Dynamic Loading Battery Tester for CCA Precision
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Solution Overview
Problem
Conventional battery testers provide inaccurate testing results when detecting rechargeable batteries of different capacities due to a fixed resistance and loading duration in the 1/2 CCA testing method, which is not precise for all battery types.
Innovation Solution
A battery tester with a microprocessor that determines a loading time based on the battery's cold cranking amperes, voltage, and detection requirements, using a strategic decision process to adjust the loading time for accurate detection, allowing for precise health assessment of batteries with varying capacities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed resistance and loading duration are used in the 1/2 CCA testing method, then the testing process is simple and consistent, but the testing precision is insufficient for batteries with different capacities
Solution Approach 1:
The patent applies dynamics by transitioning from a fixed loading time to a dynamically adjusted loading time based on battery capacity. The microprocessor calculates the optimal loading time using the formula T_load = (1/N) × (60/CCA) × I_b, where the loading time adapts to each battery's specific characteristics. This dynamic adjustment resolves the contradiction by enabling precise testing across different battery capacities while maintaining operational simplicity through automated calculation.
Solution Approach 2:
The patent implements parameter changes by modifying the loading time parameter based on battery capacity and detection requirements. Instead of using a constant loading duration, the system varies the loading time parameter according to the specific battery being tested. This parameter adaptation allows the testing method to achieve high precision for batteries with different capacities while the microprocessor handles the complexity of parameter adjustment automatically.
2Measurement precision
If the loading time is extended to improve detection accuracy for large capacity batteries, then the testing precision improves, but the testing time increases
Solution Approach 1:
The patent uses parameter changes to optimize the loading time based on battery capacity. The formula T_load = (1/N) × (60/CCA) × I_b dynamically adjusts the loading time parameter to match each battery's specific requirements. For large capacity batteries, the loading time is automatically extended to ensure accurate detection, while for smaller batteries, the loading time is reduced accordingly. This parameter adaptation resolves the contradiction by achieving high detection accuracy without unnecessarily extending testing time for all battery types.
Solution Approach 2:
The patent applies partial or excessive action by providing a mechanism to load more than the standard 1/2 CCA when necessary for accurate detection of large capacity batteries. The system can adjust the loading current and duration to provide sufficient stimulus for accurate measurement without always applying the maximum possible load. This approach ensures detection accuracy is achieved only when needed, optimizing the balance between precision and testing time.
Data Source
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AI summary
The battery tester has a casing 10 having an input device 11 and two detecting wires 12, a microprocessor 20, a loading unit 21 and a battery power status detecting unit 22. The microprocessor 20 builds a strategic decision process therein to determine a loading time 21 for a battery 30 according to the battery capacity, battery voltage and detection requirements having 1/N CCA and a loading time input from the input device 11. Therefore, the battery tester detects batteries 30 with different capacities and has accurate detecting results.