Powertrain Battery Life Prediction Using Multi-Source Data Analysis
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Solution Overview
Problem
Current methods for predicting and warning about the remaining life of batteries in powertrains are inaccurate due to the complexity of factors influencing battery deterioration, such as vehicle characteristics, environment, and usage patterns, leading to inadequate awareness of battery condition and potential for vehicle inoperability during long-distance drives.
Innovation Solution
A data processing unit that collects and processes battery environment, power consumption, and vehicle running data to estimate battery deterioration, providing a precise prediction of remaining life and timely warnings through a controller and display system, accounting for various influencing factors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional battery life prediction methods are used, then the system is simple, but the prediction accuracy is low due to inability to account for multiple deterioration factors
Solution Approach 1:
The patent segments the battery deterioration prediction into multiple independent modules: a data acquisition module that collects various deterioration factors (temperature, charge/discharge cycles, voltage, current), a data processing module that analyzes each factor separately, and a prediction module that integrates the results. This segmentation allows accurate measurement of each factor while managing system complexity through modular architecture.
Solution Approach 2:
The control device performs multiple functions: it monitors battery parameters, processes deterioration data, predicts remaining life, and provides warnings. By integrating these functions into a single multi-functional system, the patent achieves comprehensive prediction accuracy without proportionally increasing complexity.
2Reliability
If comprehensive battery monitoring is implemented to account for all deterioration factors, then prediction accuracy improves, but the device complexity increases
Solution Approach 1:
The system continuously monitors battery parameters and feeds this information back to the control device, which updates the deterioration prediction in real-time. This feedback mechanism ensures reliable battery condition awareness by constantly adjusting predictions based on actual measured data, while the automated feedback loop manages complexity through established control protocols.
Solution Approach 2:
The control device automatically collects, processes, and analyzes battery deterioration data without requiring external intervention. The system self-manages the monitoring process by integrating data acquisition, analysis, and prediction functions, thereby improving reliability while containing complexity through automation.
3Loss of time
If real-time battery deterioration tracking is performed, then the warning timeliness improves, but the computational requirements and system complexity increase
Solution Approach 1:
The system performs preliminary data processing and deterioration analysis continuously in the background, preparing prediction results before they are needed. This preliminary action ensures that when a warning is required, the system can provide timely alerts without experiencing computational delays, while the ongoing background processing manages complexity through distributed computation.
Data Source
AI summary
A battery life predicting apparatus comprises a data processing unit for obtaining and processing data on a vehicle having a battery used as a power source of the vehicle, the data including battery environment data, power consumption data concerning electrical components, and vehicle running data, a recording unit for recording vehicle characteristic data and histories of the data obtained and processed, a storage for storing data concerning battery deterioration obtained in a vehicle running test, and a controller for estimating a degree of battery deterioration relative to durable years of the battery from the data recorded in the recording unit and calculating remaining life of the battery, and presents the remaining life of the battery to a driver in the display. Further, a battery life warning apparatus estimates a timing of replacing the battery and presents a level of warning to the driver.