EV Battery Aging Tracking for Truck Replacement Planning
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Solution Overview
Problem
Electrically drivable trucks experience faster battery aging due to different usage modes and charging behaviors compared to passenger vehicles, leading to premature battery degradation and increased costs for replacement, which existing methods do not adequately address for efficient planning and management.
Innovation Solution
A method for monitoring and tracking electrochemical energy stores in electric vehicles, involving the ascertainment of energy store characteristic variables, creation of usage certificates, and provision of recommended courses of action to determine the optimal timing for battery replacement or maintenance, utilizing a data-based aging model and probabilistic models like Gaussian processes to predict the remaining useful life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If electrically drivable trucks are used with frequent rapid charging processes, then productivity and utilization of the vehicle is improved, but the battery ages much faster and reliability deteriorates
Solution Approach 1:
The system performs preliminary assessment of battery aging state and predicts future replacement needs before actual failure occurs. By analyzing historical charging data and calculating aging metrics in advance, the system enables proactive planning for battery replacement, allowing operators to schedule maintenance during planned downtime rather than experiencing unexpected failures.
Solution Approach 2:
The system continuously monitors battery parameters and provides feedback on aging state to operators. This feedback loop allows dynamic adjustment of charging strategies and maintenance scheduling based on actual battery condition, balancing productivity requirements with battery longevity through informed decision-making.
2Ease of operation
If battery replacement is performed without advance planning, then ease of operation is maintained, but loss of time and productivity occur due to unavailability of replacement components
Solution Approach 1:
The system calculates and communicates recommended courses of action in advance, allowing repair shops to prepare replacement batteries before they are needed. This advance planning ensures that when battery replacement becomes necessary, the replacement component is already available, eliminating waiting time and keeping the vehicle in service longer.
Solution Approach 2:
The system automatically tracks battery aging and generates replacement recommendations without requiring manual intervention. This self-monitoring capability ensures that replacement timing is optimized based on actual usage patterns, preventing both premature replacement and operation beyond safe limits.
3Ease of repair
If expensive battery components are kept in stock for quick replacement, then ease of repair is improved, but loss of substance and increased costs occur due to warehouse storage and component aging
Solution Approach 1:
The system extracts only the essential information needed for replacement planning - specifically, the recommended course of action and timing - and communicates this to repair shops in advance. This allows repair shops to order replacement batteries just-in-time based on actual need rather than maintaining large inventories, reducing storage costs while ensuring availability when required.
Data Source
AI summary
A computer-implemented method for monitoring and tracking an electrochemical energy store of an electrically drivable vehicle.