Removable Battery Runtime Calculation for Materials Handling Vehicles
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Solution Overview
Problem
The reliance on state-of-charge (SOC) measurements alone is insufficient for accurately determining the useful residual charge of a battery in materials handling vehicles, as it does not account for the decline in state-of-health (SOH) and varying energy capacities of batteries.
Innovation Solution
Implementing a forward-looking remaining runtime calculation based on learning algorithms that use Exponentially Weighted Moving Average (EWMA) signal filters to account for the unique characteristics of individual batteries, providing a more predictable and accurate assessment of battery capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If state-of-charge (SOC) measurements alone are used to determine battery status, then the system is simple and easy to operate, but the measurement precision of useful residual charge is insufficient
Solution Approach 1:
The patent transforms the single SOC parameter into multiple parameters including SOC, SOH (state of health), and runtime calculations. The system uses EWMA (Exponentially Weighted Moving Average) filters to process current and voltage data, generating a runtime parameter that predicts remaining operational time. This multi-parameter approach significantly improves measurement precision of useful residual charge while accounting for battery aging and capacity variations.
2Reliability
If conventional SOC-based runtime calculation is used, then the system is simple, but the reliability of runtime prediction deteriorates due to abrupt drop-offs and inaccuracies
Solution Approach 1:
The system implements continuous feedback loops where EWMA filters process real-time current and voltage measurements, comparing actual battery performance against predicted runtime. The algorithm continuously updates runtime predictions based on changing battery conditions, smooths out anomalies, and provides progressive warnings to operators. This feedback mechanism significantly improves runtime prediction reliability by eliminating abrupt drop-offs and providing accurate, progressive runtime estimates.
3Adaptability or versatility
If batteries of different charge capacities are used in the same vehicle fleet, then the adaptability of the battery system is improved, but the loss of information occurs because SOC indication alone becomes less useful
Solution Approach 1:
The patent creates a universal battery management system that functions across batteries of different capacities, ages, and types. The EWMA-based runtime calculation algorithm adapts to each battery's unique characteristics by learning from its performance patterns. The system provides standardized runtime predictions and operational guidance that work universally across the entire battery fleet, regardless of individual battery specifications, thereby preventing loss of useful residual charge information.
Data Source
AI summary
Battery management systems, removable battery assemblies with integrated battery management systems, and vehicles are provided for implementing the various runtime calculations disclosed herein. A vehicle, which may be a materials handling vehicle, is provided comprising a drive subsystem, a removable battery assembly, and vehicle control hardware. The battery assembly comprises a battery management system programmed to input or generate a state of charge signal representing a state of charge SOC of the battery assembly, implement a first EWMA signal filter F1 to calculate a succession of contemporary current calculations IC, implement a second EWMA signal filter F2 to calculate a runtime current IR, wherein the runtime current calculation IR comprises the contemporary current calculations IC from the first EWMA signal filter F1, and implement a remaining runtime calculation such that the vehicle control hardware responds functionally to the runtime calculation.