EV Trip Planning System with Charging Station Recommendation
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Solution Overview
Problem
The limited driving range of battery electric vehicles (BEVs) poses challenges for developing a mature transportation system, as drivers need to carefully plan their trips to avoid being stranded due to drained batteries, and the accessibility of charging facilities is crucial for their viability.
Innovation Solution
A vehicle-based computing system that includes a processor and interface to identify and recommend nearby charging stations, query databases for time-from-route and wait-times, and schedule recharging, ensuring drivers can plan their trips effectively and avoid battery drainage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If drivers rely on limited battery range for trip planning, then vehicle simplicity is maintained, but drivers become stranded due to drained batteries
Solution Approach 1:
The system automatically queries databases for charging station locations, calculates time-from-route, estimates wait-times, and presents charging options without requiring manual driver intervention. The vehicle's processor autonomously performs trip planning and charging coordination, freeing drivers from complex manual planning while maintaining system simplicity.
Solution Approach 2:
The system continuously monitors battery charge levels, compares remaining range against destination requirements, and provides real-time feedback to drivers about charging needs. It dynamically adjusts trip plans based on actual battery status and charging station availability, ensuring reliable trip planning through ongoing feedback loops.
2Productivity
If drivers manually plan charging stops, then system complexity is reduced, but trip planning time and driver effort increase
Solution Approach 1:
The system pre-identifies charging stations along potential routes before the driver needs to make a charging decision. By querying databases in advance and pre-calculating time-from-route and wait-times, the system prepares charging options ahead of time, allowing drivers to make rapid decisions without manual planning effort.
Solution Approach 2:
The system replaces manual driver calculations and map-based planning with automated electronic databases and processor-based route analysis. Instead of drivers manually measuring distances and estimating charging times, the system uses digital databases to provide precise, real-time information about charging station locations and availability.
3Ease of operation
If charging stations are densely distributed, then driver accessibility to charging is improved, but infrastructure cost and complexity increase
Solution Approach 1:
The system provides more charging station information than drivers would manually search for, including detailed data on time-from-route, current wait-times, and availability status. By over-providing this information, the system compensates for the fact that not all charging stations need to be physically accessible, as drivers can make informed decisions based on comprehensive data about the charging network.
Data Source
AI summary
A vehicle includes a traction battery, an interface, and at least one processor configured to present, via the interface, a message including a charge-vehicle recommendation for at least one charge station within the drive range, in response to (i) a selected destination for the vehicle lacking a charge facility for the battery and being within a drive range of the vehicle and (ii) a charge station being within the drive range.