Apparatus for controlling pulley of continuously variable transmission and method therefor

An apparatus of controlling a pulley of a continuously variable transmission and a method therefore is provided. The apparatus includes a non-transitory storage configured for storing a deep learning model, learning of which is completed and a controller that predicts a vehicle speed and an accelerator position sensor (APS) value for each future time point based on the deep learning model and controls the pulley of the continuously variable transmission based on a pulley ratio for each future time point, the pulley ratio corresponding to the predicted vehicle speed and the predicted APS value, thus preventing a reverse control phenomenon of the pulley ratio and increasing a tension of the belt in the continuously variable transmission.

CROSS-REFERENCE TO RELATED APPLICATION

The present application claims priority to Korean Patent Application No. 10-2021-0079509, filed on Jun. 18, 2021, the entire contents of which is incorporated herein for all purposes by this reference.

BACKGROUND OF THE INVENTION

Field of the Invention

The present invention relates to technologies of predicting a pulley ratio for each future time point and controlling a pulley of a continuously variable transmission based on the predicted pulley ratio for each future time point.

Description of Related Art

In general, a continuously variable transmission may include a drive pulley, a driven pulley, and a belt, which may control oil pressure supplied to the drive pulley and the driven pulley to move the drive pulley and the driven pulley in a shaft direction, thus continuously changing a pulley ratio (a transmission ratio) by a change in diameter of a contact surface between the belt and the drive pulley and a change in diameter of a contact surface between the belt and the driven pulley.

Such a continuously variable transmission may obtain a continuous transmission ratio to enhance power transfer efficiency, have no shift shock while driving, improve fuel efficiency of the vehicle, and maintain an optimal driving state.

Such an existing technology of controlling the pulley of the continuously variable transmission is a method of adjusting a pulley ratio based on a demand power corresponding to a vehicle speed and the amount of accelerator pedal (an accelerator position sensor (APS) value). The existing technology decreases a pulley ratio (under drive) to lower revolutions per minute (RPM) of a power source to decrease an output power, when the demand power is low, and increases a pulley ratio (overdrive) to increase an RPM of the power source, when the demand power is high.

Such an existing technology causes a pulley ratio reverse control phenomenon of controlling a pulley in a direction of decreasing the pulley ratio and immediately controlling the pulley in a direction of increasing the pulley ratio, when a future demand power is higher than a current demand power, and increases a pulley ratio in a state where a high load is loaded onto the belt as the demand power is increased in advance to increase a tension of the belt.

BRIEF SUMMARY

Various aspects of the present invention are directed to providing an apparatus of controlling a pulley of a continuously variable transmission for predicting a vehicle speed and an accelerator position sensor (APS) value for each future time point based on a deep learning model, the learning of which is completed and controlling the pulley of the continuously variable transmission based on a pulley ratio for each future time point, corresponding to the predicted vehicle speed and the predicted APS value, to prevent a reverse control phenomenon of the pulley ratio and prevent a tension of a belt in the continuously variable transmission from being increased and a method therefor.

The technical problems to be solved as various exemplary embodiments of the present invention are not limited to the aforementioned problems, and any other technical problems not mentioned herein will be clearly understood from the following description by those skilled in the art to which various exemplary embodiments of the present invention pertains. Furthermore, it may be easily seen that purposes and advantages of the present invention may be implemented by means indicated in claims and a combination thereof.

According to various aspects of the present invention, an apparatus of controlling a pulley of a continuously variable transmission may include a non-transitory storage configured for storing a deep learning model, learning of which is completed and a controller that predicts a vehicle speed and an accelerator position sensor (APS) value for each future time point based on the deep learning model and controls the pulley of the continuously variable transmission based on a pulley ratio for each future time point, the pulley ratio corresponding to the predicted vehicle speed and the predicted APS value.

In various exemplary embodiments of the present invention, the controller may maintain a current pulley ratio during a reference time, when a number of pulley ratios higher than the current pulley ratio above a threshold among pulley ratios for every future time points is greater than a reference value, at a downward control time point of the current pulley ratio.

In various exemplary embodiments of the present invention, the controller may upwardly control a current pulley ratio, when a number of pulley ratios higher than a current pulley ratio above a threshold among pulley ratios for every future time points is greater than a reference value, in a state where a current gear stage is maintained.

In various exemplary embodiments of the present invention, the controller may increase the current pulley ratio in proportion to the APS value.

In various exemplary embodiments of the present invention, the deep learning model may be a variational auto-encoder (VAE)-based deep learning model having an encoder configured to receive time series data for a driving profile prior to a predicted time point and a decoder configured to predict a speed of a vehicle and an APS value based on a low-dimensional variable, which is an output of the encoder, and a vehicle speed, an APS value, and a driving profile at the predicted time point.

In various exemplary embodiments of the present invention, the driving profile may include at least one of a gas pedal position (GPP) value, revolutions per minute (RPM), a pulley ratio, a vehicle speed, a gradient of a road, a curvature of the road, a steering angle, a brake pedal position (BPP) value, a separation distance from a preceding vehicle, a relative speed with the preceding vehicle, information related to traffic lights in front, or an APS value.

In various exemplary embodiments of the present invention, the deep learning model may output a vehicle speed in a form of time series data and an APS value in a form of time series data.

In various exemplary embodiments of the present invention, the encoder may model a feature of the time series data for the driving profile prior to the predicted time point as a low-dimensional variable distributed in a first region.

According to various aspects of the present invention, a method for controlling a pulley of a continuously variable transmission may include storing, by a storage, a deep learning model, learning of which is completed, predicting, by a controller, a vehicle speed and an accelerator position sensor (APS) value for each future time point based on the deep learning model, and controlling, by the controller, the pulley of the continuously variable transmission based on a pulley ratio for each future time point, the pulley ratio corresponding to the predicted vehicle speed and the predicted APS value.

In various exemplary embodiments of the present invention, the controlling of the pulley of the continuously variable transmission may include maintaining a current pulley ratio during a reference time, when a number of pulley ratios higher than the current pulley ratio above a threshold among pulley ratios for every future time points is greater than a reference value, at a downward control time point of the current pulley ratio.

In various exemplary embodiments of the present invention, the controlling of the pulley of the continuously variable transmission may include upwardly controlling a current pulley ratio, when a number of pulley ratios higher than a current pulley ratio above a threshold among pulley ratios for every future time points is greater than a reference value, in a state where a current gear stage is maintained.

In various exemplary embodiments of the present invention, the upwardly controlling of the current pulley ratio may include increasing the current pulley ratio in proportion to a change rate of the APS value.

DETAILED DESCRIPTION

Hereinafter, various exemplary embodiments of the present invention will be described in detail with reference to the exemplary drawings. In adding the reference numerals to the components of each drawing, it should be noted that the identical or equivalent component is designated by the identical numeral even when they are displayed on other drawings. Furthermore, in describing the exemplary embodiment of the present invention, a detailed description of well-known features or functions will be ruled out in order not to unnecessarily obscure the gist of the present invention.

FIG.1is a block diagram illustrating a system for controlling a pulley of a continuously variable transmission in a vehicle, to which embodiments of the present invention are applied, which illustrates that a power source is an engine10. However, it is obvious that it is applicable in the same manner when the power source is a motor.

As shown inFIG.1, the system for controlling the pulley of the continuously variable transmission in the vehicle, to which embodiments of the present invention are applied, may include a throttle position sensor (TPS)100, an accelerator position sensor (APS)110, a vehicle speed sensor120, an acceleration sensor130, a wheel speed sensor140, a slope sensor150, a brake position sensor (BPS)160, an engine revolutions per minute (RPM) sensor170, a torque sensor180, a pulley ratio sensor190, a transmission control unit (TCU)200, a memory210, and a display220.

Seeing the respective components, first of all, the TPS100may detect a throttle position according to an opening and closing amount of a throttle valve of an engine10to generate a throttle position sensing signal according to the throttle position. The APS110may detect an accelerator position according to a manipulation state of an accelerator pedal of a driver to generate an accelerator position sensing signal according to the accelerator position. The vehicle speed sensor120may detect a vehicle speed according to driving of the vehicle to generate a vehicle speed sensing signal according to the vehicle speed. The acceleration sensor130may detect a change in longitudinal acceleration according to driving of the vehicle to generate a longitudinal acceleration sensing signal according to the sensed change or may detect a change in lateral acceleration according to driving of the vehicle to generate a lateral acceleration sensing signal according to the sensed change The wheel speed sensor140may detect a wheel speed (a speed of a wheel) according to driving of the vehicle to generate a wheel speed sensing signal according to the wheel speed. The slope sensor150may detect a slope of a vehicle body according to hill (or curved road) driving of the vehicle to generate a slope sensing signal according to the slope of the vehicle body. The BPS160may detect a manipulation state of a brake pedal of the driver to generate a brake position sensing signal according to the manipulation state of the brake pedal. The engine RPM sensor170may detect a rotary RPM according to running of the engine10to generate an RPM sensing signal according to the rotary RPM. The torque sensor180may detect a rotational torque of a torque converter (T/C)20combined between the engine10and a continuously variable transmission30to generate a torque sensing signal according to the rotational torque of the T/C20. The pulley ratio sensor190may detect a manipulation state of a pulley ratio according to shift of the continuously variable transmission30to generate a pulley ratio sensing signal according to the manipulation state of the pulley ratio.

Meanwhile, to control shift of the vehicle, the TCU200may receive the throttle position sensing signal from the TPS100, the accelerator position sensing signal from the APS110, the vehicle speed sensing signal from the vehicle speed sensor120, the acceleration sensing signal from the acceleration sensor130, the wheel speed sensing signal from the wheel speed sensor140, the slope sensing signal from the slope sensor150, the brake position sensing signal from the BPS160, the RPM sensing signal from the engine RPM sensor170, the torque sensing signal from the torque sensor180, or the pulley ratio sensing signal from the pulley ratio sensor190.

The TCU200may collect data for identifying a road state (e.g., a gradient, a curvature, or the like) and a driving state of the vehicle by the sensing signal from each sensor and may analyze the collected data to classify information. In the instant case, driving information data analyzed by the collected data may include an opening and closing amount of the throttle valve, a position of an accelerator, a current pulley ratio of the continuously variable transmission30, a vehicle speed, acceleration, an engine RPM, an average vehicle speed, a difference in wheel RPM of a wheel, a slope of the vehicle, an operational period of a brake, a required amount of torque of the engine10, a curvature of the road, a gradient of the road, or the like. The TCU200may adjust a pulley ratio based on the analyzed driving information data. The memory210may store various logics, algorithms, and programs necessary for shift. The display220may display a current pulley ratio under control of the TCU200such that the driver may identify the current pulley ratio.

FIG.2is a drawing illustrating a continuously variable transmission in a system for controlling a pulley of the continuously variable transmission in a vehicle, to which embodiments of the present invention are applied.

As shown inFIG.2, a continuously variable transmission30in the system for controlling the pulley of the continuously variable transmission in the vehicle, to which embodiments of the present invention are applied, may be composed such that power of an engine10is transferred in an order of a T/C20, a planetary gear PG, a drive pulley P1, a driven pulley P2, a deceleration gear, and a driving wheel W. The power of the engine10may be varied to a continuously variable transmission ratio by a pulley to be delivered to the driving wheel W.

Herein, the drive pulley P1may be connected to the engine10and the driven pulley P2may be connected to the driving wheel W. When static shift in a direction opposite to a driving direction is generated by a driver while driving, a rotation direction of the drive pulley P1is rapidly changed by power of the engine10, whereas the driven pulley P2performs late direction conversion while maintaining its rotation direction by inertia of the driving wheel W, although receiving power through a belt.

Due to the provided configuration, as a tensile force and a compressive force are loaded onto both sides of the belt connecting between the drive pulley P and the driven pulley P2, the belt may slip on the drive pulley P1and the driven pulley P2to be damaged. A TCU200may upwardly control pressure of the drive pulley P1and the driven pulley P2, when static shift occurs, to prevent such a belt slip phenomenon. In the instant case, the drive pulley P1and the driven pulley P2may be varied and controlled in pressure according to operations of actuators respectively connected thereto. As the actuators apply oil pressure, the TCU200may upwardly control the pressure of the drive pulley P1and the driven pulley P2.

FIG.3is a block diagram illustrating a configuration of an apparatus of controlling a pulley of a continuously variable transmission according to various exemplary embodiments of the present invention.

As shown inFIG.3, the apparatus of controlling the pulley of the continuously variable transmission according to various exemplary embodiments of the present invention may include a storage31and a controller32. In the instant case, the respective components may be combined into one component and some components may be omitted, depending on a manner which executes the apparatus of controlling the pulley of the continuously variable transmission according to various exemplary embodiments of the present invention.

Seeing the respective components, first of all, the storage31may store various logics, algorithms, and programs required in a process of predicting a vehicle speed and an accelerator position sensor (APS) value for each future time point based on a deep learning model, the learning of which is completed, and controlling a pulley of a continuously variable transmission based on a pulley ratio for each future time point, corresponding to the predicted vehicle speed and the predicted APS value. In the instant case, the pulley ratio for each future time point may be predicted by the vehicle speed for each future time point and the APS value for each future time point and may be used to control the pulley of the continuously variable transmission.

Such a storage31may include at least one type of storage medium, such as a flash memory type memory, a hard disk type memory, a micro type memory, a card type memory (e.g., a secure digital (SD) card or an extreme digital (XD) card), a random access memory (RAM), a static RAM (SRAM), a read-only memory (ROM), a programmable ROM (PROM), an electrically erasable PROM (EEPROM), a magnetic RAM (MRAM), a magnetic disk, and an optical disk.

The controller32may perform the overall control such that respective components may normally perform their own functions. Such a controller32may be implemented in a form of hardware, may be implemented in a form of software, or may be implemented in a form of a combination thereof. The controller32may be implemented as, but not limited to, a microprocessor.

The controller32may perform a variety of control in a process of predicting a vehicle speed and an accelerator position sensor (APS) value for each future time point based on a deep learning model, the learning of which is completed, and controlling a pulley of a continuously variable transmission based on a pulley ratio for each future time point, corresponding to the predicted vehicle speed and the predicted APS value. In the instant case, the controller32may predict (determine) a pulley ratio for each future time point based on the predicted vehicle speed and the predicted APS value.

When the number of pulley ratios higher than a current pulley ratio above a threshold among pulley ratios for every future time points is greater than a reference value (e.g., 2) at a downward control time point of the pulley ratio, the controller32may maintain the current pulley ratio during a reference time (e.g., one second) to prevent a reverse control phenomenon of the pulley ratio. Herein, downward control of the pulley ratio in a continuously variable transmission30ofFIG.1may correspond to upshift control in a steptronic automatic transmission, and upward control of the pulley ratio in the continuously variable transmission30may correspond to downshift control in the steptronic automatic transmission. Furthermore, the pulley ratio indicates the ratio of a diameter of a driven pulley P2ofFIG.2to a diameter of a drive pulley P1ofFIG.2. Furthermore, the pulley ratio higher than the current pulley ratio above the threshold refers to 1.5, when the current pulley ratio is 1.

When the number of pulley ratios higher than the current pulley ratio above the threshold among the pulley ratios for every future pulley ratios is greater than the reference value (e.g., 2) at a time point when the pulley ratio is maintained, the controller32may control the continuously variable transmission30to perform upward control of the pulley ratio, thus preventing a tension of the belt in the continuously variable transmission30from being increased. In the instant case, the controller32may increase a pulley ratio in proportion to a change rate of the APS value.

Hereinafter, the operation of the controller32will be described in detail with reference toFIG.4andFIG.5.

FIG.4is a drawing illustrating an operation of a controller provided in an apparatus of controlling a pulley of a continuously variable transmission according to various exemplary embodiments of the present invention.

As shown inFIG.4, as pulley ratios for every future time points, for example, a controller32ofFIG.3may predict a pulley ratio after one second based on a vehicle speed after one second and an APS value after one second, may predict a pulley ratio after two seconds based on a vehicle speed after two seconds and an APS value after two seconds, may predict a pulley ratio after three seconds based on a vehicle speed after three seconds and an APS value after three seconds, may predict a pulley ratio after four seconds based on a vehicle speed after four seconds and an APS value after four seconds, and may predict a pulley ratio after five seconds based on a vehicle speed after five seconds and an APS value after five seconds. Herein, both the vehicle speed and the APS value may be predicted values, and the pulley ratio determined based on the vehicle speed and the APS value may also be a predicted value. In the instant case, it is safe for the algorithm of determining the pulley ratio using the vehicle speed and the APS value to use any scheme which is generally known.

Although a downward condition of the pulley ratio is met at a current time point, when the number of pulley ratios higher than a current pulley ratio above a threshold among the predicted five pulley ratios is plural in number, the controller32may maintain the current pulley ratio, for example, one second (see reference numeral410). Thereafter, the controller32may predict a pulley ratio for each future time point again at a time point when one second has passed and may control a pulley of the continuously variable transmission based on the predicted pulley ratio.

FIG.5is a drawing illustrating an operation of a controller provided in an apparatus of controlling a pulley of a continuously variable transmission according to various exemplary embodiments of the present invention.

As shown inFIG.5, as pulley ratios for every future time points, for example, a controller32ofFIG.3may predict a pulley ratio after one second based on a vehicle speed after one second and an APS value after one second, may predict a pulley ratio after two seconds based on a vehicle speed after two seconds and an APS value after two seconds, may predict a pulley ratio after three seconds based on a vehicle speed after three seconds and an APS value after three seconds, may predict a pulley ratio after four seconds based on a vehicle speed after four seconds and an APS value after four seconds, and may predict a pulley ratio after five seconds based on a vehicle speed after five seconds and an APS value after five seconds.

In a state where the current pulley ratio is maintained because the current pulley ratio is an optimal pulley ratio, when the number of pulley ratios higher than the current pulley ratio above a threshold among the predicted five pulley ratios is plural in number, the controller32may perform upward control of the current pulley ratio (see reference numeral510). In the instant case, the controller32may increase a pulley ratio in proportion to a change rate of the APS value.

Hereinafter, a description will be provided of a process where the controller32learns a deep learning model and predicts a vehicle speed and an APS value for each future time point based on the deep learning model, the learning of which is completed. First of all, a storage31ofFIG.3may store a power map in which a demand power corresponding to a vehicle speed and an APS value is recorded and an energy consumption map of a power source for each gear stage.

FIG.6is a drawing illustrating a deep learning model provided in an apparatus of controlling a pulley of a continuously variable transmission according to various exemplary embodiments of the present invention.

A controller32ofFIG.3may input time series data610for a driving profile prior to a predicted time point to an encoder620of a variational auto-encoder (VAE), may learn a deep learning model of predicting a speed of a vehicle and an APS value based on a low-dimensional variable Z, which is an output of the encoder620, a vehicle speed and an APS value at the predicted time point, which are additionally input, and a driving profile at the predicted time, and may predict the speed of the vehicle and the APS value based on the deep learning model, the learning of which is completed.

Herein, the driving profile prior to the predicted time point is a value measured during a certain time prior to the current time point, which refers to information forming a driving pattern of the vehicle. Such a driving profile may include a gas pedal position (GPP) value, revolutions per minute (RPM), a pulley ratio, a vehicle speed, a gradient of a road, a curvature of the road, a steering angle, a brake pedal position (BPP) value (e.g., brake on/off or brake pressure), a separation distance from a preceding vehicle, a relative speed with the preceding vehicle, information related to traffic lights in front, an APS value, or the like. In the instant case, the driving profile is time series data measured during a certain time.

Furthermore, the driving profile at the predicted time point indicates a value measured at the current time point. In the instant case, the GPP value, the RPM, the pulley ratio, the vehicle speed, the steering angle, the BPP value, and the APS value may be obtained over a vehicle network. The gradient and the curvature of the road may be obtained from a navigation device provided in the vehicle. The relative distance from the preceding vehicle and the relative speed with the preceding vehicle may be obtained from a radar provided in the vehicle. The information related to the traffic lights in front (lighting information) may be obtained from a traffic light controller.

In a process of predicting the vehicle speed and the APS value based on the deep learning model, the learning of which is completed, the controller32may input time series data for a driving profile prior to the predicted time point to the encoder of the VAE, and may input the low-dimensional variable Z, which is the output of the encoder, the vehicle speed and the APS value at the predicted time point, and the driving profile at the predicted time point to a decoder of the VAE.

As shown inFIG.6, the controller32may learn a VAE-based deep learning model of predicting a speed of the vehicle based on the low-dimensional variable Z, which is the output of the encoder, the vehicle speed and the APS value at the predicted time point, which are additionally input, and the driving profile at the predicted time point.

Reference numeral ‘620’ indicates the probabilistic encoder, reference numeral ‘610’ indicates the time series data X during the reference time (Tpast˜Tpresent) prior to the predicted time point (Tpresent), which is learning data for the driving profile, reference numeral ‘660’ indicates the probabilistic decoder, reference numeral ‘640’ indicates the low-dimensional variable Z which is the output of the encoder, reference numeral ‘630’ indicates the vehicle speed and the APS value at the predicted time point, reference numeral ‘650’ indicates the driving profile at the predicted time point, and reference numeral ‘670’ indicates the predicted speed and the predicted APS value of the vehicle in the future. In the instant case, Y′ may be the vehicle speed and the APS value during the reference time (Tpresent˜Tfuture) from the current time point, which may be represented in a form of time series data. Furthermore, μ denotes the average of distribution, and σ denotes the variance of distribution.

The encoder620may have a convolutional neural network (CNN) and a multi layer perceptron network (MLPN). The decoder660may have a multi layer perceptron network (MLPN) and a deconvolutional neural network (DNN).

For reference, the decoder (pθ(x|z)) may be parameterized by a deep neural network having a parameter θ. The decoder (pΦx|z)) may be parameterized by a deep neural network having a parameter Φ. The low-dimensional variable z is defined to embed compression information of data X. The encoder620may map a data space to a potential space. The encoder620and the decoder660may be parameterized using a diagonal Gaussian distribution.

FIG.7is a flowchart illustrating a method for controlling a pulley of a continuously variable transmission according to various exemplary embodiments of the present invention.

First of all, in operation701, a storage31ofFIG.3may store a deep learning model, the learning of which is completed.

In operation702, a controller32ofFIG.3may predict a vehicle speed and an APS value for each future time point based on the deep learning model.

In operation703, the controller32may control a pulley of a continuously variable transmission based on a pulley ratio for each future time point, corresponding to the vehicle speed and the APS value.

FIG.8is a block diagram illustrating a computing system for executing a method for controlling a pulley of a continuously variable transmission according to various exemplary embodiments of the present invention.

Referring toFIG.8, the above-mentioned method for controlling the pulley of the continuously variable transmission according to various exemplary embodiments of the present invention may be implemented by the computing system. A computing system1000may include at least one processor1100, a memory1300, a user interface input device1400, a user interface output device1500, storage1600, and a network interface1700, which are connected to each other via a bus1200.

Thus, the operations of the method or the algorithm described in connection with the exemplary embodiments included herein may be embodied directly in hardware or a software module executed by the processor1100, or in a combination thereof. The software module may reside on a storage medium (that is, the memory1300and/or the storage1600) such as a RAM, a flash memory, a ROM, an EPROM, an EEPROM, a register, a hard disk, an SSD (Solid State Drive), a removable disk, and a CD-ROM. The exemplary storage medium may be coupled to the processor, and the processor may read information out of the storage medium and may record information in the storage medium. Alternatively, the storage medium may be integrated with the processor1100. The processor and the storage medium may reside in an application specific integrated circuit (ASIC). The ASIC may reside within a user terminal. In another case, the processor and the storage medium may reside in the user terminal as separate components.

The apparatus of controlling the pulley of the continuously variable transmission and the method therefore may be provided to predict a vehicle speed and an accelerator position sensor (APS) value for each future time point based on the deep learning model, the learning of which is completed, and control the pulley of the continuously variable transmission based on a pulley ratio corresponding to the predicted vehicle speed and the predicted APS value, thus preventing a reverse control phenomenon of the pulley ratio and preventing a tension of the belt in the continuously variable transmission from being increased.

Hereinabove, although the present invention has been described with reference to exemplary embodiments and the accompanying drawings, the present invention is not limited thereto, but may be variously modified and altered by those skilled in the art to which various exemplary embodiments of the present invention pertains without departing from the spirit and scope of the present invention claimed in the following claims.