Battery Pack Charge Transfer Timing for Vehicle Availability Forecasts
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Solution Overview
Problem
Existing systems for powered vehicles, such as electric vehicles, face challenges in accurately predicting when they will be available for service due to the variability in battery charging times, which affects scheduling and asset usage, as charging times are influenced by factors like battery architecture, current state of charge, and off-board power source capabilities.
Innovation Solution
A charge transfer timing system that calculates the time required to charge or discharge multiple battery packs based on their current state of charge, pack configuration, and depletion configuration, using a controller with processors to determine the predicted charge or depletion time and adjust operations to ensure precise scheduling and efficient usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the powered system charges from an off-board power source to reach a target voltage or energy level, then the batteries are recharged for future operations, but the powered system becomes unavailable for productive use during the extended charging time
Solution Approach 1:
The system performs preliminary calculations of charge transfer time using current state of charge, pack configuration, and charge capability parameters before actually charging. This allows scheduling and planning to be done in advance, reducing the impact of charging time on productivity by enabling better coordination of available time windows.
2Use of energy by moving object
If the charging time is extended to reach a target voltage or energy level, then the batteries are fully recharged, but it becomes difficult to predict when the powered system will be available for active service
Solution Approach 1:
The system continuously monitors actual charge transfer and compares it against predicted values. By tracking parameters like current state of charge, charge capability, and pack configuration during the charging process, the system can update and refine its time predictions, improving accuracy of availability forecasts while maintaining full charge levels.
Solution Approach 2:
The system calculates predicted charge transfer time in advance using current system parameters before charging begins. This preliminary prediction enables better scheduling and communication about when the powered system will be available, reducing uncertainty in service planning.
3Measurement precision
If various factors such as battery architecture, current state of charge, and charge capability are taken into account, then the charge time calculation becomes more accurate, but the system complexity increases
Solution Approach 1:
The system segments the charge time prediction into distinct components: current state of charge assessment, pack configuration analysis, and charge capability evaluation. Each component is calculated separately using specific parameters, then combined to produce the overall predicted time. This modular approach improves accuracy by considering multiple factors while managing complexity through structured calculation steps.
Data Source
AI summary
A charge transfer timing system and method include determining a depletion configuration of one or more loads of a powered system. The one or more loads are configured to be powered by multiple battery packs of the powered system. The charge transfer timing system and method include calculating a time required to deplete the battery packs to at least one of a target voltage or a target energy level. Calculating the time is based at least in part on a current state of charge (SOC) of the battery packs, a pack configuration of the battery packs, and the depletion configuration.