EV Charger Placement Using Battery and Environmental Dynamics
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing methods for electric vehicle charger placement fail to accurately account for dynamic battery ranges influenced by environmental conditions, leading to inefficient charger deployment and potential under or over-provisioning.
Innovation Solution
A high-fidelity agent-based simulation framework that utilizes high-performance computing to simulate thousands of electric vehicles under various conditions, coupling vehicle and battery dynamics to optimize charger placement by accurately incorporating environmental factors like wind, elevation, and temperature.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a grid-based approach is used to place chargers at constant distances, then charger demand coverage is improved, but infrastructure cost increases significantly
Solution Approach 1:
The patent applies dynamics by transitioning from static, uniform charger placement to dynamic placement that adapts to varying environmental conditions. The system simulates vehicle trips under different weather, traffic, and route conditions to determine where chargers are actually needed, placing them dynamically based on simulated demand rather than uniform spacing.
Solution Approach 2:
The patent changes key parameters including environmental conditions (temperature, wind, elevation), vehicle characteristics, and trip patterns to simulate realistic operating scenarios. By varying these parameters in simulations, the system identifies optimal charger locations that account for how environmental factors affect battery range and vehicle performance.
2Device complexity
If the battery is treated as a black box with a single range value, then model complexity is reduced, but charger placement accuracy deteriorates
Solution Approach 1:
The patent transforms the static black box battery model into a dynamic system that responds to environmental conditions. By coupling vehicle dynamics with battery dynamics, the system simulates how temperature, wind, elevation, and other factors affect battery performance and range in real-time during simulated trips, providing accurate, condition-specific range estimates.
Solution Approach 2:
The patent replaces the simplified black box battery model with a physics-based coupled dynamics model that incorporates thermal, electrical, and mechanical interactions. This substitution uses fundamental physical principles to simulate battery behavior under varying conditions, improving accuracy without requiring proprietary black box data.
3Measurement precision
If environmental conditions are incorporated into battery modeling, then range estimation accuracy is improved, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by performing extensive computational simulations beforehand to pre-determine optimal charger locations. The system runs thousands of simulated vehicle trips under various environmental conditions to build a comprehensive understanding of charger demand patterns, allowing for accurate placement decisions without real-time computational burden during actual operation.
Solution Approach 2:
The patent uses copying by creating virtual replicas of vehicles, batteries, and environmental conditions in a simulation environment. Instead of directly computing complex battery dynamics for every real-time scenario, the system copies and simulates numerous representative trips to generate statistical data on charger utilization and demand, which then informs optimal placement without requiring ongoing complex calculations.
Data Source
AI summary
A method for the efficient placement of electric vehicle chargers 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.