Battery Charge Timing Control for Accurate Fleet Scheduling
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Solution Overview
Problem
Existing systems for electric vehicles and powered systems face challenges in accurately predicting charge times due to factors like battery architecture, current state of charge, and off-board power source capabilities, leading to inefficiencies in scheduling and asset usage.
Innovation Solution
A charge transfer timing system that determines the time required to charge or discharge battery packs by analyzing the current state of charge, pack configuration, and charge capability of power sources, using a controller with processors to calculate and adjust for precise scheduling and operation planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If extended charging time is used to reach target voltage or energy level, then battery charge completeness is improved, but system availability for productive use deteriorates
Solution Approach 1:
The system performs preliminary calculations of charge time requirements before charging begins, using known parameters (battery capacity, power source capability, target energy level) to predict when charging will complete. This allows advance planning of vehicle deployment schedules without requiring extended buffer time for charging operations.
Solution Approach 2:
The system continuously monitors charging progress and compares actual state of charge against predicted trajectories, adjusting predictions in real-time based on actual charging rates. This feedback mechanism provides accurate, up-to-date estimates of time to completion, enabling dynamic scheduling adjustments.
2Measurement precision
If multiple factors (battery architecture, state of charge, power source capability) are considered for charge time prediction, then prediction accuracy is improved, but system complexity deteriorates
Solution Approach 1:
The prediction system is segmented into distinct functional modules: a data acquisition module that collects parameters (battery capacity, state of charge, power source capability), a calculation module that computes charge time using these parameters, and an output module that provides predictions. This modular segmentation reduces overall system complexity while maintaining comprehensive analysis of multiple factors.
Solution Approach 2:
The controller performs multiple functions using the same hardware resources: it manages battery charging operations, monitors system parameters, calculates charge time predictions, and communicates with external systems. This multi-functionality reduces hardware complexity while enabling accurate predictions that consider multiple factors.
Data Source
AI summary
A charge transfer timing system and method include determining a charge capability of one or more power sources configured to supply charging power to multiple battery packs of a powered system. The system and method include calculating a time required to charge the battery packs to at least one of a target voltage or a target energy level. The time that is calculated may be 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 charge capability.