EV Charging Scheme for Limited Battery and Grid Availability
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Solution Overview
Problem
Charging systems for electric and hybrid vehicles are limited by battery storage capacity and external power source availability, leading to inadequate charging when the power grid is unavailable or costly, and environmental factors affect charging efficiency, frustrating both providers and customers.
Innovation Solution
A vehicle charging system with a charging optimization engine that generates an optimized charging scheme based on electrical, environmental, and scheduling data, using machine learning to maximize the number of vehicles charged by balancing battery and grid power usage and adjusting charging rates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the charging system uses battery storage to charge vehicles, then charging can be provided when the power grid is unavailable, but the battery capacity is limited and may be depleted before all reserved vehicles can be charged
Solution Approach 1:
The charging system dynamically adjusts charging rates and vehicle selection based on real-time battery state of charge, grid availability, and reservation priorities. The system transitions between different charging modes (fast charge, standard charge, standby) to optimize the use of limited battery capacity while ensuring all reserved vehicles receive appropriate charging service.
2Productivity
If the charging system charges vehicles at high rates to serve more vehicles quickly, then the number of vehicles charged increases, but the battery depletes faster reducing overall charging availability
Solution Approach 1:
The system implements periodic charging cycles that alternate between high-rate charging when battery capacity is sufficient and lower-rate charging when battery levels are declining. This allows the system to maximize vehicle throughput during periods of adequate capacity while extending operational duration during periods of limited capacity, effectively serving more vehicles over the complete cycle.
3Ease of operation
If the charging system prioritizes fast charging to improve customer satisfaction, then charging speed increases, but energy consumption increases and may exacerbate grid availability issues
Solution Approach 1:
The system changes charging parameters (current rate, voltage, charging mode) based on real-time conditions including battery state of charge, grid availability, vehicle requirements, and reservation priorities. This allows the system to provide fast charging when appropriate to maintain customer satisfaction while reducing energy consumption and grid dependency when conditions warrant conservation.
4Productivity
If the charging system monitors and optimizes charging based on multiple factors including environmental conditions, then charging efficiency improves, but system complexity increases
Solution Approach 1:
The charging system automatically monitors multiple parameters (battery state of charge, environmental conditions, vehicle requirements, reservation data) and autonomously makes optimization decisions without requiring complex external control systems. The system self-adjusts charging parameters based on sensor inputs and pre-programmed optimization algorithms, reducing the need for additional complex control infrastructure while maintaining high charging efficiency.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system effectively optimizes charging to serve a maximum number of vehicles by efficiently utilizing battery and grid power, ensuring timely charging even during power outages or peak demand, enhancing customer satisfaction and reducing operational costs.
Implementation Method 1
a battery configured to receive and store electric power derived from the input electric power received at the power input port
Data Source
AI summary
A charging system comprises a local energy storage disposed at a charging site; an electric coupling configured to provide an electrical interconnect between the charging site and an electric vehicle (EV); and one or more controllers configured to: (i) detect a condition related to availability of electrical energy at the charging station, (ii) in response to the detecting of the condition: (a) estimate a number of EVs to which a charge remaining at the local energy storage is to be distributed within a certain time interval, (b) initiate a charging session for transferring electric energy from the local energy storage to the EV, via the electric coupling, and (c) limit an amount of electrical energy in the charging session in view of at least the estimated number of EVs.