EV Trip Planner Charging Stops Based on Partial Battery Range
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Solution Overview
Problem
It is challenging for electric vehicle drivers to accurately identify necessary charging stations along their route due to reliance on historical data, leading to potential unnecessary charging stops and inefficient charging times, especially when sufficient historical data is not available.
Innovation Solution
A navigation system that determines a partial range based on the current state of charge of the electric vehicle's battery and suggests charging stations as waypoints only when the destination is outside this range, optimizing charging stops by calculating the required recharge time to reach a predetermined state of charge.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If charging stations are suggested based on fixed minimum SOC threshold, then charging stations are suggested when battery charge drops below threshold, but unnecessary charging stops are added to the route especially for short trips
Solution Approach 1:
The patent changes the parameter from a fixed minimum SOC threshold to a dynamic partial range calculation based on current SOC and predetermined percentage. This allows the system to adapt the charging suggestion criteria to the specific trip context, avoiding unnecessary stops while ensuring adequate charging when needed.
Solution Approach 2:
The system transitions from a static charging suggestion approach to a dynamic one that continuously evaluates the partial range based on current battery state and trip requirements. This dynamic adjustment enables real-time optimization of charging stops along the route.
2Loss of information
If historical data is used to predict charging needs, then charging station suggestions can be made, but accurate predictions cannot be made when sufficient historical data is not available
Solution Approach 1:
The system uses real-time vehicle state information and route parameters to self-determine charging needs without relying on external historical data. The partial range calculation is performed autonomously based on current conditions, making the system self-sufficient and adaptable to any trip scenario.
Solution Approach 2:
The system pre-calculates the partial range based on current SOC and predetermined percentages before the trip begins. This preliminary determination of charging requirements allows accurate planning without needing historical trip data, enabling the system to adapt to any destination and route.
3Productivity
If charging stations are suggested without considering partial range optimization, then charging suggestions can be made, but charging time cannot be optimized to reach destination with sufficient charge level
Solution Approach 1:
The patent introduces predetermined percentages (e.g., 80%) of current SOC as optimization parameters to determine the partial range. By charging to maintain this optimized charge level rather than depleting to a fixed threshold, the system reduces total charging time while ensuring sufficient charge for the destination.
Solution Approach 2:
The system continuously monitors current SOC and recalculates the partial range throughout the trip. This feedback mechanism allows dynamic adjustment of charging suggestions to maintain optimal charge levels, ensuring the vehicle reaches the destination with sufficient charge while minimizing total charging time.
Data Source
AI summary
Systems and methods are provided for suggesting a charging station for an electric vehicle. A partial range of the electric vehicle corresponding to a predetermined percentage of the current state of charge of a battery of the electric vehicle is determined. A location corresponding to the partial range, along a route to a destination, is determined and used to select a suggested charging station based on the location corresponding to the partial range. The suggested charging station is generated for presentation at a display.