Charging Station Ranking Using Topography to Limit Brake Load
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Solution Overview
Problem
Existing route planning systems for electric heavy-duty vehicles struggle to account for topography when ranking vehicle charging stations, leading to potential brake issues and inefficient charging strategies.
Innovation Solution
A computer system that processes topography data to determine a vehicle station ranking metric for each charging station, prioritizing stations with smaller maximum possible altitude drops to reduce brake load and optimize charging.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the vehicle charges to a high state of charge at a charging station located before a substantial descent, then the vehicle has sufficient energy for the route, but the service brakes experience excessive load leading to brake fading or excessive wear
Solution Approach 1:
The system performs preliminary analysis of topography data around charging stations to identify potential substantial descents ahead. By ranking charging stations based on this preliminary assessment before the vehicle arrives, the system enables the driver to select charging stations that avoid future brake problems, rather than reacting to brake issues after they occur.
Solution Approach 2:
The topography data and ranking metric serve as an intermediary between the charging station selection and the brake performance outcome. Instead of directly controlling brake operation, the system uses topographical information as a mediator to indirectly prevent brake fading by guiding charging station selection away from locations that would cause substantial descents afterward.
2Measurement precision
If the system requires detailed route information and vehicle position data for route planning, then the route planning accuracy improves, but the complexity of information collection and computational operations increases
Solution Approach 1:
The system extracts only the essential topography data needed for charging station ranking, separating this critical information from the full detailed route information. By taking out only the elevation data within predefined areas around charging stations, the system achieves sufficient planning accuracy without requiring complete route details or real-time vehicle position data.
Solution Approach 2:
Instead of analyzing the entire route in detail, the system applies local quality analysis by focusing topographical data collection and processing only on predefined areas around each charging station. This localized approach reduces computational complexity while maintaining the accuracy needed for making charging station selection decisions.
Data Source
AI summary
A computer system has a processor device configured to, for each vehicle charging station in a set of vehicle charging stations: receive topography data indicative of elevations within a predefined area around the vehicle charging station; determine, based on the topography data, a maximum possible altitude drop in relation to the vehicle charging station within the area; and determine, based on the maximum possible altitude drop, a vehicle station ranking metric for the vehicle charging station, wherein the vehicle station ranking metric is determined in such a way that a vehicle charging station with a relatively large first maximum possible altitude drop is ranked lower than a vehicle charging station with a relatively small second maximum possible altitude drop.