EV Charging Monitor Using Wait-Time and State-of-Charge Feedback
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Solution Overview
Problem
The construction of electric vehicle charging stations has lagged behind the sales of EVs, leading to increased wait times and uncertainty for users, especially new EV users unfamiliar with optimal charging practices that affect battery life.
Innovation Solution
An electric vehicle monitoring system with a display, server, and electronic control unit (ECU) that processes data from charging stations to generate a frequency diagram showing wait times and charge times, utilizing geofenced zones, location data, and battery state to optimize charging decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If EV charging stations are constructed to meet growing EV sales demand, then charging availability improves, but construction costs and infrastructure complexity increase
Solution Approach 1:
The system continuously collects real-time data from charging stations including availability status, wait times, and utilization metrics. This feedback loop enables dynamic routing recommendations that adapt to current charging station conditions, allowing the system to guide users to optimally available stations without requiring over-provisioning of infrastructure.
Solution Approach 2:
The monitoring system automatically tracks charging station status, calculates wait times, and generates routing recommendations without manual intervention. The system serves itself by collecting data from charging stations, processing it through the server, and providing actionable insights to users, reducing the need for manual infrastructure management.
2Reliability
If users charge EV batteries to full capacity like ICE vehicle fuel tanks, then energy security improves, but battery lifespan deteriorates due to improper charging practices
Solution Approach 1:
The system recommends charging to partial capacity (e.g., 80%) rather than full capacity, which is sufficient for most daily driving needs. This partial charging approach extends battery lifespan while providing adequate energy security for typical use cases, avoiding the harmful effect of frequent full charging cycles.
Solution Approach 2:
The monitoring system acts as an intermediary between the user and the charging process, providing data-driven recommendations on optimal charging levels. By analyzing battery state, usage patterns, and charging station availability, the system mediates between the desire for energy security and the need to preserve battery health.
3Ease of operation
If users seek nearest charging stations without wait time information, then navigation simplicity improves, but unexpected delays increase due to unknown wait times
Solution Approach 1:
The system calculates and provides wait time estimates before users arrive at charging stations. By preliminarily assessing charging station utilization and queue status, the system enables users to plan their routes and time their charging stops in advance, avoiding unexpected delays while maintaining simple navigation through pre-computed routing recommendations.
Solution Approach 2:
The system continuously monitors charging station status and provides real-time feedback on wait times and availability. This feedback enables dynamic adjustment of routing recommendations, allowing the system to guide users to stations with acceptable wait times while keeping the navigation process simple and automated.
4Measurement precision
If monitoring system collects real-time data from all charging stations, then charging information accuracy improves, but data processing requirements and system complexity increase
Solution Approach 1:
The system extracts only the most relevant data elements from charging stations, such as availability status, current utilization rate, and queue length. By focusing on key metrics rather than collecting all possible data, the system achieves sufficient charging information accuracy while minimizing data processing complexity and computational requirements.
Solution Approach 2:
The system processes and analyzes data with different levels of detail based on local needs. For routing recommendations, it focuses on charging station availability and wait times. For battery management advice, it focuses on charging patterns and battery state. This localized data processing approach maintains accuracy where needed while reducing overall system complexity.
Data Source
AI summary
An electric vehicle (EV) monitoring system for a vehicle includes a display and a server configured to receive data from one or more charging stations. The data includes a rate of charge. The EV monitoring system also includes an electronic control unit (ECU) communicatively coupled with the server and the display. The ECU includes data processing hardware that includes an EV monitoring application. The EV monitoring application includes a state of charge of the vehicle and is configured to generate a frequency diagram based on the rate of charge received by the server and the state of charge.