Vehicle Battery Health Assessment Using Telematics and Ohmic Testing
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Solution Overview
Problem
Automotive battery failures are common and difficult to accurately assess, making it challenging to determine the remaining life of vehicle batteries, which can lead to unexpected failures.
Innovation Solution
A system that uses a telematics device to collect data from sensors and ohmic testing devices, processing it to create a dataset that is then analyzed by an intelligence system to evaluate battery health and predict future performance, providing accurate assessments to drivers and dynamically improving prediction methodologies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional battery monitoring methods are used, then the system complexity is low, but the measurement precision of battery health is insufficient
Solution Approach 1:
The battery monitoring system is divided into multiple independent components: ohmic testing devices for electrical resistance measurement, temperature sensors for thermal monitoring, and a telematics device for data collection. Each component focuses on a specific parameter, and their results are integrated to provide comprehensive battery health assessment, resolving the contradiction between measurement precision and system complexity.
Solution Approach 2:
The telematics device serves multiple functions: collecting data from various sensors, processing the data, communicating with the intelligence system, and displaying results to the user. This multi-functional approach consolidates complexity into a single device while maintaining high measurement precision through integrated monitoring capabilities.
2Measurement precision
If comprehensive sensor data collection is implemented, then the measurement precision of battery performance is improved, but the loss of information increases due to data processing requirements
Solution Approach 1:
The system extracts only the necessary parameters from comprehensive sensor data collection. The telematics device selectively processes data from temperature sensors, ohmic testing devices, and other sensors to identify key indicators of battery health, such as internal resistance changes and temperature trends, while filtering out redundant information to reduce processing overhead.
Solution Approach 2:
The system performs preliminary data processing and feature extraction locally at the telematics device before transmitting data to the intelligence system. This preliminary action reduces the amount of information that needs to be processed remotely, minimizing data transmission requirements and processing overhead while maintaining measurement precision.
3Reliability
If real-time battery monitoring is implemented, then the reliability of battery operation is improved, but the use of energy by the monitoring system increases
Solution Approach 1:
The battery monitoring system implements periodic sampling of sensor data rather than continuous monitoring. The telematics device collects data at predetermined intervals, such as during vehicle operation or at scheduled times, which reduces energy consumption while maintaining sufficient reliability to detect battery degradation trends and potential failures.
Solution Approach 2:
The system uses the battery's own operational parameters (voltage, current, temperature) to monitor its health, minimizing the need for additional external power sources. The ohmic testing devices and sensors leverage the battery's natural operation to gather diagnostic information, reducing the energy burden on the monitoring system while maintaining reliable operation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This system provides drivers with accurate assessments of battery health and remaining life, enabling informed decisions and reducing unexpected failures by leveraging machine-learning techniques and self-learning algorithms.
Implementation Method 1
ohmic testing information related to the vehicle battery. The ohmic testing information may include an internal resistance of the vehicle battery
Data Source
AI summary
Techniques described herein may be used to provide a driver of a vehicle with an accurate assessment of the remaining life of the vehicle battery. An on-board device may collect information from one or more sensors or devices within the vehicle. The information may be processed to generate a data set that accurately describes the current status and operating conditions of the battery. The data set may be used to evaluate the health of the battery and make predictions regarding the future performance of the battery, which may be communicated to the driver of the vehicle. Machine-learning techniques may be implemented to improve upon methodologies to evaluate the health of the battery and make predictions regarding battery performance.