KR20120060067A - System for learning driver's propensity to drive of hybrid vehicle and method thereof - Google Patents

Abstract

PURPOSE: A system for learning driver's propensity to drive of hybrid vehicle and a method thereof are provided to improve oscillation performance by obtaining stable output torque and to improve fuel efficiency. CONSTITUTION: A system for learning driver's propensity to drive of hybrid vehicle comprises an acceleration pedal detection part(101), a (ISG)Idle Stop and Go(210), and a hybrid control unit. The acceleration pedal detection part provides information of pushing power and operating frequency of the accelerating pedal to the hybrid control unit. The ISG executes idle stop and reboot of an engine(200) according to control of the hybrid control unit. The hybrid control unit determines driver's propensity to drive of hybrid vehicle by detecting foot effort of the accelerating pedal if driving mode is in operation mode of stagnant section and center of city.

Description

System and method for learning driving tendency of hybrid vehicle {SYSTEM FOR LEARNING DRIVER'S PROPENSITY TO DRIVE OF HYBRID VEHICLE AND METHOD THEREOF}

The present invention relates to a hybrid vehicle, and more particularly, to a driving tendency learning apparatus and method for learning a driver's driving tendency to provide oscillation performance and fuel efficiency improvement without increasing the capacity of a power electronic system. It is about.

As demands for improved fuel economy and tighter emission regulations are increasing, demands for eco-friendly vehicles are increasing, and hybrid vehicles are being provided as a realistic alternative.

The meaning of a hybrid vehicle may be distinguished from a fuel cell vehicle and an electric vehicle. In the present specification, the hybrid vehicle includes a pure electric vehicle and a fuel cell vehicle, and includes one or more batteries, and the energy stored in the battery Refers to a vehicle used as a driving force.

Hybrid cars are powered by engines and motors, and according to the driving situation, ISG (Idle Stop and Go) function, regenerative braking function, and engine and motor optimal operating point control characteristics improve fuel economy and exhaust gas. Provide abatement.

In a hybrid vehicle, the ISG function is one of the key functions to reduce fuel consumption by stopping the engine (idle stop) when the vehicle enters a stopped state by waiting for a traffic light or driving on a congested road.

The release of the idle stop is determined according to the driver's acceleration will, that is, the pedal pedal's degree of pedaling and the electric load condition.

Therefore, a hybrid vehicle capable of driving in EV mode (electric vehicle mode) may cause a difference in fuel consumption rate according to driver's driving tendency (acceleration tendency).

In particular, as the ISG function is frequently executed by frequent accelerator pedal operation during urban operation and congestion road, the engine starts on and off repeatedly, causing deterioration of driving performance and increasing fuel consumption rate according to excessive consumption of starting fuel. Problem occurs that causes fuel economy to fall.

In the conventional hybrid vehicle, in order to overcome this phenomenon, the motor capacity of the power electronic system and the capacity of the battery are increased to solve the method of extending the EV mode (electric vehicle mode) section.

However, due to the characteristics of the hybrid vehicle, electric power is limited by the engine which is the main source of power. Therefore, it cannot be regarded as an infinite energy source. Cause.

The present invention has been proposed to solve the above problems, and an object of the present invention is to learn the driving tendency (acceleration tendency) of the driver so that the performance of the optimized vehicle can be provided without increasing the capacity of the power electronic system. It is to provide oscillation performance and fuel economy improvement at the same time.

According to a feature of the present invention to achieve the above object, a hybrid vehicle having an engine and a motor, comprising: an accelerator pedal detection unit for providing the hybrid controller with the information of the pedal power and the number of times of operation of the accelerator pedal during operation; An ISG for executing idle stops and restarts of engines under control of the hybrid controller; A hybrid controller which determines driving mode and detects driving propensity by detecting accelerator pedal power in driving mode and learns whether oscillation performance priority or fuel efficiency is satisfied according to the determined driving tendency. A driving tendency learning apparatus for a hybrid vehicle is provided.

The hybrid controller may execute SOC management of the battery by using the learned result while learning the driving tendency.

The hybrid controller may determine the driving mode by using the current vehicle speed, the average vehicle speed, and the average moving distance calculated from the information of the vehicle speed and the shift stage.

The hybrid controller may determine the driving tendency by using the average moving distance and the accelerator pedal manipulation frequency as additional information in the pedal pedal effort provided by the accelerator pedal detector.

The hybrid controller may detect the pedal pedal effort by dividing it into heavy tip in (HTI), middle tip in (MTI), and light tip in (LTI).

The hybrid controller can satisfy the oscillation performance through learning to give a weight to the basic engine on-maintenance time if the accelerator pedal effort is an acceleration or higher than MTI or a frequent operation.

The hybrid controller may manage the SOC of the battery by controlling the partial load charging and the regenerative braking charging because a rapid acceleration and braking occurs when the accelerator pedal has a rapid acceleration having a frequent operation of more than MTI or more than necessary.

The hybrid controller can satisfy fuel economy through learning that gives a reduction in basic engine on-maintenance time when the pedal pedal effort is less than LTI.

The hybrid controller drives the learning tendency of the hybrid vehicle, characterized in that the SOC of the battery is managed by idle charging when the pedal pedal effort is less than LTI.

In addition, according to another feature of the invention, the process of determining the driving mode by applying the current vehicle speed, the average vehicle speed, the average travel distance; Determining the driving tendency by detecting the pedaling force of the accelerator pedal when the driving mode is a driving mode of a city and a congestion section; Storing and executing learning that satisfies oscillation performance or learning that satisfies fuel economy first according to the determined driving tendency; There is provided a driving propensity learning method for a hybrid vehicle including a process of executing SOC management of a battery using the driving propensity learning results.

The driving tendency may be determined by applying the average moving distance and the accelerator pedal manipulation frequency as additional information to the pedal pedal effort.

The pedal effort of the accelerator pedal for determining the driving tendency can be detected by dividing it into HTI, MTI, and LTI.

In the determination of the driving tendency, if the pedal pedal effort is MTI or a rapid acceleration with frequent operation, learning may be performed to give a weight to the basic engine on-maintenance time to satisfy the oscillation performance.

If the learning result of the driving tendency satisfies oscillation performance, the SOC of the battery may be managed by partial load charging and regenerative braking charging.

In the determination of the driving tendency, if the pedal speed of the accelerator pedal is less than or equal to the LTI, the learning may be performed to give a saving value to the basic engine on time for satisfactory fuel economy.

If the learning result of the driving tendency satisfies fuel economy, the SOC of the battery may be managed by idle charging.

In addition, according to another feature of the invention, the process of determining whether the driving mode of the city center and congestion section by determining the driving mode; Determining the driving tendency by detecting the pedal effort of the accelerator pedal by HTI, MTI, LTI; Setting the oscillation performance to the first control by learning to give a weight to the basic engine on-maintenance time if the accelerator pedal power is higher than MTI or a rapid acceleration operation with frequent operation; If the pedal effort of the accelerator pedal is a slow acceleration of less than the LTI, the process of setting the fuel economy reduction to the priority control by learning to give a reduction in the basic engine on-maintenance time; Managing the SOC of the battery by partial load charging and regenerative braking charging when the oscillation performance is set to priority control due to a rapid acceleration operation with an accelerator pedal of more than MTI or frequent operation; If the pedal speed of the accelerator pedal is set to control the fuel economy by the slow acceleration of LTI or less, the control method for driving characteristics of a hybrid vehicle is provided.

Thus, according to the embodiment of the present invention, by setting the driving performance of the driver so that the oscillation performance is satisfied first if the rapid acceleration tendency, and the stable fuel torque by setting so that the fuel efficiency improvement is prioritized if the slow acceleration tendency. It can improve oscillation performance and at the same time provide fuel economy.

1 is a view schematically showing a driving tendency learning apparatus of a hybrid vehicle according to an exemplary embodiment of the present invention.
2 is a flowchart illustrating a driving propensity learning procedure of a hybrid vehicle according to an exemplary embodiment of the present invention.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings so that those skilled in the art to which the present invention pertains can easily carry out the embodiments.

The present invention can be embodied in various different forms, and thus the present invention is not limited to the embodiments described herein.

1 is a view schematically showing a driving tendency learning apparatus of a hybrid vehicle according to an exemplary embodiment of the present invention.

Referring to FIG. 1, an embodiment of the present invention includes an accelerator pedal detection unit 101, an engine control unit (ECU) 102, a hybrid control unit 103 (HCU), a power control unit 105 (PCU), and a battery 106. ), BMS (Battery Management System: 107), the engine 200, ISG (Idle Stop and Go: 210), the engine clutch 250, the motor 300, the transmission 400.

The accelerator pedal detection unit 101 detects the information of the pedal power and the number of times of operation of the accelerator pedal operated while driving and provides the information to the HCU 103.

The ECU 102 controls the general operation of the engine 200 in cooperation with the HCU 103 connected to the network, and provides operation state information of the engine 200 to the HCU 103.

The HCU 103 is a top-level controller, which collectively controls the lower controllers connected to the network and collects and analyzes information of the lower controllers to control the overall behavior of the hybrid vehicle.

The HCU 103 calculates the current vehicle speed, the average vehicle speed, and the average moving distance by using the information of the vehicle speed and the shift stage, and applies the HCU 103 to determine whether the current driving mode is a driving mode of a highway or a driving mode of a city and a congested section. To judge.

When the driving mode is determined as the driving mode of the city center and the congestion section, the HCU 103 applies the average travel distance and the accelerator pedal operation frequency as additional information to the pedal power of the accelerator pedal provided by the accelerator pedal detection unit 101 to drive the driver. Determine propensity (acceleration propensity).

The pedal effort can be classified into heavy tip in (HTI), middle tip in (MTI), and light tip in (LTI).

The HCU 103 defines a contradiction (fuel consumption rate vs. power performance) for frequent operation of the accelerator pedal according to the determined driver's driving tendency (acceleration tendency) and determines a learning control strategy by analyzing the objective function, means, and side effects. do.

In the determination of the learning control strategy, the HCU 103 performs, for example, the frequent execution of the ISC function by the frequent accelerator pedal operation (starting on / off of the engine) to increase the fuel consumption of the transient state and to maintain the idle state. This can be disadvantageous in preparation for fuel consumption.

And, the driver of the tendency to operate the accelerator pedal frequently generates a short and frequent acceleration and deceleration state more than necessary, so that the surplus energy generated at this time can be recovered by Part Load charging and regenerative braking charging.

Therefore, by learning the driver's driving tendency (acceleration tendency), if the rapid acceleration tendency is set, the on-hold time of the engine is preferentially set so that the oscillation performance is satisfied first, thereby extending the operation range of the hybrid mode (HEV), In order to improve fuel efficiency, the engine-on maintenance time is reduced, and the operation area of the electric vehicle mode (EV mode) is extended.

If the pedal pedal power is above MTI (Middle Tip In) or more than the rapid acceleration tendency is necessary, the learning time is basically weighted to maintain the hybrid mode (HEV mode). To increase it.

Therefore, the driving propensity (acceleration propensity) having an accelerator pedal of more than MTI or frequent operation is necessary to satisfy the oscillation performance rather than reducing the fuel consumption rate.

In addition, if the accelerator pedal has a slow acceleration tendency of less than LTI (Light Tip In), learning to give a reduction to the engine on-maintenance time, which is basically set, will gradually increase the maintenance time of the electric vehicle mode (EV mode). Make it work.

Therefore, the driving propensity (acceleration propensity) in which the pedal pedal effort is less than or equal to the LTI is preferentially satisfied to reduce fuel consumption rather than oscillation performance.

However, it is possible to set the engine on holding time weighting limit value and set the learning value initialization condition so that the trade off of the excessive fuel consumption and the average idle fuel consumption is possible.

The HCU 103 manages a state of charge (SOC) of the battery 106 through the BMS 107 according to the learning tendency (acceleration tendency).

The SOC management of the battery 106 may be divided into idle charging, partial load charging and regenerative braking charging, and the acceleration and braking may be performed in an operation tendency (acceleration propensity) having an accelerator pedal response of more than MTI or more frequent operation than necessary. Since it is a situation that occurs a lot, actively charge by partial load charging and regenerative braking.

In addition, the driving propensity (acceleration propensity) in which the pedal pedal effort is less than or equal to LTI is used to manage the SOC of the battery 106 through idle charging.

In managing the SOC of the battery 106, the charge / discharge limit value is gradually expanded so that the driving of the hybrid mode (HEV mode) and the electric vehicle mode (EV mode) can be induced to the maximum.

In addition, when the SOC of the battery 106 has a predetermined reference value or less, continuous charging may be provided up to the charge allowable amount.

The PCU 105 includes an inverter and a protection circuit composed of a motor control unit (MCU) and a plurality of power switching elements, and the DCU 105 supplies a DC voltage supplied from the battery 106 according to a control signal applied from the HCU 103. The motor 300 is controlled by converting into a three-phase AC voltage.

The power switching element included in the PCU 105 may be configured of any one of an Insulated Gate Bipolar Transistor (IGBT), a MOSFET, a transistor, and a relay.

In addition, the protection circuit included in the PCU 105 monitors the flow of the driving power, and distributes or blocks the driving power when overvoltage and overcurrent flow into the driving power due to various causes such as a collision, a collision, a lightning strike, and the like of the vehicle. It protects all systems provided in the hybrid vehicle and stably protects the occupants from high pressure.

The battery 106 supplies power to the motor 300 to assist the output of the engine 200 in the HEV mode, and charges the voltage generated by the motor 300 by regenerative braking control.

In addition, power is supplied to the motor 300 in the EV mode, and the regenerative braking control charges the voltage generated by the motor 300 operated as a generator.

In the SOC management of the battery 106, partial load charging, regenerative braking charging, and idle charging are executed according to a management strategy determined by the driving tendency (acceleration tendency) to keep the SOC state stable.

The BMS 107 detects and controls the state of charge by comprehensively detecting information such as voltage, current, and temperature of the battery 106, and controls the amount of charge / discharge current of the battery 106 to be over-discharged below a threshold voltage or above a threshold voltage. Do not overcharge.

The BMS 107 controls the main relay for controlling the output of the battery 106 on or off according to a control signal required by the HCU 103.

The engine 200 is driven and controlled to an optimal driving point according to the control of the ECU 102.

The ISG 210 executes idle stop and restart of the engine 200 under the control of the HCU 103.

The engine clutch 250 is disposed between the engine 200 and the motor 300, and is operated under the control of the HCU 103 to control power transmission between the engine 200 and the motor 300.

The motor 300 is driven by a three-phase AC voltage supplied through the PCU 105 to support the output torque of the engine 200, and is operated as a generator when there is excess torque at the output of the engine 200 or when braking. .

The transmission 400 adjusts the transmission ratio according to the control of the HCU 103, and distributes the output torques applied through the clutch 250 according to the driving mode to the transmission ratio to the driving wheels so that the vehicle can be driven. do.

The transmission 400 may be applied to an automatic transmission or a continuously variable transmission.

Since a typical operation in the hybrid vehicle according to the present invention including the above functions is performed in the same or similar manner as the conventional hybrid vehicle, a detailed description thereof will be omitted.

Since the present invention is to enable the driving performance (acceleration propensity) of the driver to be opposed to each other, the oscillation performance and fuel economy improvement can be provided, and thus only the operation thereof will be described in detail.

2 is a flowchart illustrating a driving propensity learning procedure of a hybrid vehicle according to an exemplary embodiment of the present invention.

In the state in which the hybrid vehicle to which the present invention is applied, the HCU 103 calculates the current vehicle speed, the average vehicle speed, and the average moving distance by using information of the vehicle speed and the shift stage, and applies the current to the driving mode of the highway. It is determined whether the mode is the driving mode of the city center and the congestion section (S101).

In the determination of S101, if it is determined that the driving mode is the driving mode of the city center and the congestion section, the HCU 103 applies the average moving distance and the accelerator pedal operation frequency as additional information to the pedal power of the accelerator pedal provided by the accelerator pedal detection unit 101. The driver's driving propensity (acceleration propensity) is determined (S102).

The pedal effort of the accelerator pedal may be detected by dividing it into a heavy tip in (HTI), a middle tip in (MTI), and a light tip in (LTI).

Subsequently, the HCU 103 analyzes the driver's driving tendency from the pedaling power of the accelerator pedal to determine whether it is a rapid acceleration having a MTI or more or more frequent operations (S103).

In the determination of S103, when the HCU 103 analyzes at a rapid acceleration having a frequent operation of more than MTI or more than necessary, the HCU 103 executes learning that weights the engine on holding time which is basically set to maintain driving in the hybrid mode (HEV mode). Time is gradually increased (S104).

The limit of the maximum value is set for the learning which can increase the driving holding time of the hybrid mode (HEV mode) (S105).

Thereafter, the HCU 103 determines the SOC management of the battery 106 according to the learned driving tendency, so that rapid acceleration and braking occur a lot so that partial load charging and regenerative braking can be executed preferentially. Active charging is performed (S106).

Thereafter, it is determined whether the SOC of the battery 106 is stabilized (S107). If it is not stable, the process returns to the process of S101, and the above-described process is repeated. If the SOC of the battery 106 is stabilized, the management of the SOC is changed. Set and limit the maximum value and the minimum value that can be charged and discharged, and then stores the learning value (S108) (S109).

Therefore, the driving propensity (acceleration propensity) of which the pedal pedal is more than the MTI or the frequent operation is required to satisfy the oscillation performance rather than reducing the fuel consumption rate.

In addition, in the determination of S103, when the HCU 103 analyzes the acceleration pedal pedal force at a slow acceleration of less than or equal to LTI, the HCU 103 executes a learning that gives a saving value to the engine on-maintenance time that is basically set, thereby driving in the EV mode. In order to gradually increase the holding time (S110).

Then, the minimum limit is set for learning that can increase the running time of the electric vehicle mode (EV mode) (S111).

Subsequently, the HCU 103 determines the SOC management of the battery 106 according to the learning propensity to learn, and manages the SOC of the battery 106 with idle charging since the accelerator pedal has a driving propensity less than or equal to LTI. In step 112, the charging / discharging limit is gradually extended to manage the electric vehicle mode (EV mode).

Thereafter, it is determined whether the SOC of the battery 106 is stabilized (S107). If it is not stable, the process returns to the process of S101, and the above-described process is repeated. If the SOC of the battery 106 is stabilized, the management of the SOC is changed. Set and limit the maximum value and the minimum value that can be charged and discharged, and then stores the learning value (S108) (S109).

Therefore, the driving propensity (acceleration propensity) of which the pedal pedal is less than or equal to the LTI can satisfy the fuel consumption rate reduction rather than the oscillation performance.

However, it is possible to set the engine on holding time weighting limit value and set the learning value initialization condition so that the trade off of the excessive fuel consumption and the average idle fuel consumption is possible.

While the present invention has been particularly shown and described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments, , Additions, deletions, and so on, other embodiments may be easily suggested, but this is also included in the spirit of the present invention.

101: accelerator pedal detection unit 103: HCU
106: battery 200: engine
210: ISG

Claims (17)

In a hybrid vehicle having an engine and a motor,
An accelerator pedal detection unit providing information on the pedaling force and the number of operation of the accelerator pedal operated during operation;
An ISG for executing idle stops and restarts of engines under control of the hybrid controller;
A hybrid controller which determines a driving mode and detects driving propensity by detecting the pedaling force of the accelerator pedal in the driving mode of the city center and the congestion section, and stores whether the oscillation performance priority is satisfactory or the fuel saving priority is satisfied according to the determined driving tendency;
Driving propensity learning device of a hybrid vehicle comprising a. The method of claim 1,
When the hybrid controller learns driving propensity, the driving propensity learning device for a hybrid vehicle, characterized in that to execute SOC management of a battery using the learned result. The method of claim 1,
The hybrid controller is a driving tendency learning apparatus of the hybrid vehicle, characterized in that for determining the driving mode using the current vehicle speed, the average vehicle speed, the average travel distance calculated by the information of the vehicle speed and the gear stage. The method of claim 1,
The hybrid controller is a driving up learning device for a hybrid vehicle, characterized in that the driving tendency is determined by using the average travel distance and the accelerator pedal operation frequency as additional information in response to the accelerator pedal provided by the accelerator pedal detection unit. The method of claim 1,
The hybrid controller detects the driving force of the accelerator pedal by distinguishing and detecting HTI (Heavy Tip In), MTI (Middle Tip In), LTI (Light Tip In). The method of claim 5,
The hybrid controller is a driving tendency learning device of the hybrid vehicle, characterized in that the accelerator pedal satisfies the oscillation performance by learning to give a weight to the basic engine on-maintenance time if the acceleration or acceleration is more than MTI or frequent operation. The method of claim 6,
The hybrid controller is a situation in which a rapid acceleration and braking occurs when the accelerator pedal effort is more than the MTI or more frequent operation than necessary, so that the SOC of the battery is managed by controlling partial load charging and regenerative braking charging. Driving propensity learning device of a hybrid vehicle. The method of claim 5,
The hybrid controller is characterized in that the driving propulsion learning device of the hybrid vehicle, characterized in that it satisfies the fuel economy savings by learning to give a reduction in the basic engine on-maintenance time if the pedal pedal speed is less than LTI. The method of claim 8,
The hybrid controller learns driving propensity of a hybrid vehicle, characterized in that the SOC of the battery is managed by idle charging when the pedal speed of the accelerator pedal is less than LTI. Determining a driving mode by applying a current vehicle speed, an average vehicle speed, and an average moving distance;
Determining the driving tendency by detecting the pedaling force of the accelerator pedal when the driving mode is a driving mode of a city and a congestion section;
Storing and executing learning that satisfies oscillation performance or learning that satisfies fuel economy first according to the determined driving tendency;
Executing SOC management of the battery using the learning result of the driving tendency;
Driving propensity learning method of a hybrid vehicle comprising a. The method of claim 10,
The driving tendency is determined by applying the average moving distance and the accelerator pedal manipulation frequency as additional information to the pedal effort of the accelerator pedal. The method of claim 10,
The driving pedal learning method of a hybrid vehicle, characterized in that the pedaling of the accelerator pedal for determining the driving tendency is detected by dividing it into HTI, MTI, and LTI. The method of claim 10,
In the determination of the driving tendency, the driving tendency learning of the hybrid vehicle, characterized in that if the accelerator pedal power is higher than the MTI or the rapid acceleration with frequent operation, the weighting is applied to the basic engine on-maintenance time to satisfy the oscillation performance. Way. The method of claim 10,
If the learning result of the driving tendency satisfies the oscillation performance, the driving tendency learning method of a hybrid vehicle, characterized in that the SOC of the battery is managed by partial load charging and regenerative braking charging. The method of claim 10,
The driving propensity learning method of a hybrid vehicle, characterized in that the learning to give a reduction in the basic engine on-maintenance time for fuel economy satisfactory if the pedal speed of the accelerator pedal is less than the acceleration in the determination of the driving tendency. The method of claim 10,
If the learning result of the driving tendency satisfies fuel economy, driving tendency learning apparatus of the hybrid vehicle, characterized in that the management of the SOC of the battery by charging the idle. Determining whether the driving mode is the driving mode of the city center and the congestion section;
Determining the driving tendency by detecting the pedal effort of the accelerator pedal by HTI, MTI, LTI;
Setting the oscillation performance to the first control by learning to give a weight to the basic engine on-maintenance time if the accelerator pedal power is higher than MTI or a rapid acceleration operation with frequent operation;
If the pedal effort of the accelerator pedal is a slow acceleration of less than the LTI, the process of setting the fuel economy reduction to the priority control by learning to give a reduction in the basic engine on-maintenance time;
Managing the SOC of the battery by partial load charging and regenerative braking charging when the oscillation performance is set to priority control due to a rapid acceleration operation with an accelerator pedal of more than MTI or frequent operation;
Managing the SOC of the battery by charging the idler when the pedal speed of the accelerator pedal is set to the control of the fuel economy due to the slow acceleration of LTI or less;
Driving propensity learning method of a hybrid vehicle comprising a.

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