Dynamic SOC Assignment for EV Fleet Battery Life
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Solution Overview
Problem
Electric vehicle fleets face accelerated battery degradation and increased operational costs due to the practice of loaning out vehicles with fully charged batteries, leading to prolonged downtimes and premature battery replacement.
Innovation Solution
A method and computer program that assign electric vehicles to users based on their specific energy requirements, determining a target state of charge for each vehicle to avoid high charge levels, allowing for more efficient charging and reduced downtime, thereby extending battery life and optimizing fleet utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If electric vehicles are loaned out only when fully charged (100% SOC), then users receive vehicles with sufficient energy, but batteries experience accelerated degradation and longer charging times
Solution Approach 1:
The patent changes the state of charge parameter from fixed (100% SOC) to dynamic (target SOC between 20-80%). The control unit determines optimal target SOC values based on usage requirements, avoiding the harmful extremes of fully charged or fully depleted states. This parameter change resolves the contradiction by enabling vehicle assignment with moderate charge levels (extending battery life) while ensuring sufficient energy for user needs (maintaining fleet utilization).
Solution Approach 2:
Instead of requiring full charging (excessive action), the system applies partial charging to reach target SOC levels sufficient for user requirements. The control unit calculates minimum necessary charge based on trip distance and energy consumption, assigning vehicles at partial charge states (e.g., 60-80% SOC) rather than waiting for 100% charge. This reduces charging time and battery stress while maintaining adequate energy supply.
2Use of energy by moving object
If electric vehicles are charged to maximum state of charge before assignment, then users have adequate energy availability, but charging time increases and battery protection mechanisms are activated
Solution Approach 1:
The system applies partial charging to reach target SOC levels (20-80%) sufficient for user requirements rather than charging to maximum. The control unit calculates minimum necessary charge based on trip distance and energy consumption, reducing charging time while maintaining adequate energy supply for the planned journey.
Solution Approach 2:
The control unit performs preliminary calculation of energy requirements based on user input (trip distance, route, vehicle characteristics) before charging begins. This allows the system to charge only to the necessary target SOC level in advance, avoiding unnecessary charging time while ensuring sufficient energy availability for the user's planned trip.
3Ease of operation
If electric vehicles are assigned with high state of charge to ensure user needs, then user satisfaction increases, but fleet operational costs increase due to premature battery replacement
Solution Approach 1:
The patent changes the SOC parameter from high fixed values (90-100%) to dynamic target values (20-80%) based on usage requirements. This parameter change reduces battery degradation and extends service life (preserving fleet value) while still providing sufficient energy for user needs (maintaining satisfaction). The control unit continuously adjusts target SOC based on trip requirements, avoiding unnecessary high charge states.
Solution Approach 2:
The control unit autonomously determines optimal target SOC levels and manages charging without requiring user intervention or manual monitoring. The system self-calculates energy requirements based on trip data and automatically assigns vehicles at appropriate charge levels, ensuring user needs are met while optimizing battery health and fleet value preservation.
4Adaptability or versatility
If electric vehicles are kept in stock with high charge levels for availability, then user choice increases, but battery aging accelerates during storage
Solution Approach 1:
The system changes the storage SOC parameter from high fixed levels (90-100%) to dynamic target levels (20-80%) based on anticipated usage. The control unit adjusts target SOC for stored vehicles based on predicted demand and trip requirements, avoiding prolonged storage at high charge states that accelerate aging while maintaining vehicle availability for assignment.
Solution Approach 2:
The system dynamically adjusts target SOC levels for vehicles in stock based on real-time demand patterns, trip requirements, and battery health considerations. Rather than maintaining static high charge levels for all stored vehicles, the control unit continuously optimizes charge states, assigning vehicles at appropriate charge levels and managing recharge cycles to extend battery service life while preserving fleet availability.
Data Source
AI summary
A method for assigning an electric vehicle (20, 22, 24) to a user includes: receiving a request from the user via a receiving device stating that the user needs an electric vehicle (20, 22, 24), the request including usage information regarding the planned use of the electric vehicle (20, 22, 24); determining a target state of charge of a battery (22) of at least one available electric vehicle (20, 22, 24) depending on the usage information; determining an actual state of charge of the battery (22) of the electric vehicle (20, 22, 24); and assigning the electric vehicle (20, 22, 24) to the user when the determined actual state of charge is greater than or equal to the determined target state of charge.