Vehicle Battery Diagnosis Apparatus for Voltage Deviation Prediction
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Solution Overview
Problem
High-voltage batteries in electric vehicles experience voltage deviations due to self-discharge rates and differences in cell characteristics, leading to potential system failures that are difficult to predict and prevent with existing balancing circuits.
Innovation Solution
A vehicle battery diagnosis apparatus that calculates self-discharge rates based on cell voltage and parking time, and cell balancing capacitance based on vehicle usage time, enabling advanced prevention diagnosis and safe maintenance by comparing these values to determine if cell balancing is necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cell balancing is performed continuously, then voltage deviation is prevented, but energy is wasted and battery life is reduced
Solution Approach 1:
Instead of continuous balancing, the system performs partial balancing actions only when necessary. By calculating self-discharge rates and comparing with balancing capacitance, the system determines the minimum required balancing intervention, performing only the necessary portion of balancing to maintain voltage uniformity without excessive energy consumption.
Solution Approach 2:
The diagnosis apparatus performs periodic voltage deviation predictions and recommends balancing actions at optimal intervals rather than continuous balancing. This periodic approach allows the system to maintain voltage uniformity while minimizing energy waste by performing balancing only when the predicted voltage deviation exceeds acceptable thresholds.
2Measurement precision
If battery diagnosis is performed late after voltage deviation affects the system, then system failures are detected, but vehicle operation is already compromised
Solution Approach 1:
The system performs preliminary diagnosis by calculating self-discharge rates and comparing them with balancing capacitance to predict future voltage deviation issues before they affect system operation. This advance detection provides early warning, allowing maintenance to be scheduled before vehicle operation is compromised.
Solution Approach 2:
The system replaces traditional reactive mechanical diagnosis with a predictive computational approach. By using mathematical models to calculate self-discharge rates and predict voltage deviation, the system substitutes physical trial-and-error diagnosis with precise computational prediction, enabling earlier and more accurate detection of potential issues.
Data Source
AI summary
A vehicle battery diagnosis apparatus includes: a measurement unit configured to measure a battery cell voltage; and a controller configured to diagnose a cell voltage deviation based on the battery cell voltage. The controller calculates a self-discharge rate for each cell based on the battery cell voltage and a parking time and calculates the cell voltage deviation based on the battery cell voltage, and when the calculated cell voltage deviation is greater than a preset cell balancing reference voltage deviation, the controller compares cell balancing capacitance calculated based on a vehicle usage time with a maximum self-discharge rate among the calculated self-discharge rates for respective cells and determines whether cell balancing is enabled or diagnoses the cell voltage deviation.