which varies with driving habits and environmental conditions, leading to uneven battery performance and reduced service life.
Innovation Solution
A battery performance management system using an electric vehicle charging station that collects and analyzes battery performance evaluation information through a network-connected server, employing an artificial intelligence model to determine degradation levels and update control factors for optimized charging/discharging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Duration of action of stationary object
If battery charging/discharging control logic is not updated based on degradation state, then device complexity is reduced, but battery service life is shortened
Solution Approach 1:
The system pre-establishes multiple charging/discharging control logic templates corresponding to different battery degradation states (SOH ranges). Instead of dynamically generating control logic in real-time, the server selects from pre-prepared templates based on the battery's current SOH, reducing computational complexity while enabling adaptive control throughout the battery lifecycle
Solution Approach 2:
The system changes control parameters (charging current limits, voltage thresholds, temperature constraints) based on battery degradation state. As SOH decreases, the control logic automatically adjusts parameters to reduce stress on the battery, extending service life without requiring complex structural modifications
2Measurement precision
If centralized monitoring of multiple batteries is implemented, then manufacturing precision of battery management is improved, but device complexity increases
Solution Approach 1:
A centralized server acts as an intermediary between multiple batteries and the monitoring system. The server collects performance data from various batteries, performs unified analysis to determine SOH and degradation states, and distributes appropriate control logic. This intermediary structure enables precise centralized monitoring without requiring complex direct connections between all system components
Solution Approach 2:
The server performs multiple functions: data collection from multiple batteries, SOH calculation, degradation state determination, control logic selection, and parameter optimization. This multi-functional approach consolidates what would otherwise require separate specialized systems into a single unified platform
3Reliability
If battery control logic is updated frequently, then reliability is improved, but loss of time increases
Solution Approach 1:
The system implements periodic control logic updates based on significant degradation milestones rather than continuous updates. Control logic is recalibrated when the battery enters new SOH thresholds (e.g., 100-80%, 79-60%, 59-40%, below 40%), ensuring reliability is maintained while avoiding unnecessary frequent updates that would waste time
Data Source
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AI summary
Disclosed is a battery performance management system and method using an electric vehicle charging station. The battery performance management server collects battery performance evaluation information including identification information and operation characteristic accumulative information of a battery, identification information and driving characteristic accumulative information of the electric vehicle, and latest charging characteristic information of the battery from a plurality of charging stations through a network. Also, the server determines a current SOH corresponding to the collected battery performance evaluation information by using an artificial intelligence model that is trained in advance to receive the battery performance evaluation information and output a SOH of the battery. Also, the server determines a latest control factor corresponding to the current SOH, and transmits the latest control factor to the charging station through the network so that the charging station may transmit the latest control factor to a control system of the electric vehicle to update the control factor.