Battery Device Selection Using Usage-Based Ageing Prediction
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Solution Overview
Problem
Existing methods for determining the ageing state of battery-powered devices, such as vehicle batteries, are inaccurate and costly, lacking direct measurement capabilities and resulting in varying residual values at the end of their useful life, which complicates leasing and maintenance processes due to differing usage behaviors among users.
Innovation Solution
A method that associates a user with a specific battery-powered device by predicting the ageing state based on usage behavior, simulating usage parameter profiles, and selecting devices to minimize battery degradation, using a hybrid ageing state model combining physical and data-based approaches to estimate the remaining service life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If direct measurement of ageing state using sensors is implemented, then measurement precision is improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The patent introduces an intermediary system consisting of a usage behavior analysis unit and ageing simulation unit that mediates between operational data and ageing state determination. Instead of directly measuring ageing with sensors, the system uses operational parameter profiles and usage behavior patterns as intermediaries to predict ageing state through simulation, thereby avoiding complex sensor integration while maintaining measurement precision.
Solution Approach 2:
The patent replaces the mechanical/sensor-based direct measurement system with a data-processing-based prediction system. By substituting physical sensors with computational models that analyze operational parameters and simulate ageing processes, the system achieves accurate ageing state determination without the complexity and cost of direct measurement hardware.
2Measurement precision
If high sampling rates are used for operational parameter data, then measurement precision is improved, but loss of energy increases
Solution Approach 1:
The patent applies partial action by transmitting operational parameter profiles at optimized intervals rather than continuous high-rate transmission. The system determines appropriate sampling and transmission rates based on the specific operational context and device type, transmitting only necessary data at necessary times, thereby reducing energy consumption while maintaining sufficient precision for accurate ageing determination.
Solution Approach 2:
The patent implements periodic transmission of operational parameter profiles instead of continuous transmission. By establishing regular transmission intervals adapted to the operational characteristics and device type, the system maintains adequate data quality for ageing prediction while significantly reducing the energy burden of constant data communication.
3Adaptability or versatility
If usage behavior is not categorized, then adaptability is improved, but measurement precision of ageing state deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-defining usage categories and associated usage parameter profiles before actual device assignment. The system prepares multiple device types with their specific usage profiles in advance, allowing for precise matching between user behavior patterns and appropriate devices. This preliminary categorization enables both adaptability in device selection and precision in ageing prediction by selecting the most relevant device profile.
Solution Approach 2:
The patent implements local quality by assigning different usage parameter profiles and ageing characteristics to different device types based on their specific operational requirements. Instead of using a single generic model, the system tailors the usage behavior categories and prediction parameters to match the local characteristics of each device type, thereby achieving both versatility across devices and precision for each specific device.
Data Source
AI summary
A computer-implemented method, for associating a user with a device type of a battery powered technical device having a device battery and belonging to a plurality of various device types. In one example, the method includes providing a usage behavior of the user; associating a usage category with the user's usage behavior; determining a predicted usage parameter profile of at least one usage parameter according to the usage category, wherein the at least one usage parameter is indicative of a mode of operation of the technical device affecting a load on the device battery; simulating a predicted ageing state profile for the predicted usage parameter profile for a predetermined duration for each type of device belonging to a plurality of device types to determine a predicted ageing state at a predetermined end of a useful life period; and selecting a device type depending on the predicted ageing state.