BEV Navigation Routing for Energy Conservation
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Solution Overview
Problem
Conventional navigation systems for battery electric vehicles (BEVs) do not optimally account for the need to conserve energy when the battery state of charge (SOC) is low, leading to potential power down situations and damage if no charging station is available, as they typically prioritize shortest distance or time over energy efficiency.
Innovation Solution
The navigation system preferentially selects low-speed routes and congested roads based on real-time traffic and speed limit information to reduce energy consumption, and recommends avoiding high-occupancy vehicle lanes when the SOC is insufficient to reach a destination using conventional routes, thereby directing the vehicle to a charging station if necessary.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If conventional navigation systems select routes based on shortest distance or time, then travel efficiency is improved, but energy consumption increases and battery electric vehicles face power down risk
Solution Approach 1:
The navigation system changes the routing parameter from minimizing time to minimizing energy consumption. It calculates energy consumption for different routes and selects the route that minimizes battery usage, thereby resolving the contradiction between travel time and energy consumption by transforming the optimization criterion.
Solution Approach 2:
The system dynamically adjusts route selection based on real-time battery state of charge levels. When battery charge is high, it may select faster routes; when charge is low, it prioritizes energy-efficient routes, making the routing strategy adaptive to changing energy conditions.
2Productivity
If high speed routes are selected to minimize travel time, then productivity is improved, but energy consumption increases leading to reduced travel range
Solution Approach 1:
The system changes the optimization parameter from speed to energy efficiency. It evaluates routes based on energy consumption characteristics rather than travel time, selecting routes that minimize battery usage even if they are slower, thereby resolving the contradiction between productivity and energy consumption.
Solution Approach 2:
The routing system dynamically adapts to battery state of charge, adjusting the balance between speed and energy efficiency. When battery charge is sufficient, it may allow higher speed routes; when charge is low, it prioritizes energy conservation, making the system responsive to energy constraints.
3Ease of operation
If the vehicle follows conventional routing to destination, then destination reachability is improved, but power down events occur and battery damage risk increases when charging is needed
Solution Approach 1:
The system performs preliminary calculation of energy consumption for the entire route before departure and identifies potential power down risks in advance. It proactively selects routes that ensure sufficient energy margin to reach the destination or a charging station, preventing power down events before they occur.
Solution Approach 2:
The system continuously monitors battery state of charge during travel and compares it with the planned energy consumption profile. When it detects that the vehicle may not reach the destination with current charge, it provides feedback to the driver or automatically adjusts the route to a charging station, ensuring reliable operation.
Data Source
AI summary
A battery electric vehicle (BEV) navigation routing system and routing methods are presented, in which a traveling route is determined from the current vehicle location to the destination location by preferentially selecting low speed routes over higher speed routes if the present state of charge of the vehicle battery is insufficient to reach the destination location using shortest time or shortest distance routes.