EV Route Planning With Charging Stops for Accurate Range Prediction
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Solution Overview
Problem
Existing electric vehicle (EV) systems fail to accurately predict range due to limited recharging options and simplistic algorithms, leading to range anxiety for drivers.
Innovation Solution
A route optimization system for EVs that considers various vehicle and environmental factors to intelligently determine energy consumption and propose charging locations along the route, using real-time and historical data to enhance range prediction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If simple algorithms are used to estimate vehicle range, then the system complexity is reduced, but the measurement precision of range prediction deteriorates
Solution Approach 1:
The system dynamically adjusts multiple parameters including vehicle operating conditions (speed, acceleration, temperature), environmental factors (weather, terrain, elevation), and charging station data to continuously refine range predictions. This multi-parameter approach transforms the simple algorithm into an adaptive prediction system that maintains accuracy without requiring overly complex infrastructure.
Solution Approach 2:
The system implements feedback loops where actual energy consumption data from previous trips is compared with predicted consumption, and the algorithm adjusts future predictions based on these discrepancies. Real-time vehicle sensor data feeds back into the prediction model, allowing continuous improvement of range accuracy while maintaining computational efficiency.
2Device complexity
If limited recharging options are available, then the infrastructure complexity is reduced, but the reliability of EV travel deteriorates
Solution Approach 1:
The system performs preliminary identification and evaluation of charging stations along the planned route before the vehicle reaches them. It pre-calculates optimal charging stops, estimates charging times, and verifies station availability in advance, allowing drivers to plan trips with confidence even when charging infrastructure is limited or sparsely distributed.
Solution Approach 2:
The route optimization system acts as an intermediary between the vehicle and the charging infrastructure, translating limited charging options into reliable travel plans. It mediates the mismatch between vehicle range requirements and available charging stations by intelligently selecting optimal charging stops and adjusting routes to ensure reliable completion of trips.
3Measurement precision
If more vehicle operating conditions are evaluated, then the measurement precision of energy consumption prediction is improved, but the device complexity increases
Solution Approach 1:
The system segments the evaluation of vehicle operating conditions into distinct modules: propulsion system parameters (motor power, efficiency), thermal management (battery temperature, HVAC), auxiliary systems (lights, wipers), and environmental factors. Each segment processes specific data independently and contributes to the overall energy consumption calculation, making the complex evaluation manageable and computationally efficient.
Data Source
AI summary
A route optimization system for a battery electric vehicle (BEV) includes a controller programmed to perform the following operations. Determine a navigational route to a destination. Determine a predicted intelligent energy consumption of the BEV based on a set of vehicle operating conditions. Determine a trip estimated energy consumption based on the navigational route and the predicted intelligent energy consumption. If the trip estimated energy consumption is greater than a remaining energy in the high voltage battery, determine an electric vehicle supply equipment (EVSE) charging location along the navigational route. Determine an updated trip estimated energy consumption that accounts for addition of the EVSE charging location to the navigational route. Propose, to the user, an updated navigational route including the EVSE charging location if the remaining energy in the high voltage battery is sufficient to account for the addition of the EVSE charging location to the navigational route.