Battery Pack Health Estimation Through Discharge Tracking
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Solution Overview
Problem
Existing rechargeable batteries, particularly lead acid batteries, have limitations such as size, energy storage capacity, slow charging, overheating, and short life cycles, which are not suitable for fast charging and require specialized facilities for safe charging, and lithium-ion batteries need improved longevity to enhance return on investment.
Innovation Solution
A system and method for determining the state of health of a battery pack using predictive quantum balancing, which includes storing charge usage data, setting operating state of charge ranges based on usage thresholds, and balancing cell voltages to extend battery life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If lithium-ion batteries are used instead of lead acid batteries, then energy storage capacity and power output are improved, but battery life and reliability need further enhancement
Solution Approach 1:
The system performs preliminary actions by storing charge usage data for multiple days and analyzing usage patterns before determining the state of health. The controller proactively monitors depth of discharge, charge capacity, and cycle life estimation to predict battery condition before failure occurs, enabling preventive maintenance and extending battery life.
Solution Approach 2:
The system implements feedback by continuously monitoring battery parameters (depth of discharge, charge capacity, temperature) and using this information to update state of health indicators. The controller adjusts charging strategies based on real-time battery condition feedback, optimizing both performance and longevity.
2Speed
If fast charging is implemented, then charging speed is improved, but overheating and safety hazards worsen
Solution Approach 1:
The system applies dynamics by adjusting the state of charge range dynamically based on real-time usage data. The controller modifies charging parameters adaptively, expanding the state of charge range when usage is low and contracting it when usage is high, thereby managing thermal load and preventing overheating during fast charging operations.
Solution Approach 2:
The system changes parameters by adjusting the operating state of charge range according to usage patterns. The controller modifies charging voltage, current, and state of charge thresholds based on monitored depth of discharge and charge capacity data, optimizing charging speed while maintaining safe operating temperatures.
3Productivity
If the state of charge range is expanded to maximize battery utilization, then energy availability is improved, but battery degradation and life cycle worsen
Solution Approach 1:
The system dynamically adjusts the state of charge range based on real-time usage data and battery condition. The controller expands the state of charge range when usage is low to maximize energy availability, and contracts it when usage is high or battery condition deteriorates, thereby optimizing the balance between productivity and battery life cycle.
Solution Approach 2:
The system changes the operating parameters by adjusting the state of charge range according to usage patterns and battery health indicators. The controller modifies charge and discharge thresholds to optimize energy availability while preventing excessive degradation, thereby extending battery life cycle.
Data Source
AI summary
A system and method of determining a battery condition includes a discharge circuit determining a depth of discharge prior to charging a battery and determining an average depth of discharge over a time period. A cycle life estimation module determines a cycle life estimation based on the average depth of discharge. A state of health determination circuit determines a state of health of the battery based on the cycle life estimation. A display displays a state of health indicator.