Adsptive assistance system for electric-assisted vehicle

Abstract

This invention relates to an adaptive system for an electric-assisted vehicle, comprising: a sensing module, a storage module, a communication module, a processor, and a drive module. The sensing module acquires pedaling torque and cadence signals from the electric-assisted vehicle. The processor calculates real-time power and obtains riding data based on these signals, and transmits the riding data to a cloud platform via the communication module. A machine learning algorithm is then used to obtain the power and form the current power. The processor obtains a dynamic power range based on the ratio of the current power to a reference value. When the real-time power is less than or greater than the power range and remains below or above the range for a set time, it generates a downshift or upshift command, causing the drive module to drive the motor to upshift or downshift.

Claims

1. An adaptive system for an electric-assisted vehicle, comprising: A sensing module includes a torque sensor and a cadence sensor, the torque sensor acquiring a pedaling torque signal from an electric-assisted vehicle, and the cadence sensor acquiring a cadence signal from the electric-assisted vehicle; a storage module storing current power, the pedaling torque signal, the cadence signal, and cycling data; and a communication module for communicating with a cloud platform and the storage module, wherein the communication module can transmit the cycling data to the cloud platform, and the cloud platform obtains a power based on the cycling data using a machine learning algorithm. A processor is communicatively connected to the communication module, the sensing module, and the storage module. The processor calculates a real-time power based on the pedaling torque signal and the cadence signal and obtains the riding data. It can also receive the power from the cloud platform through the communication module and store the power in the storage module to form the current power. Based on the ratio of the current power to a reference value, it applies a reference downshift power and a reference upshift power to obtain a dynamic power range. When the real-time power is less than the minimum value of the power range and the duration exceeds a set time, the processor generates a downshift command. When the real-time power is greater than the maximum value of the power range and the duration exceeds the set time, the processor generates an upshift command. A drive module is connected to the processor and drives a motor of the electric-assisted vehicle to downshift or upshift according to the downshift command or the upshift command.

2. The electric-assisted vehicle adaptive system as claimed in claim 1, wherein the power is a functional threshold power.

3. The electric-assisted vehicle adaptive system as claimed in claim 1 further includes an environment sensor that acquires an environment parameter, and the processor generates the downshift command or the upshift command based on the environment parameter, wherein the environment parameter includes a slope parameter, a headwind parameter, a road resistance parameter, and a load parameter.

4. The electric-assisted vehicle adaptive system as claimed in claim 1, wherein when the instantaneous power is less than an effective set power threshold and the duration of the cadence signal being less than an effective set cadence threshold exceeds a predetermined time, the processor determines that the electric-assisted vehicle is in a gliding state.

5. The electric-assisted vehicle adaptive system as described in claim 4 further includes a locking module communicatively connected to the processor, wherein when the processor determines that the electric-assisted vehicle is in the coasting state, the processor is restricted by the locking module from transmitting the upshift command or the downshift command to the drive module.

6. The electric-assisted vehicle adaptive system as claimed in claim 1, further comprising an electronic device communicatively connected to the cloud platform and the communication module, wherein the processor can transmit the riding data to the electronic device, and the electronic device can transmit the riding data to the cloud platform.

7. The electric-assisted vehicle adaptive system as claimed in claim 1, wherein the drive module includes multiple power assist levels, and the drive module drives the motor to shift up or down in a range corresponding to the multiple power assist levels according to the upshift command or the downshift command.

8. The electric-assisted vehicle adaptive system as claimed in claim 1, wherein the cloud platform receives at least three riding data points and obtains the power based on the at least three riding data points through the machine learning algorithm, and when the difference between the power and the current power obtained by the cloud platform through the communication module in the storage module does not exceed a set range, the cloud platform transmits the power to the processor.

9. The electric-assisted vehicle adaptive system as claimed in claim 7, further comprising an interface module communicatively connected to the processor, the interface module being configured to display the current instantaneous power value, the power value, and the value of one of the plurality of assist levels.

10. The electric-assisted vehicle adaptive system as claimed in claim 5, wherein the power is a functional threshold power; the electric-assisted vehicle adaptive system further includes an environmental sensor that acquires an environmental parameter, and the processor generates the downshift command or the upshift command based on the environmental parameter, wherein the environmental parameter includes a slope parameter, a headwind parameter, a road resistance parameter, and a load parameter; the electric-assisted vehicle adaptive system further includes an electronic device that is communicatively connected to the cloud platform and the communication module, the processor can transmit the riding data to the electronic device, and the electronic device can transmit the riding data to the cloud platform; the drive module includes multiple assist levels, and the drive module drives the motor to upshift or downshift according to the upshift command or the downshift command corresponding to the range of the multiple assist levels; the cloud platform receives at least three riding data sets and obtains a result through the machine learning algorithm based on the at least three riding data sets. The power is transmitted to the processor when the difference between the power and the current power obtained by the cloud platform through the communication module and the current power in the storage module does not exceed a set range. The electric-assisted vehicle adaptive system also includes an interface module that communicates with the processor. The interface module displays the current real-time power value, the power value, and the value of one of the multiple assist levels. The electric-assisted vehicle adaptive system also includes a system constant. The real-time power is the product of the pedaling torque signal, the cadence signal, and the system constant. The riding data includes a normalized power, a peak power, and a power stability curve. When the normalized power exceeds a power range, the peak power exceeds a peak limit, or the fluctuation range of the power stability curve exceeds a fluctuation limit, the machine learning algorithm does not obtain the power based on the riding data. The communication module is a Bluetooth module. The setting range is ±15%.

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