Battery Load Forecasting for Deterioration-Aware Battery Allocation
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Solution Overview
Problem
Current battery management systems for secondary batteries in electric vehicles fail to accurately predict and manage battery deterioration, leading to reduced cruising distance and inefficient vehicle management due to inadequate consideration of past usage history and future battery loads.
Innovation Solution
A battery management system that includes a usage history acquisition unit, deterioration estimation unit, battery load acquisition unit, deterioration change degree identification unit, and battery management unit to estimate current deterioration states, identify deterioration change degrees, and associate secondary batteries with future use modes to minimize deterioration evaluation values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If battery management systems use simple current state monitoring without considering usage history and future loads, then the system complexity is low, but the deterioration prediction accuracy is insufficient
Solution Approach 1:
The system performs preliminary actions by acquiring usage history information before deterioration occurs and estimating future battery loads in advance. The deterioration estimation unit calculates current deterioration states based on past usage patterns, and the battery load acquisition unit predicts future loads, enabling proactive battery management and optimized association before actual deterioration impacts performance.
Solution Approach 2:
The system implements feedback mechanisms where the deterioration estimation unit continuously monitors battery state based on usage history, and the battery management unit uses this feedback to optimize the association between batteries and use devices. The system adjusts associations based on identified deterioration change degrees, creating a closed-loop control that improves prediction accuracy over time.
2Duration of action of stationary object
If the system optimizes battery association based on detailed deterioration analysis, then battery life is extended, but the computational time and processing complexity increase
Solution Approach 1:
The system performs preliminary deterioration estimation and future load prediction before making association decisions. By calculating deterioration states in advance based on usage history and estimating future battery loads, the system prepares optimization data beforehand, reducing real-time computational burden while extending battery life through informed association choices.
Solution Approach 2:
The system focuses on key deterioration factors and critical association decisions rather than analyzing every possible parameter continuously. The deterioration estimation unit identifies significant deterioration change degrees, and the battery management unit makes targeted association optimizations, achieving adequate battery life extension without excessive computational overhead.
3Productivity
If the system frequently updates deterioration estimates and re-optimizes associations, then the management efficiency improves, but the operational complexity and resource consumption increase
Solution Approach 1:
The system implements periodic action by updating deterioration estimates and re-optimizing associations at scheduled intervals or when specific triggers are met. The usage history acquisition unit collects data over periods, the deterioration estimation unit processes updates periodically, and the battery management unit re-optimizes associations at appropriate intervals, balancing management efficiency with operational simplicity.
Solution Approach 2:
The system enables self-service through automated deterioration monitoring and association optimization. The deterioration estimation unit automatically calculates battery states based on acquired usage history, and the battery management unit autonomously makes association decisions based on identified deterioration change degrees, reducing manual operational complexity while maintaining high management efficiency.
Data Source
AI summary
A battery management system includes a usage history acquisition unit, a deterioration estimation unit, a battery load acquisition unit, a deterioration change degree identification unit, and a battery management unit. The usage history acquisition unit acquires usage history information. The deterioration estimation unit estimates a current deterioration state and a deterioration factor of the secondary battery based on the usage history information. The battery load acquisition unit acquires battery load information indicating a future battery load. The deterioration change degree identification unit identifies a deterioration change degree by using the current deterioration state, the deterioration factor and the battery load information of the secondary battery. The battery management unit uses the deterioration change degree to associate secondary batteries with future use modes so that an evaluation value indicating a degree of deterioration of the secondary battery in use devices becomes a minimum value.