Virtual Gearing for Autonomous E-Bikes With Pedal-Wheel Torque Mapping
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Solution Overview
Problem
Current transportation solutions for short distances, such as traditional public transportation, taxis, and bikeshare services, are often inconvenient, inflexible, and expensive, lacking user agency in route selection and requiring extensive infrastructure, which hinders efficient on-demand transportation within city centers.
Innovation Solution
An autonomous electronic bicycle system that allows bicycles to be summoned on demand, autonomously navigating to users and then switching to manual mode for rider operation, utilizing a combination of electric motors, sensors, and navigation systems to optimize route efficiency and vehicle distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If bikeshare services saturate the entire service area with many static pickup points, then service availability is improved, but infrastructure cost and device quantity increase significantly
Solution Approach 1:
The patent implements dynamic vehicle redistribution where bicycles autonomously navigate to high-demand locations based on real-time user requests and historical data. Instead of static pickup points, the system continuously adjusts vehicle distribution, allowing a smaller fleet to serve the entire area by moving vehicles to where they are needed most at any given time.
Solution Approach 2:
The autonomous bicycles self-navigate to users and self-reposition to optimal locations without requiring manual retrieval or fixed infrastructure. The vehicles autonomously travel to pickup points, deliver themselves to users, and can autonomously return to base stations or relocate to high-demand areas, eliminating the need for extensive static infrastructure.
2Ease of operation
If traditional public transportation is used, then transportation service is provided, but flexibility in route selection and user agency are lost
Solution Approach 1:
The system pre-calculates optimal routes based on user preferences, historical data, and real-time conditions before the user even requests service. When a user requests a bicycle, the autonomous vehicle has already determined the most efficient pickup location and route, allowing the user to simply accept the suggested route or select from pre-computed alternatives without complex decision-making during the ride.
Solution Approach 2:
The system continuously collects user feedback on route preferences, travel times, and satisfaction levels, then uses this feedback to refine future route recommendations. Users can adjust their preferences, and the system adapts by modifying route calculations to better match user needs, maintaining flexibility while improving convenience over time.
3Ease of operation
If taxi or rideshare services are used for short trips, then transportation is provided, but cost increases and traffic congestion worsens
Solution Approach 1:
The patent replaces the mechanical system of human-operated taxis and rideshare vehicles with autonomous electric bicycles. This substitution eliminates the need for paid drivers, significantly reducing operational costs. The electric bicycles also consume far less energy per passenger-mile compared to gas-powered taxis, and their smaller size allows them to navigate through traffic more efficiently, reducing overall congestion.
Solution Approach 2:
The system changes key operational parameters by using electric power instead of gasoline, autonomous operation instead of human drivers, and bicycle-scale vehicles instead of car-scale vehicles. These parameter changes collectively reduce energy consumption, lower operational costs, and improve traffic flow efficiency while maintaining transportation service quality.
Data Source
AI summary
An autonomous electronic bicycle comprises a frame, a wheel that can be powered by a first electronic motor, and a pedal assembly connected to a pedal motor. The pedal assembly is not mechanically connected to the wheel, but the autonomous electronic bicycle simulates a mechanical connection by powering the rear wheel proportional to the user's pedaling force. The autonomous electronic bicycle uses a virtual gear ratio based on the cadence of the rider, the current incline of the bicycle, and the current speed of the bicycle. The virtual gear ratio can be a ratio between a torque of the set of pedals and a torque of the wheel.