Patent Description:
Wheel loaders are widely used at construction sites to excavate aggregate such as dirt, sand, gravel and the like and load it into dump truck. Since the aggregate may be inhomogeneous loose soil or a somewhat compact material, the excavation work for digging the aggregate may be easy or difficult depending on the type of the aggregate. Further, load applied to the wheel loader may vary depending on the aggregate, which may result in tire slip. In particular, when the autonomous wheel loader performs the autonomous excavation work, the tire slip may occur thereby reducing the tire life and deteriorating productivity.

<CIT> provides a method and system for controlling a vehicle comprises a torque detector for detecting a first torque level and a second torque level applied to at least one wheel of the vehicle. <CIT> provides a method for controlling loading material to a bucket of a work machine from a stack of material. <CIT> provides a method of controlling a wheel loader, including signals representing a state of work currently performed by the wheel loader received from sensors installed in the wheel loader. Document <CIT> discloses another example of a working machine with a tire slip reduction system.

Example embodiments provide a method of controlling a wheel loader capable of performing an autonomous excavation function to improve fuel efficiency and productivity.

Example embodiments provide a control system of a wheel loader for performing the method.

According to the present invention, in a method of controlling a wheel loader, the wheel loader is moved forwards such that a bucket penetrates into an aggregate to perform an excavation work, as defined by independent claim <NUM>. Signals able to be used to determine tire slip of the wheel loader are obtained during the excavation work. Prediction algorithms obtained through training are performed to determine whether or not the tire slip occurs. In case of the tire slip, an engine speed is decreased and the bucket is lifted to remove the tire slip until after a point at which a tire tractive force and a bucket breakout force are equal to each other in case of the tire slip. The bucket is moved along a predetermined autonomous excavation trajectory when the tire slip is removed. The performing the prediction algorithms comprises performing algorithms trained using data on a first group of signals for the tire tractive force and a second group of signals for the bucket breakout force as learning data for the tire slip determination.

In the present invention, obtaining the signals able to be used to determine the tire slip of the wheel loader includes obtaining a first group of signals required for calculating a tractive force of the tire, and obtaining a second group of signals required for calculating a breakout force of the bucket.

In the present invention, the first group of signals includes an engine rotational speed signal, a turbine rotational speed signal of a torque converter, a speed step signal of a transmission, a vehicle speed signal and a wheel rotational speed signal, and the second group of signals may include a stroke signal of a boom cylinder, a stroke signal of a bucket cylinder and a pressure signal of the boom cylinder.

In example embodiments, the wheel rotational speed signal may be obtained from an encoder installed in the tire.

In example embodiments, moving the wheel loader forwards to perform the excavation work may include increasing an engine speed without an operator stepping on an acceleration pedal.

In example embodiments, lifting the bucket when the tire slip occurs may include increasing a stroke of a boom cylinder.

In example embodiments, the method may further include determining a time when the bucket penetrates into the aggregate and a speed step of a transmission is shifted down from second step to first step as an entry time of the excavation work.

In example embodiments, the method may further include terminating the autonomous excavation work mode when an angle of the bucket is at the maximum crowd state.

According to the present invention, a control system for a wheel loader includes a plurality of sensors installed respective in an engine and a work apparatus and a travel apparatus driven by the engine to detect signals able to be used to determine tire slip of the wheel loader, a control apparatus configured to output a control signal for performing an autonomous excavation work mode of the wheel loader, perform prediction algorithms obtained through training on the signals received from the sensors to determine whether or not the tire slip occurs and output first and second tire slip removal control signals so as to remove the tire slip within a desired value, an engine control device configured to decrease an engine rotational speed according to the first tire slip removal control signal, and a work control device configured to lift a bucket of the wheel loader according to the second tire slip removal control signal, wherein the engine rotational speed is decreased and the bucket (<NUM>) is lifted until after a point at which a tire tractive force and a bucket breakout force are equal to each other, in case of the tire slip, wherein the control apparatus comprises a data receiver configured to receive the signals from the sensors, a determiner configured to perform neural network algorithms on the signals to determine whether or not the tire slip occurs, and an output portion configured to output the first and second tire slip removal control signals to the engine control device and the work control device respectively, as defined by independent claim <NUM>.

In the present invention, the sensors includes a first group of sensors for detecting signals required for calculating a tractive force of a tire and a second group of sensors for detecting signals required for calculating a breakout force of the bucket.

In the present invention, the first group of sensors includes at least one of an engine speed sensor, a turbine rotational speed sensor of a torque converter, a sensor for detecting speed step of a transmission, a vehicle speed sensor and a wheel speed detection sensor, and a second group of sensors may include at least one of a boom angle sensor, a bucket angle sensor and a boom cylinder pressure sensor.

In example embodiments, the wheel speed detection sensor may include an encoder installed in the tire.

In example embodiments, the control apparatus may output an acceleration pedal output signal having a predetermined increase ratio value to the engine control device when the autonomous excavation work mode is entered, to increase the engine rotational speed.

In example embodiments, the first tire slip removal control signal may include an acceleration pedal output signal having a predetermined decrease ratio value.

In example embodiments, the second tire slip removal control signal may include a pilot pressure signal for increasing a stroke of a boom cylinder.

In example embodiments, the control apparatus may determine a time when the bucket penetrates into an aggregate and speed step of a transmission is shifted down from second step to first step as an entry time of the autonomous excavation work mode.

In example embodiments, the control apparatus may determine a time when an angle of the bucket is at the maximum crowd state as an end point of the autonomous excavation work mode.

According to example embodiments, a wheel loader may be controlled to perform an autonomous excavation work without an operator pressing an acceleration pedal when entering an autonomous excavation work mode. In addition, tire slip of the wheel loader may be determined by using prediction algorithm obtained through training such as neural network algorithms on signals received from sensors installed on the wheel loader, and when it is determined that the tire slip occurs, an engine speed may be decreased and the bucket may be lifted to remove the tire slip within a desired range.

Artificial neural network algorithms for a digging force and a tractive force that change according to the type and state of the aggregate may be used to control real-time equipment to thereby implement full autonomous excavation function. Thus, tire product life may be prevented from shortening due to excessive slippage of tires and optimized excavation trajectory control may be performed regardless of the operator's skill to thereby improve productivity.

Example embodiments will be more clearly understood from the following detailed description taken in conjunction with the accompanying drawings.

Various example embodiments will be described more fully hereinafter with reference to the accompanying drawings, in which example embodiments are shown. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to example embodiments set forth herein. Rather, these example embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of example embodiments to those skilled in the art. In the drawings, the sizes and relative sizes of components or elements may be exaggerated for clarity.

It will be understood that when an element or layer is referred to as being "on," "connected to" or "coupled to" another element or layer, it can be directly on, connected or coupled to the other element or layer or intervening elements or layers may be present. In contrast, when an element or layer is referred to as being "directly on," "directly connected to" or "directly coupled to" another element or layer, there are no intervening elements or layers present.

It will be understood that, although the terms first, second, third, etc. may be used herein to describe various elements, components, regions, layers and/or sections, these elements, components, regions, layers and/or sections should not be limited by these terms. Thus, a first element, component, region, layer or section discussed below could be termed a second element, component, region, layer or section without departing from the teachings of example embodiments.

The terminology used herein is for the purpose of describing particular example embodiments only and is not intended to be limiting of example embodiments.

<FIG> is a side view illustrating a wheel loader in accordance with example embodiments. <FIG> is a block diagram illustrating a system for controlling the wheel loader in <FIG>.

Referring to <FIG> and <FIG>, a wheel loader <NUM> may include a front body <NUM> and a rear body <NUM> connected to each other. The front body <NUM> may include a work apparatus and a front wheel <NUM>. The rear body <NUM> may include a driver cabin <NUM>, an engine bay <NUM> and a rear wheel <NUM>.

The work apparatus may include a boom <NUM> and a bucket <NUM>. The boom <NUM> may be freely pivotally attached to the front body <NUM>, and the bucket <NUM> may be freely pivotally attached to an end portion of the boom <NUM>. The boom <NUM> may be coupled to the front body <NUM> by a pair of boom cylinders <NUM>, and the boom <NUM> may be pivoted upwardly and downwardly by expansion and contraction of the boom cylinders <NUM>. A tilt arm <NUM> may be freely rotatably supported on the boom <NUM>, almost at its central portion. One end portion of the tilt arm <NUM> may be coupled to the front body <NUM> by a pair of bucket cylinders <NUM> and another end portion of the tilt arm <NUM> may be coupled to the bucket <NUM> by a tilt rod, so that the bucket <NUM> may pivot (crowd and dump) as the bucket cylinder <NUM> expands and contracts.

The front body <NUM> and the rear body <NUM> may be rotatably connected to each other through a center pin <NUM> so that the front body <NUM> may swing side to side with respect to the rear body <NUM> by expansion and contraction of a steering cylinder (not illustrated).

A travel apparatus for propelling the wheel loader <NUM> may be mounted at the rear body <NUM>. An engine <NUM> may be provided in the engine bay <NUM> to supply an output power to the travel apparatus. The travel apparatus may include a torque converter <NUM>, a transmission <NUM>, a propeller shaft <NUM>, axles <NUM>, <NUM>, etc. The output power of the engine <NUM> may be transmitted to the front wheel <NUM> and the rear wheel <NUM> through the torque converter <NUM>, the transmission <NUM>, the propeller shaft <NUM> and the axles <NUM> and <NUM>, and thus the wheel loader <NUM> may travels.

In particular, the output power of the engine <NUM> may be transmitted to the transmission <NUM> through the torque converter <NUM>. An input shaft of the torque converter <NUM> may be connected to an output shaft of the engine <NUM>, and an output shaft of the torque converter <NUM> may be connected to the transmission <NUM>. The torque converter <NUM> may be a fluid clutch device including an impeller, a turbine and a stator. The transmission <NUM> may include hydraulic clutches that shift speed steps between first to fourth speeds, and rotation of the output shaft of the torque converter <NUM> may be shifted by the transmission <NUM>. The shifted rotation may be transmitted to the front wheel <NUM> and the rear wheel <NUM> through the propeller shaft <NUM> and the axles <NUM> and <NUM> and thus the wheel loader may travel.

The torque converter <NUM> may have a function to increase an output torque with respect to an input torque, i.e., a function to make the torque ratio <NUM> or greater. The torque ratio may decrease with an increase in the torque converter speed ratio e (= Nt/Ni), which is a ratio of the number of rotations Nt of the output shaft of the torque converter <NUM> to the number of rotations Ni of the input shaft of the torque converter <NUM>. For example, if travel load is increased while the vehicle is in motion in a state where the engine speed is constant, the number of rotations of the output shaft of the torque converter <NUM>, i.e., the vehicle speed may be decreased. At this time, the torque ratio may be increased and thus the vehicle may be allowed to travel with a greater travel driving force (traction force).

The transmission <NUM> may include a forward hydraulic clutch for forward movement, a reverse hydraulic clutch for reverse movement, and first to fourth hydraulic clutches for the first to the fourth speeds. The hydraulic clutches may be each engaged or released by pressure oil (clutch pressure) supplied via a transmission control unit (TCU) <NUM>. The hydraulic clutches may be engaged when the clutch pressure supplied to the hydraulic clutches is increased, while the hydraulic clutches may be released when the clutch pressure is decreased.

When travel load is decreased and the torque converter speed ratio e is increased to be equal to or greater than a predetermined value eu, a speed step may be shifted up by one step. On the other hand, when travel load is increased and the torque converter speed ratio e is decreased to be equal to or less than a predetermined value ed, the speed step may be shifted down by one step.

A variable capacity hydraulic pump <NUM> for supplying a pressurized hydraulic fluid to the boom cylinder <NUM> and the bucket cylinder <NUM> may be mounted at the rear body <NUM>. The variable capacity hydraulic pump <NUM> may be driven using at least a portion of the power outputted from the engine <NUM>. For example, the output power of the engine <NUM> may drive the hydraulic pump <NUM> for the work apparatus and a hydraulic pump (not illustrated) for the steering cylinder via a power take-off (PTO) such as a gear train <NUM>.

A pump control device (EPOS, Electronic Power Optimizing System) may be connected to the variable capacity hydraulic pump <NUM>, and the hydraulic fluid discharged from the variable capacity hydraulic pump <NUM> may be controlled by the pump control device. A main control valve (MCV) including a boom control valve <NUM> and a bucket control valve <NUM> may be installed on a hydraulic circuit of the hydraulic pump <NUM>. The hydraulic fluid discharged from the hydraulic pump <NUM> may be supplied to the boom cylinder <NUM> and the bucket cylinder <NUM> through the boom control valve <NUM> and the bucket control valve installed in a hydraulic line <NUM> respectively. The main control valve (MCV) may supply the hydraulic fluid discharged from the hydraulic pump <NUM> to the boom cylinder <NUM> and the bucket cylinder <NUM> according to a pilot pressure in proportion to an operation rate of an operating lever. Thus, the boom <NUM> and the bucket <NUM> may be driven by the pressure of the hydraulic fluid discharged from the hydraulic pump <NUM>.

A maneuvering device may be provided within the driver cabin <NUM>. The maneuvering device may include an acceleration pedal <NUM>, a brake pedal, an FNR travel lever, the operating levers for operating the cylinders such as the boom cylinder <NUM> and the bucket cylinder <NUM>, etc..

As mentioned above, the wheel loader <NUM> may include a traveling operating system for driving the travel apparatus via the PTO and a hydraulic operating system for driving the work apparatus such as the boom <NUM> and the bucket <NUM> using the output power of the engine <NUM>.

Further, a control apparatus <NUM> for the wheel loader <NUM> such as a portion of a vehicle control unit (VCU) or a separate control unit may be mounted in the rear body <NUM>. The control apparatus <NUM> may include an arithmetic processing unit having a CPU which executes a program, a storage device such as a memory, other peripheral circuit, and the like.

The control apparatus <NUM> may receive signals from various sensors (detectors) which are installed in the wheel loader <NUM>. For example, the control apparatus <NUM> may be connected to an engine speed sensor <NUM> for detecting a rotational speed of the engine, an acceleration pedal detection sensor <NUM> for detecting an operation amount of the acceleration pedal <NUM>, a brake pedal detection sensor for detecting an operation amount of the brake pedal, and an FNR travel lever position sensor for detecting a manipulation position of the FNR travel lever, for example, forward (F), neutral (N) and reverse (R). Additionally, the control apparatus <NUM> may receive an engine rotational speed signal and an acceleration pedal signal from an engine control unit (ECU) connected to the engine speed sensor <NUM> and the acceleration pedal detection sensor <NUM>. Further, the control apparatus <NUM> may receive a speed step signal of the transmission through the transmission control unit (TCU) <NUM>.

In addition, the control apparatus <NUM> may be connected to a turbine rotational speed sensor <NUM> for detecting a rotational speed of the turbine of the torque converter <NUM>, a vehicle speed sensor <NUM> for detecting a rotational speed of an output shaft of the transmission <NUM>, i.e., and a wheel speed detection sensors <NUM>, <NUM> for detecting a wheel speed. The wheel speed detection sensors <NUM>, <NUM> may include an encoder installed in a tire. Alternatively, the control apparatus <NUM> may be connected to a GPS receiver installed in the wheel loader, to receive a current speed of the vehicle.

Further, the control apparatus <NUM> may be connected to a pressure sensor <NUM> installed in the hydraulic line <NUM> in front end of the main control valve (MCV) to detect a pressure of the hydraulic fluid discharged from the hydraulic pump <NUM>, and a boom cylinder pressure sensor <NUM> for detecting a cylinder head pressure at a head of the boom cylinder <NUM>. Furthermore, the control apparatus <NUM> may be connected to a boom angle sensor <NUM> for detecting a rotational angle of the boom <NUM> and a bucket angle sensor <NUM> for detecting a rotational angle of the bucket <NUM>.

As illustrated in <FIG> and <FIG>, the signals detected by the sensors may be inputted into the control apparatus <NUM>. As mentioned later, the control apparatus <NUM> may select one or more signals of the signals received from the sensors installed in the wheel loader <NUM>, perform prediction algorithms obtained through training such as neural network algorithms to determine whether or not tire slip occurs. Further, the control apparatus <NUM> may output a control signal to the engine control unit (ECU), the transmission control unit (TCU) <NUM>, and the pump control device (EPOS), etc, to selectively control the travel apparatus and the work apparatus of the wheel loader <NUM> based on the occurrence of the tire slip.

Hereinafter, the control apparatus for controlling the wheel loader will be explained.

<FIG> is a block diagram illustrating a control system for a wheel loader in accordance with example embodiments. <FIG> is a block diagram illustrating a control apparatus in <FIG>. <FIG> is a view illustrating a neural network circuit in a tire slip determiner in <FIG>. <FIG> is a view illustrating a signal transfer in each layer of the neural network in <FIG>. <FIG> is a graph illustrating a tractive force of a tire according to an acceleration pedal output signal inputted to an engine control unit from the control apparatus in <FIG>. <FIG> is a graph illustrating a height of a buck according to a pilot pressure signal inputted to a work control apparatus from the control apparatus in <FIG>.

Referring to <FIG>, a control system for a wheel loader may include a plurality of sensors, a control apparatus <NUM> for performing an autonomous excavation work mode, a travel apparatus control device and a work apparatus control device.

The sensors may be installed in the engine <NUM>, the work apparatus and the travel apparatus to detect signals representing state information of the wheel loader. In particular, the control system form a wheel loader may include a first group of sensors for detecting signals required for calculating a tractive force of a tire of the wheel loader <NUM> and a second group of sensors for detecting signals required for calculating a breakout (digging) force of a bucket.

For example, the first group of sensors may include the engine speed sensor <NUM>, the turbine rotational speed sensor <NUM>, the sensor for detecting the speed step of the transmission, the vehicle speed sensor <NUM>, the wheel speed detection sensor, etc. The second group of sensors may include the boom angle sensor <NUM>, the bucket angle sensor <NUM>, the boom cylinder pressure sensor <NUM>, etc..

The control apparatus <NUM> may include a data receiver <NUM>, a determiner <NUM> and an output portion <NUM>.

The data receiver <NUM> may receive signals from the sensors. Additionally, the data receiver <NUM> may receive an autonomous excavation work mode selection signal from a selection portion <NUM>. When the autonomous excavation work mode is selected by an operator, the selection portion <NUM> may output the autonomous excavation work mode selection signal to the control apparatus <NUM>. Further, the operator may select detail working conditions of the autonomous excavation work mode through the selection portion <NUM>. The detail working conditions may include an excavation workload, an excavation work speed, an allowable range of tire slip, and the like.

The determiner <NUM> may determine the entry time and end point of the autonomous excavation work mode. The determiner <NUM> may determine a time when the bucket <NUM> penetrates into the aggregate as the entry time of the autonomous excavation work mode. When the bucket <NUM> digs the aggregate and load is applied to the travel apparatus by the reaction force, and the speed step of the transmission <NUM> is shifted down to the first step, it may be determined as the entry time of the autonomous excavation work mode. When the angle of the bucket <NUM> is at the maximum crowd state, it may be determined as the end point of the autonomous excavation work mode.

Additionally, the determiner <NUM> may include neural network circuits that perform neural network algorithms to determine whether or not the tire slip occurs.

As illustrated in <FIG>, the neural network circuit may include multilayer perceptrons having a multi-input layer, a hidden layer and an output layer. Neurons may be arranged in each layer, and the neurons in each layer may be connected by connection weights. Input data may be inputted to the neurons in the input layer and transferred to the output layer though the hidden layer.

Training the neural network algorithm may be a process of tuning the interconnection weights between each nodes in order to minimize an error between an expectation value and an output value of the neural network algorithms for a specific input (actual detected data). For example, back propagation algorithm may be used for training the neural networks. Accordingly, the neural network circuits of the determiner <NUM> may vary the connection weights between the input layer, the hidden layer and the output layer using pre-collected data to provide neural network algorithms as prediction models.

In example embodiments, data obtained from the first group of sensors and the second group of sensors may be accumulated and may be used as learning data. For example, the tire slip moments may be recorded on the basis of the number of the tire revolutions obtained from the external encoder <NUM>, <NUM> installed in the tire, and tire slip occurrence data may be accumulated and used as learning data. The GPS speed of the wheel loader <NUM>, the breakout force of the bucket <NUM>, the acceleration pedal value from the engine control unit <NUM>, etc. may be used as supervised leaning data for the tire slip determination. As an example, although the tire tractive force is greater than a predetermined value and the acceleration pedal signal value does not decrease (not have a negative rate of change), data when the tire tractive force decreases by a predetermined level or more may be used as supervised learning data for the tire slip determination. Additionally, data when the bucket breakout force increases and the number of the tire revolutions increases may be used as supervised learning data for the tire slip determination.

Through supervised learning, the sensor signal weight of the artificial neural network logic may be determined and the tire slip may be determined from the sensor signals.

The output portion <NUM> may output an autonomous excavation work mode control signal for the autonomous excavation work mode and first and second tire slip removal control signals for removing the tire slip within a desired value.

The autonomous excavation work mode control signal may include an acceleration pedal output signal having a predetermined increase ratio value. The output portion <NUM> may output the autonomous excavation work mode control signal to the engine control device <NUM> when the autonomous excavation work mode is entered. The engine control device <NUM> may increase the engine speed by controlling a fuel injector <NUM> according to the autonomous excavation work mode control signal without the operator pressing the acceleration pedal.

The first tire slip removal control signal may include an acceleration pedal output signal having a predetermined decrease ratio value. The output portion <NUM> may output the acceleration pedal output signal to the engine control device <NUM> when the tire slip occurs. The engine control device <NUM> may decrease the engine speed by controlling the fuel injector <NUM> according to the first tire slip removal control signal.

The second tire slip removal control signal may include a pilot pressure signal for increasing a stroke of the boom cylinder <NUM>. The output portion <NUM> may output the pilot pressure signal to the work control apparatus, that is, the boom control valve <NUM> of the main control valve MCV when the tire slip occurs. The boom control valve <NUM> may increase the stroke of the boom cylinder <NUM> according to the pilot pressure signal to increase a height of the bucket <NUM>.

The control apparatus <NUM> may further include a storage portion. The storage portion may store data required for learning in a predictive model and calculation in the neural network algorithm which are performed in the determiner <NUM>, a control map required for determination of the control signal which is performed in the output portion <NUM>, etc..

As illustrated in <FIG>, in response to the acceleration pedal output signal having the predetermined decrease ratio value, the fuel injection amount may be decreased and thus the engine speed may be also decreased. In this case, the tractive force of the tire may be decreased according to the acceleration pedal decrease ratio (%) (point A -> point B). As the tractive force of the tire is decreased the tire slip may be removed.

As illustrated in <FIG>, in response to the pilot pressure signal, the stroke of the boom cylinder <NUM> may be increased, thereby raising the height of the bucket <NUM>. In this case, the height of the bucket <NUM> may be increased according to the stroke increase rate of the boom cylinder <NUM> (point C -> point D). The bucket <NUM> may lift the aggregate upwards and thus the load on the tire may be increased to thereby remove the tire slip.

As described above, the control apparatus <NUM> of the wheel loader may control the wheel loader <NUM> to perform the autonomous excavation work without the operator pressing the acceleration pedal when entering the autonomous excavation work mode. In addition, the control apparatus <NUM> of the wheel loader may determine the tire slip of the wheel loader <NUM> by using prediction algorithm obtained through training such as neural network algorithms on the signals received from the sensors installed on the wheel loader <NUM>, and when it is determined that the tire slip occurs, may decrease the engine speed and lift the bucket <NUM> to remove the tire slip.

The control apparatus <NUM> of the wheel loader may learn data of the tire slip by using the artificial neural network algorithms for the digging force and tractive force that change according to the type and state of the aggregate to adjust the determination weight of the equipment sensor signal and to control the real-time equipment to thereby implement full autonomous excavation function. Thus, tire product life may be prevented from shortening due to excessive slippage of tires and optimized excavation trajectory control may be performed regardless of the operator's skill to thereby improve productivity.

Hereinafter, a method of controlling a wheel loader using the control apparatus in <FIG> will be explained.

<FIG> is a flow chart illustrating a method of controlling a wheel loader in accordance with example embodiments. <FIG> is views illustrating an entry time of an auto-excavation work mode in accordance with example embodiments. <FIG> is graphs illustrating a tractive force of tire and a breakout force of a bucket in accordance with example embodiments.

Referring to <FIG>, <FIG>, <FIG> and <FIG>, first, an entry time of an autonomous excavation work mode may be determined (S <NUM>), and when the autonomous excavation work mode is entered, a wheel loader <NUM> may be accelerated to perform an excavation work (S110).

In example embodiments, in case that an operator selects the autonomous excavation work mode through an selection portion <NUM>, a time when a bucket <NUM> penetrates into an aggregate may be determined as the entry time of the autonomous excavation work mode.

As illustrated in <FIG>, the wheel loader <NUM> may move forwards and start to penetrate into the aggregate M. An angle of a bottom face of the bucket <NUM> may be kept parallel with the ground, and the boom <NUM> may be lowered so that the bottom face of the bucket <NUM> approaches closely to the ground. Then, as illustrated in <FIG>, the bucket <NUM> may dig the aggregate, and then, load is applied to a travel apparatus by the reaction force and the speed step of a transmission <NUM> is shifted down to the first step, it may be determined as the entry time of the autonomous excavation work mode.

Then, when the autonomous excavation work mode is entered, the wheel loader <NUM> may be accelerated to perform an autonomous excavation work.

For example, a control apparatus <NUM> may output an autonomous excavation work mode control signal to an engine control device <NUM> when the autonomous excavation work mode is entered. The autonomous excavation work mode control signal may include an acceleration pedal output signal having a predetermined increase ratio value. The engine control device <NUM> may increase an engine speed by controlling a fuel injector <NUM> according to the autonomous excavation work mode control signal without the operator pressing the acceleration pedal.

Then, during the autonomous excavation work mode, prediction algorithms obtained through training may be performed to determine whether or not tire slip occurs.

In example embodiments, during autonomous excavation work mode, the signals able to be used to determine the tire slip of the wheel loader <NUM> may be obtained. A first group of signals required for calculating a tractive force of a tire of the wheel loader <NUM> and a second group of signals required for calculating a breakout (digging) force of a bucket <NUM>. The first group of signals may include an engine rotational speed signal, a turbine rotational speed signal of a torque converter, a speed step signal of a transmission, a vehicle speed signal and a wheel rotational speed signal. The second group of signals may include a stroke signal of a boom cylinder, a stroke signal of a bucket cylinder and a pressure signal of the boom cylinder.

Data obtained from the first group of signals and the second group of signals may be accumulated to be used as learning data. For example, the tire slip moments obtained from an external encoder <NUM>, <NUM> installed in the tire may be recorded, and tire slip occurrence data may be accumulated to be used as learning data. The GPS speed of the wheel loader <NUM>, the tractive force of the tire, the breakout force of the bucket <NUM>, the acceleration pedal value from the engine control unit <NUM>, etc. may be used as supervised leaning data for the tire slip determination. Through supervised learning, the sensor signal weight of the artificial neural network logic may be determined and the tire slip may be determined from the sensor signals.

Then, when the tire slip occurs, the engine speed of the wheel loader <NUM> may be decreased and the bucket <NUM> may be lifted until the tire slip is removed within a desired value (<NUM>).

For example, the control apparatus <NUM> may output a first tire slip removal control signal to the engine control device <NUM> when the tire slip occurs. The engine control device <NUM> may decrease the engine speed by controlling the fuel injector <NUM> according to the first tire slip removal control signal.

A fuel injection amount may be decreased in response to an acceleration pedal output signal having a predetermined decrease ratio value, and thus, the engine speed may be also decreased. The engine control device <NUM> may increase the engine speed by controlling a fuel injector <NUM> according to the autonomous excavation work mode control signal without the operator pressing the acceleration pedal. In this case, the tractive force of the tire may be decreased according the acceleration pedal decrease ratio and thus the tire slip may be removed.

Additionally, the control apparatus <NUM> may output a second tire slip removal control signal to a work control apparatus, that is, a boom control valve <NUM> of a main control valve MCV when the tire slip occurs. The second tire slip removal control signal may include a pilot pressure signal for increasing a stroke of the boom cylinder <NUM>. The boom control valve <NUM> may increase the stroke of the boom cylinder <NUM> according to the pilot pressure signal to increase a height of the bucket <NUM>.

The stroke of the boom cylinder <NUM> may be increased in response to the pilot pressure signal, thereby increasing the height of the bucket <NUM>. In this case, the height of the bucket <NUM> may be increased according to the stroke increase rate of the boom cylinder <NUM>. The bucket <NUM> may lift the aggregate upwards and thus the load on the tire may be increased to thereby remove the tire slip.

As illustrated in <FIG>, graph G1 represents the tire tractive force and graph G2 represents the bucket digging force, and graphs G3 and G4 represent speeds of left and right wheels. In the tire slip section, the tire tractive force decreases and the GPS speed of the wheel loader <NUM> is constant or decreases, while the tire rotational speed (wheel speed) increases while vibrating rapidly. At this time, if the engine speed is decreased and the buck <NUM> is lifted to increase the bucket digging force, after the point at which the tire tractive force and the bucket dogging force are equal to each other, the tire slippage may disappear as the friction force with the ground increases, and thus, the tractive force may be increased again and the digging operation may be done smoothly.

Then, when the tire slip is removed, the bucket <NUM> may be moved along a predetermined autonomous digging trajectory, and the autonomous excavation work mode may be terminated.

For example, the control apparatus <NUM> may output the autonomous excavation control signal to the engine control device <NUM> and the work control device when the tire slip disappears. Thus, the strokes of the boom cylinder <NUM> and the bucket cylinder <NUM> may be controlled such that the end potion of the bucket <NUM> moves along the predetermined digging trajectory.

Then, when the wheel loader <NUM> moves forward while digging the aggregate and the angle of the bucket <NUM> is at the maximum crowd state, the autonomous excavation work mode may be terminated.

Claim 1:
A method of controlling a wheel loader (<NUM>), comprising:
moving the wheel loader (<NUM>) forwards such that a bucket (<NUM>) penetrates into an aggregate to perform an excavation work;
obtaining signals able to be used to determine tire slip of the wheel loader (<NUM>) during the excavation work;
performing prediction algorithms obtained through training to determine whether or not the tire slip occurs;
decreasing an engine speed and lifting the bucket (<NUM>) to remove the tire slip, until after a point at which a tire tractive force and a bucket breakout force are equal to each other, in case of the tire slip; and
moving the bucket (<NUM>) along a predetermined autonomous excavation trajectory when the tire slip is removed,
wherein performing the prediction algorithms comprises performing algorithms trained using data on a first group of signals for the tire tractive force and a second group of signals for the bucket breakout force as learning data for the tire slip determination,
wherein obtaining the signals able to be used to determine the tire slip of the wheel loader (<NUM>) comprises obtaining the first group of signals required for calculating the tire tractive force, and obtaining the second group of signals required for calculating the bucket breakout force, and
wherein the first group of signals includes at least one of an engine rotational speed signal, a turbine rotational speed signal of a torque converter, a speed step signal of a transmission, a vehicle speed signal and a wheel rotational speed signal, and the second group of signals includes at least one of a stroke signal of a boom cylinder, (<NUM>) a stroke signal of a bucket cylinder (<NUM>) and a pressure signal of the boom cylinder (<NUM>).