Battery Controller State-of-Charge Estimation for Variable Power Loads
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Solution Overview
Problem
Conventional battery controllers inaccurately estimate the state-of-charge of battery packs due to variations in power requirements among different devices, such as cordless drills and LED spotlights, as they do not account for unique power demands of each device.
Innovation Solution
A battery controller that obtains data indicative of the power requirement for the connected device, including electrical parameters and model numbers, to adjust the state-of-charge of the battery cells accordingly, using a processing circuit and memory devices to execute a state-of-charge algorithm and provide notifications for display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a universal battery pack is used to power multiple types of tools with different power requirements, then the battery pack's versatility is improved, but the accuracy of state-of-charge estimation deteriorates
Solution Approach 1:
The battery controller dynamically adjusts the state-of-charge estimation based on the detected tool type and its specific power requirements. The system transitions from a static estimation approach to a dynamic one that adapts to different load conditions, thereby maintaining accuracy across multiple tool applications while preserving versatility.
Solution Approach 2:
The system changes the estimation parameters (such as discharge rate, capacity factors, and voltage thresholds) based on the detected tool type. By modifying these parameters according to the specific power requirements of each tool, the system maintains accurate state-of-charge estimation while supporting a universal battery pack design that works with multiple tool types.
2Device complexity
If the battery controller uses a fixed state-of-charge algorithm, then the device complexity is reduced, but the measurement precision of state-of-charge estimation deteriorates
Solution Approach 1:
The battery controller automatically detects the tool type and selects the appropriate estimation parameters without requiring manual intervention or complex user configuration. This self-service approach allows the system to maintain high estimation accuracy through adaptive algorithms while keeping the user interface simple and the overall device complexity manageable.
Solution Approach 2:
The system incorporates feedback mechanisms where the battery controller continuously monitors current draw, voltage, and tool operation characteristics to refine state-of-charge estimates. This feedback loop enables the controller to adapt to actual usage conditions, improving measurement precision while using relatively simple computational algorithms that do not excessively increase device complexity.
Data Source
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AI summary
A method of estimating a state-of-charge of a battery pack having one or more cells is provided. The method includes obtaining, by a battery controller of the battery pack, data from a device electrically coupled to the battery pack. The data is indicative of a power requirement for the device. The method can further include determining, by the battery controller, a state-of-charge of the battery pack based, at least in part, on the data indicative of the power requirement for the device.