Depot EV Charging Scheduling for Cost and SoC Priority
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Solution Overview
Problem
Existing technologies face challenges in efficiently managing the charging of electric vehicles (EVs) at depots, particularly in optimizing the total cost of travel for EVs on known routes, achieving peak shaving in charging as a service, and ensuring efficient use of directional and bi-directional wireless power transfer.
Innovation Solution
A system comprising at least one charger, a wireless communication system, and a depot controller that executes instructions to manage EV charging. The depot controller collects data on EVs' state of charge, goals, routes, and schedules, determines charging priorities, and optimizes charging start times and durations to minimize total electricity cost while ensuring EVs meet their state of charge goals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If charging is performed without optimization, then EVs can be charged, but the total cost of electricity is high and peak demand occurs
Solution Approach 1:
The system performs preliminary actions by collecting route estimates and state of charge data before charging begins, determining charging priorities and schedules in advance to optimize when charging occurs, thereby reducing total electricity cost and avoiding peak demand periods
Solution Approach 2:
The charging management system dynamically adjusts charging schedules based on real-time data including state of charge, route estimates, and electricity pricing, allowing the system to respond to changing conditions and optimize charging timing to reduce costs and manage peak demand
2Reliability
If charging duration is extended to meet state of charge goals, then EVs achieve required charge levels, but productivity is reduced due to longer depot停留 time
Solution Approach 1:
The system determines the minimum necessary charging duration in advance based on the state of charge goal and current battery level, allowing vehicles to be charged for exactly the time needed to meet their operational requirements, thereby minimizing depot停留 time while ensuring reliability
Solution Approach 2:
The system changes charging parameters dynamically, adjusting charging priority and duration based on individual vehicle state of charge goals, route estimates, and operational schedules, thereby optimizing the balance between achieving required charge levels and maintaining vehicle availability
3Productivity
If multiple EVs are charged simultaneously, then charging efficiency increases, but peak demand and electricity cost increase
Solution Approach 1:
The system implements periodic charging schedules by distributing charging sessions across different time periods, charging multiple EVs at different times rather than simultaneously, thereby maintaining high charging throughput while avoiding peak demand periods and reducing electricity costs
Solution Approach 2:
The charging management system dynamically schedules charging sessions based on real-time conditions, adjusting when each vehicle is charged to balance the load on the charging infrastructure, thereby achieving high productivity while managing peak demand and reducing overall electricity costs
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 reduces the total cost of travel for EVs by optimizing charging operations, achieving peak shaving in electricity usage, and efficiently utilizing wireless power transfer capabilities, thereby enhancing the operational efficiency and cost-effectiveness of EV charging at depots.
Implementation Method 1
a wireless communication system for communicating with EVs
Implementation Method 2
WPT acts as an open core transformer with a primary (ground-side) coil and a secondary (vehicle-side) coil to transfer power over an air-gap in accordance to Faraday's first law of electromagnetic induction
Data Source
AI summary
A system and method that manages charging of Electric Vehicles (EVs) at a depot equipped with EV chargers. For each EV arriving at the depot, data is collected from the EV including a current state of charge (SoC), an SoC goal, a route estimate, and a charging schedule. A depot controller determines from the collected data a charging priority for the EV relative to other EVs at the depot. When charging is required to meet the SoC goal of the EV, a charger is selected for charging the EV and a charging start time and charging duration is determined by an optimization algorithm that concurrently optimizes a minimal total cost of electricity for total power transferred to the EV during charging while maximizing a probability of the EV leaving the depot with its SoC goal satisfied.