Battery Charging Interface With Predictive Aging Profiles
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Solution Overview
Problem
Users of battery-operated devices, such as electric vehicles, lack transparency and control over the influence of charging strategies on battery aging, leading to non-transparent degradation and reduced service life due to varying usage behaviors and ambient conditions.
Innovation Solution
A user interface that detects historical usage patterns, predicts future usage, and simulates different charging strategies to inform users about their impact on battery aging, allowing them to select strategies that optimize between battery life and charging speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If rapid charging strategy is applied to reduce charging time, then productivity is improved, but device battery aging accelerates and reliability deteriorates
Solution Approach 1:
The system dynamically adjusts charging parameters based on real-time battery state monitoring and historical usage pattern analysis. The charging strategy is not fixed but adapts continuously to current battery conditions, state of charge, temperature, and predicted future usage, resolving the contradiction between charging speed and battery aging by optimizing the charging curve dynamically rather than using a static rapid charging mode
Solution Approach 2:
The system performs preliminary analysis of historical usage patterns and predicts future usage scenarios before executing the charging process. By pre-calculating the optimal charging strategy based on predicted battery discharge patterns and user behavior, the system can plan charging curves that minimize aging while still meeting future energy demands, thus resolving the contradiction before the charging actually occurs
2Reliability
If gentle charging strategy is applied to extend battery service life, then reliability is improved, but productivity deteriorates due to longer charging time
Solution Approach 1:
The system dynamically adjusts charging parameters based on real-time battery state monitoring and historical usage pattern analysis. The charging strategy is not fixed but adapts continuously to current battery conditions, state of charge, temperature, and predicted future usage, resolving the contradiction between charging speed and battery aging by optimizing the charging curve dynamically rather than using a static rapid charging mode
Solution Approach 2:
The system changes charging parameters (current, voltage, temperature thresholds) based on battery state and predicted usage patterns. By adjusting these parameters dynamically according to the battery's current condition and forecasted discharge behavior, the system optimizes the balance between charging speed and aging prevention, neither consistently using gentle nor rapid charging but adapting parameters to achieve both goals
3Ease of operation
If multiple charging strategies are provided with detailed aging information, then user control and transparency are improved, but device complexity increases
Solution Approach 1:
The system creates simplified representations (copies) of complex battery aging data and charging strategy options for user display. Instead of showing raw technical parameters and complex aging models, the system generates user-friendly visualizations and summaries that convey essential information about charging options and their impact on battery life, thus providing user control without exposing the underlying complexity
Solution Approach 2:
The system introduces an intermediary layer between the complex battery management system and the user. This intermediary processes complex aging data, charging strategy calculations, and usage pattern analyses, then presents simplified information and recommendations to the user. The intermediary translates technical complexity into actionable user-friendly options, enabling ease of operation while hiding device complexity
Data Source
AI summary
A computer-implemented method for operating a user interface for specifying a charging strategy for charging a device battery of a battery-operated device includes detecting a historical usage pattern of an operation of the device battery, and specifying a plurality of different charging strategies. Each charging strategy having a corresponding charging curve for charging of the device battery. The method further includes determining an aging indication for each of the charging strategies based on (i) the historical usage pattern, and (ii) an assumption that all future charging processes for charging the device battery are performed using a relevant charging strategy of the plurality of different charging strategies. The method also includes informing a user about a relevant characteristic variable for each of the charging strategies and the respectively associated aging indication, and specifying one of the charging strategies for future charging processes corresponding to a received user selection.