Battery Deterioration Prediction via Environmental Data Collection
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Solution Overview
Problem
Reusable batteries, which are not suitable for vehicles due to reduced chargeable capacity, face challenges in accurately predicting their deterioration due to varied usage environments, making effective maintenance and management difficult.
Innovation Solution
An information providing system that connects information collection devices with a server via a network, utilizing monitoring circuits and sensors to collect and transmit data on battery states and environmental conditions, allowing for the construction of accurate deterioration models and power demand models, which are then provided to users for informed management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a deterioration model for new secondary batteries is applied to reusable batteries, then the model construction is simple, but the prediction accuracy is insufficient due to varied usage environments
Solution Approach 1:
The system performs preliminary data collection from multiple information collection devices deployed in various usage environments before constructing the deterioration model. This advance gathering of environmental and operational data enables the model to account for real-world variations, improving prediction accuracy without requiring complex adjustments during the modeling phase itself
Solution Approach 2:
The deterioration model is designed to be universal across different usage environments by incorporating data from multiple information collection devices that operate in diverse conditions. The model uses common parameters (SOC, temperature, usage patterns) that can be standardized across applications while capturing environment-specific variations, allowing one model to serve multiple purposes and environments
2Adaptability or versatility
If reusable batteries are used in various different environments and use conditions, then the adaptability and application range increase, but the ability to accurately predict deterioration decreases
Solution Approach 1:
The system segments the usage environment into multiple information collection devices deployed in different locations and conditions. Each device collects local environmental data and battery performance metrics, allowing the overall system to handle diverse environments while maintaining prediction accuracy through localized measurements that are then aggregated for comprehensive analysis
Solution Approach 2:
The system implements feedback mechanisms where actual battery performance data and environmental conditions from various usage scenarios are continuously collected and fed back into the deterioration model. This feedback loop allows the model to learn from real-world variations in different environments and adjust predictions accordingly, maintaining accuracy despite environmental diversity
Data Source
AI summary
An information providing system in which a plurality of information collection devices, a server, and a plurality of information reception devices are connected by a network, each of the plurality of information collection devices comprises: a rechargeable battery configured to supply power to drive the information collection device; a monitoring circuit configured to monitor a state of the battery; a sensor configured to detect a state of an environment where the plurality of information collection devices are installed; a memory configured to store first data indicating a history of the state of the battery monitored by the monitoring circuit and second data indicating a state of the environment detected by the sensor; and a transmission unit configured to transmit the first data and the second data stored in the memory via the network based on a request from the server.