EV Charger Placement Using Battery and Route Simulation
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Solution Overview
Problem
Existing methods for electric vehicle charger deployment fail to accurately account for dynamic battery range and environmental conditions, leading to inefficient charger placement and potential underutilization or overutilization of chargers.
Innovation Solution
A high-fidelity agent-based simulation framework that utilizes high-performance computing to simulate thousands of electric vehicles under various conditions, incorporating vehicle and battery dynamics, environmental factors, and route simulations to optimize charger placement based on real-time demand and location-specific data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a grid-based approach is used to place chargers at constant distances, then charger deployment coverage is improved, but infrastructure cost increases significantly
Solution Approach 1:
The patent applies dynamics by transitioning from static grid-based charger placement to dynamic agent-based simulation that adapts to varying environmental conditions, vehicle routes, and battery performance characteristics. The system dynamically determines optimal charger locations based on simulated vehicle behavior under different weather, elevation, and traffic conditions, rather than deploying chargers uniformly across the entire service area.
Solution Approach 2:
The patent changes key parameters from fixed grid coordinates to variable locations determined by simulated vehicle demand. The simulation varies parameters such as battery temperature, state of charge, vehicle speed, and environmental conditions to determine where chargers are actually needed, allowing optimal placement that responds to changing operational parameters rather than static geographic grids.
2Device complexity
If the battery is treated as a black box with single range assumption, then model complexity is reduced, but charger placement accuracy deteriorates
Solution Approach 1:
The patent segments the battery system from the vehicle model, treating battery dynamics as a separate, detailed subsystem with its own state variables (temperature, state of charge, degradation). This allows the battery to be modeled with high fidelity while keeping the overall simulation manageable through modular architecture where battery models can be independently developed and tested.
Solution Approach 2:
The patent introduces battery state variables as intermediary parameters that mediate between vehicle operation and charger placement decisions. Rather than directly using simplified range estimates, the simulation uses detailed battery state tracking (temperature, charge level, degradation state) to accurately determine when and where vehicles will need charging, improving placement precision without overwhelming model complexity.
3Productivity
If environmental conditions are not incorporated into the model, then computational requirements are reduced, but charger deployment optimization deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-processing environmental data (weather patterns, elevation profiles, traffic conditions) and pre-defining simulation scenarios before running the agent-based model. This allows the system to account for environmental variability without performing real-time calculations during simulation, maintaining computational efficiency while incorporating comprehensive environmental factors into charger placement decisions.
Data Source
AI summary
A method for the efficient management of a fleet of electric vehicles in a target area couples vehicle dynamics and battery dynamics modeling with environmental factors to accurately incorporate the impact that the environment has on the range of the battery into the placement of the chargers by simulating trips of fleets of electric vehicles. The vehicles can be of various types, for example, motorcycles, cars, trucks or aircraft, and will each have their battery state of charge monitored as they traverse a simulated trip through the target area.