EV Charging Authority Control for Cost-Aware Recharge Timing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing electric vehicle charging systems lack the ability to selectively commence re-charging sessions based on various dynamic factors, such as cargo weight, destination, travel distance, time of travel, and electricity pricing, which can lead to inefficiencies and increased costs.
Innovation Solution
A system and method that utilize an assigning authority engine connected to the vehicle through a mobile network to determine optimal charging times and conditions based on real-time data and predictive analytics, ensuring cost-effectiveness and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If electric vehicles charge whenever connected to a charging station, then the vehicle maintains operational readiness, but charging costs increase and energy usage becomes inefficient
Solution Approach 1:
The assigning authority engine performs preliminary analysis of multiple factors including cargo weight, destination, travel distance, time of travel, and electricity pricing before determining when to charge. This advance planning allows the system to schedule charging during optimal times (e.g., off-peak hours with lower electricity rates) rather than charging immediately upon connection, thereby reducing costs while ensuring the vehicle is ready when needed
Solution Approach 2:
The system continuously monitors and evaluates real-time data about vehicle assignments, battery charge levels, and electricity pricing conditions. This feedback mechanism allows the assigning authority engine to dynamically adjust charging decisions based on current conditions, optimizing the balance between maintaining operational readiness and minimizing charging costs
2Loss of time
If electric vehicles charge immediately when connected, then charging time is reduced, but charging costs and energy inefficiency increase
Solution Approach 1:
The system performs preliminary evaluation of charging conditions and schedules charging in advance during optimal time windows. By planning charging sessions ahead of time based on predicted electricity pricing and vehicle requirements, the system can charge during off-peak hours when rates are lower, then wait for the vehicle to be ready without incurring additional time loss during critical operational periods
3Productivity
If the system monitors multiple dynamic factors for charging decisions, then charging efficiency and cost-effectiveness improve, but system complexity increases
Solution Approach 1:
The system combines multiple data sources and evaluation criteria (cargo weight, destination, travel distance, time of travel, electricity pricing, battery charge levels) into a single integrated assigning authority engine. This consolidation allows the system to process multiple factors simultaneously through unified algorithms, improving charging efficiency without proportionally increasing system complexity as would occur with separate independent systems for each factor
Solution Approach 2:
The assigning authority engine serves multiple functions: it monitors vehicle assignments, tracks battery charge levels, analyzes electricity pricing conditions, and determines optimal charging schedules. This multi-functional approach allows a single system component to handle diverse charging decision-making requirements, reducing overall system complexity compared to having specialized systems for each function
Data Source
AI summary
A system (700) and method (720) for enabling a vehicle (710) utilizing electrical propulsion to selectively commence a re-charging session based on one or more variables determined by an assigning authority (1105 that is connected to the vehicle through a mobile network (1110) is disclosed herein. The system (1100) comprises an assigning authority engine (1105), a mobile device (110) for an electric vehicle (1000), and a charging station (715).