E-Bike Motor Assistance Control for Changing Drag Conditions
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Solution Overview
Problem
Conventional electric bicycle control systems often require frequent manual adjustments of assistance levels due to varying riding conditions, leading to discomfort, especially in conditions where gradual adjustments are needed, such as urban riding.
Innovation Solution
A system that automatically and continuously modulates the assistance level based on a parameter representing drag forces, such as slope gradient, headwind, or rolling resistance, using empirical data and sensor information to estimate drag deviations, thereby smoothing assistance level changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional control systems use pre-programmed assistance levels, then the system structure remains simple, but the user must frequently manually adjust assistance levels in varying riding conditions
Solution Approach 1:
The control system automatically adjusts the assistance level by itself based on measured drag forces, eliminating the need for manual user intervention. The system monitors riding conditions through sensors and autonomously modulates the modulation coefficient to match changing drag conditions.
Solution Approach 2:
The system continuously measures actual drag forces using sensors (torque sensor, speed sensor, acceleration sensor) and feeds this information back to the controller, which then adjusts the assistance level accordingly. This closed-loop feedback mechanism enables automatic adaptation to varying riding conditions.
2Speed
If assistance level changes are made abruptly to respond to changing conditions, then the system responds quickly to drag variations, but riding comfort deteriorates
Solution Approach 1:
The assistance level is dynamically adjusted based on the magnitude of drag force changes. The system calculates the difference between current and reference drag forces, and only modulates the assistance level when this difference exceeds a threshold, creating a dynamic rather than static response strategy.
Solution Approach 2:
The system changes the modulation coefficient parameter continuously rather than in discrete steps. By modulating this coefficient based on the measured drag deviation, the system achieves smooth transitions in assistance level that maintain riding comfort while responding to changing conditions.
3Ease of operation
If the system continuously monitors and adjusts assistance level, then riding comfort improves, but energy consumption increases
Solution Approach 1:
The system uses a reference drag force profile that predicts expected drag under nominal conditions. By comparing actual drag against this pre-established reference, the system can anticipate when adjustments are needed and prepare accordingly, reducing unnecessary monitoring and adjustment cycles.
Solution Approach 2:
The system performs continuous monitoring but only executes assistance level adjustments when the drag deviation exceeds a predetermined threshold. This partial action approach avoids the energy waste of constant adjustment while still maintaining comfort during significant drag variations.
4Measurement precision
If the system uses multiple sensors and complex calculations to estimate drag forces, then measurement precision improves, but device complexity increases
Solution Approach 1:
Existing sensors in the electric bicycle system (torque sensor, speed sensor, acceleration sensor) are utilized for multiple purposes. These sensors not only perform their primary functions but also contribute to drag force estimation, eliminating the need for additional dedicated sensors and reducing overall system complexity.
Solution Approach 2:
The drag force estimation combines multiple measurement sources (torque, speed, acceleration) into a single unified calculation. By merging these data streams and processing them through a combined estimation algorithm, the system achieves precise drag measurement without requiring separate dedicated measurement systems for each parameter.
Data Source
AI summary
The present disclosure relates to a method for controlling an electric motor of a pedal-operated vehicle, comprising the steps of measuring a pedal torque applied to a crankset of the vehicle; applying to the electric motor a control proportional to the product of the torque and a variable assistance level; determining a parameter indicative of a deviation of vehicle drag forces from nominal conditions, as a linear combination of a measurement of a motor torque, indicative of an instantaneous force supplied by the motor, the measured pedal torque, indicative of an instantaneous force resulting from pedaling, and a nominal drag force, function of speed and constant friction coefficients determinable for nominal riding conditions; and continuously modulating the assistance level as a function of the parameter indicative of the drag deviation.