Method and system for controlling riding of electric bike

Abstract

A method for riding control of an electric bicycle includes: receiving or measuring riding information of the electric bicycle via a motor driver of the electric bicycle; receiving the riding information via a near-end computing device to calculate and generate a plurality of riding targets corresponding to the electric bicycle and a component ratio of the plurality of riding targets; when the riding information is updated, determining via the computing device whether to adjust the component ratio; if so, adjusting the component ratio; if not, proceeding to the next step; and using an algorithm via the computing device to calculate a set of optimized parameters based on the riding information and the component ratio, updating and storing them in an optimized parameter array list of the electric bicycle for riding control of the electric bicycle.

Claims

1. A method for controlling the riding of an electric bicycle, comprising: The method involves receiving or measuring riding information of an electric bicycle via a motor driver, including pedaling force, cadence, and speed; receiving the riding information via a near-end computing device to calculate and generate a plurality of riding targets for the electric bicycle, and a component ratio of the plurality of riding targets; when the riding information is updated, the computing device determines whether to adjust the component ratio; if so, the component ratio is adjusted; if not, the next step is performed; a plurality of target scores are calculated for each plurality of riding targets based on the riding information, the plurality of riding targets, and the component ratio; a plurality of weights are obtained for each plurality of target scores, and a weighted result is calculated based on the plurality of weights; and the computing device uses an algorithm to calculate a set of optimization parameters based on the weighted result, updates the set of optimization parameters, and stores it in an optimization parameter array table of the electric bicycle for riding control, wherein the set of optimization parameters is related to the motor driver.

2. The method for controlling the riding of an electric bicycle as described in claim 1, wherein the plurality of riding objectives includes at least two of a performance objective, a riding comfort objective, and a range objective.

3. The method for controlling the riding of an electric bicycle as described in claim 2 further includes: When the riding information and the composition ratio are updated, the plurality of weights are adjusted according to the updated riding information and the updated composition ratio to update the group optimization parameters.

4. The method for controlling riding an electric bicycle as described in claim 2, wherein the weighted result is calculated based on a weighted average method, a weighted geometric average method, a nonlinear weighting method, or a hierarchical weighting method.

5. The method for controlling the riding of an electric bicycle as described in claim 4, wherein when the weighted result is calculated based on the weighted average method, the weighted result st is represented as follows: where is a performance score, is a riding comfort score, is a range score, is a first weight corresponding to the performance score, is a second weight corresponding to the riding comfort score, and is a third weight corresponding to the range score.

6. The method for controlling the riding of an electric bicycle as described in claim 5, wherein the first weight, the second weight, and the third weight are represented as follows: where and are constants, is a preset lower limit value of the ride comfort score, is a preset lower limit value of the range score, is a preset minimum value of the second weight, is a preset maximum value of the second weight, is a preset minimum value of the third weight, is a preset maximum value of the third weight, is a preset initial value of the second weight, and is a preset initial value of the third weight.

7. The method for controlling the riding of an electric bicycle as described in claim 5, wherein the first weight has a preset initial value, and the preset initial value of the first weight, the preset initial value of the second weight, and the preset initial value of the third weight are expressed as follows: where is a constant, is a preset minimum value of the first weight, and refers to the performance target.

8. The method for controlling riding an electric bicycle as described in claim 1, wherein the algorithm comprises a Nondominated Sorting Genetic Algorithm II (NSGA-II), a Genetic Algorithm (GA), a Multi-Objective Particle Swarm Optimization (MOPSO) algorithm, or a Multi-Objective Ant Colony Optimization (MOACO) algorithm.

9. A system for controlling the riding of an electric bicycle, comprising: An electric bicycle includes: a motor driver for receiving or measuring riding information of a user riding the electric bicycle, the riding information including pedaling force, cadence and speed; And a controller, connected to the motor driver, for receiving the riding information; The device also includes a near-end computing unit connected to the controller, comprising: a processor for receiving riding information transmitted by the controller to calculate and generate a plurality of riding targets corresponding to the electric bicycle and a component ratio of the plurality of riding targets; and a memory connected to the processor for storing at least one computer-readable instruction, wherein the processor uses the at least one computer-readable instruction to execute a method of riding control of the electric bicycle, the method of riding control comprising: calculating a plurality of target scores corresponding to the plurality of riding targets based on the riding information, the plurality of riding targets and the component ratio; obtaining a plurality of weights corresponding to the plurality of target scores and calculating a weighted result based on the plurality of weights; and calculating a set of optimization parameters using an algorithm based on the weighted result, updating and storing the set of optimization parameters in an optimization parameter array table of the electric bicycle for riding control of the electric bicycle, wherein the set of optimization parameters is related to the motor drive.

10. The electric bicycle riding control system as described in claim 9, wherein the controller updates a parameter setting of the motor driver based on the set of optimized parameters.

11. The electric bicycle riding control system as described in claim 9, wherein the electric bicycle further includes a storage device connected to the controller for storing the optimized parameter array table.

12. The electric bicycle riding control system as described in claim 9, wherein the electric bicycle further includes an on-board diagnostic system connected to the controller, and the computing device is connected to the on-board diagnostic system via a wired or wireless communication interface.

13. The electric bicycle riding control system as described in claim 12, wherein the motor driver transmits the riding information to the controller, which transmits the riding information to the on-board diagnostic system via a local area network communication protocol.

14. The electric bicycle riding control system as described in claim 9, wherein the computing device further comprises: A bus connects the processor and the memory; A display element, connected to the processor via the bus, is used to display data or instructions and provide user operation; a transmission module, connected to the processor via the bus, the processor communicates with an on-board diagnostic system of the electric bicycle via the transmission module, and stores the set of optimization parameters back to a storage device built into the electric bicycle to update the optimization parameter array table stored in the storage device; and a power supply element, providing the power required for the operation of the processor, the memory and the transmission module via the bus.

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