KR100569139B1 - Motor assistance control method of hybrid electric vehicle - Google Patents

Abstract

The present invention relates to a motor assist control method of a hybrid electric vehicle that can improve fuel efficiency and driving performance by implementing an optimum motor assistance considering the driver acceleration index, and a motor optimization algorithm in terms of battery balance and fuel economy of a hybrid electric vehicle. The motor optimization algorithm in terms of acceleration performance achieves optimum motor assistance considering driver acceleration index.

Hybrid, electric, vehicle, motor, auxiliary

Description

MOTOR ASSISTANCE CONTROL METHOD OF HYBRID ELECTRIC VEHICLE}

1 is a flowchart illustrating a method of controlling a motor of a hybrid electric vehicle according to an exemplary embodiment of the present invention.

2 and 3 illustrate a signal flow of a fuzzy logic controller according to an embodiment of the present invention.

4 is a diagram showing the configuration of a fuzzyifier module according to an embodiment of the present invention.

FIG. 5 illustrates a fuzzy rule that distinguishes the driver's will in accordance with an embodiment of the present invention. FIG.

6 is a diagram illustrating a configuration of a defuzzifier module according to an embodiment of the present invention.

The present invention relates to a motor assisted control method of a hybrid electric vehicle.

Typically, optimizing motor assistance to minimize fuel consumption in hybrid electric vehicles is one of the very important development goals.

In order to determine the optimal motor assistance amount, a mathematical optimization technique in a specific driving mode is used to find an optimal motor assistance pattern, or in consideration of the transient characteristics of the engine, a fast response is a motor and a steady state response is an engine. Various optimal motor assistance algorithms have been proposed.

When using the above method, the conventional motor assistance algorithms often aim to improve fuel efficiency and may not sufficiently exhibit the acceleration performance of the vehicle.

In addition, the conventional motor assist algorithm is difficult to fully exhibit the acceleration performance of the vehicle to meet the target only to improve fuel efficiency, and algorithms written mainly on the acceleration performance of the vehicle are not easy to balance the battery or to violate fuel efficiency.

In addition, multi-objective optimization is required to optimize these two performance indices (fuel efficiency, acceleration performance) at the same time, but this is a very expensive method, and the user's intuition has to work a lot. .

An object of the present invention is to provide a motor assist control method for a hybrid electric vehicle that can improve fuel efficiency and driving performance by implementing the optimum motor assistance in consideration of the driver acceleration index.

In order to achieve the above object, the present invention provides a motor assisted control method for a hybrid electric vehicle, wherein the driver acceleration through a motor optimization algorithm in terms of battery balance and fuel economy and a motor optimization algorithm in terms of acceleration performance of the hybrid electric vehicle. It is characterized by implementing the optimum motor assistance considering the index.

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. While many specific details, such as the following description and the annexed drawings, are shown to provide a more general understanding of the invention, these specific details are illustrated for the purpose of explanation of the invention and are not meant to limit the invention thereto. And a detailed description of known functions and configurations that may unnecessarily obscure the subject matter of the present invention will be omitted.

1 is a flowchart illustrating a motor assisted control method of a hybrid electric vehicle according to an exemplary embodiment of the present invention.

2 and 3 illustrate a signal flow of a fuzzy logic controller according to an exemplary embodiment of the present invention, and FIG. 2 illustrates a fuzzy logic controller for determining a driver sport index (driver acceleration index). 3 is a diagram illustrating signal conditioning.

4 and 6 are views illustrating the configuration of a fuzzyifier module and a defuzzifier module according to an embodiment of the present invention.

FIG. 5 illustrates a fuzzy rule distinguishing the driver's will according to an exemplary embodiment of the present invention.

An embodiment of the present invention configures a motor optimization algorithm in terms of battery balance and fuel efficiency and a motor optimization algorithm in terms of acceleration performance in order to implement optimal motor assistance in consideration of a driver acceleration index.

First, the motor optimization algorithm in terms of battery balance and fuel economy.

When constructing a driving control algorithm for a hybrid electric vehicle, the control strategy must be configured to maintain the SOC before and after driving.

Therefore, the regenerative braking amount that can be obtained through simulation or test in the object mode is obtained.

Once the regenerative braking amount is found, the optimum motor assistance amount is determined within this value.

Then, the determined optimal motor assistance amount is obtained in the form of map data according to the vehicle speed and the driver's accelerator pedal opening degree (S110 and S112).

The following is an algorithm for additional motor assist torque determination in terms of acceleration performance, which is the subject of the present invention.

First, an additional torque amount of the motor is determined to obtain additional acceleration force in a situation where the driver's acceleration will be strong (S114).

The additional torque of the motor is usually determined by the rated maximum torque of the motor, but must be tuned by vehicle testing.

In order to determine the driver's willingness to receive the following input (S120).

a) accelerator pedal opening

b) engine speed

c) vehicle speed

d) brake switch

A fuzzy logic controller (or fuzzy controller) as shown in FIG. 2 is configured to determine the driver acceleration index from the input to the accelerator pedal opening degree.

A driver acceleration index (0, 0.5, 1) is determined from the purge controller (S122).

Then, the final amount of motor assistance is determined by multiplying the determined additional torque of the motor by the driver acceleration index (S124).

A fuzzy controller is used to represent the four inputs as one driver acceleration index.

The fuzzy controller consists of a fuzzifier and a defuzzifier using four inputs.

The four signals input to the purge controller are accelerator pedal opening degree (DD_IP), engine speed (N_Eng_IP), vehicle speed (VS_IP), and brake switch (Brake_IP) signals.

That is, the fuzzy controller is composed of a fuzzy and defuzzifier using four inputs of the accelerator pedal opening degree DD_IP, the engine speed N_Eng_IP, the vehicle speed VS_IP, and the brake switch Brake_IP.

For example, in the case of the accelerator pedal opening degree DD_IP, the acceleration pedal opening degree DD_IP is determined to be low when it is smaller than 0.1 and high when it is larger than 0.2.

Four inputs for determining the driver's will are digitized to two levels as shown in FIG. 4, and a fuzzy rule for fuzzy is shown in FIG. 5.

The driver's will is divided into economy, normal, and sport according to the acceleration will by the fuzzy rule shown in FIG. 5.

Each fuzzy rule is as follows.

First, the economy fuzzy rule consists of the following conditions.

IF accelerator pedal opening = Low

AND

Vehicle speed change = Low

AND

Acceleration pedal opening change = Low

AND

Engine speed = Low

THEN Driver Acceleration Index = Economy (0.0)

Normal purge rules are made under the following conditions.

IF NOT Driver Acceleration Index = Economy

AND

NOT Driver Acceleration Index = Sport

THEN Driver Acceleration Index = Normal (0.5)

The sports fuzzy rule consists of the following conditions.

IF accelerator pedal opening = High

AND

Vehicle speed change = High

OR

Engine speed = High

OR

Acceleration pedal opening amount = High

THEN Driver Acceleration Index = Sport (1.0)

As described above, the driver's will determined by Economy, Normal, and Sport is represented by driver acceleration indices of 0, 0.5, and 1, respectively, as shown in FIG.

As described above, the motor assisted control method of the hybrid electric vehicle according to the present invention proposes a motor assisted optimization method in terms of fuel consumption, and can develop a driver acceleration index that can reflect the driver's acceleration will while using the optimization map as it is. It has an effect.

Claims (7)

In a motor assist control method of a hybrid electric vehicle that implements the optimum motor assistance in consideration of the driver acceleration index through a motor optimization algorithm in terms of battery balance and fuel economy and a motor optimization algorithm in terms of acceleration performance, Motor optimization algorithm in terms of battery balance of hybrid electric vehicles, Obtaining a regenerative braking amount to maintain a battery charge amount SOC before and after the hybrid electric vehicle is driven; Determining an optimum motor assistance amount within this value when the regenerative braking amount is obtained; Obtaining the determined optimal motor assistance amount in the form of map data according to the vehicle speed and the accelerator pedal opening degree, The motor optimization algorithm in terms of acceleration performance Receiving an accelerator pedal opening degree, an engine speed, a vehicle speed, and a brake switch input to determine an acceleration will of the driver; Determining a driver acceleration index from an input for an accelerator pedal opening degree; Calculating an additional torque amount of the motor to obtain an additional acceleration force according to the driver's acceleration will; And determining a final amount of motor assistance by multiplying the calculated amount of additional torque of the motor by the driver acceleration index. delete delete The method of claim 1, wherein the driver acceleration index is determined through a fuzzy rule set in a fuzzy logic controller according to four input conditions of an accelerator pedal opening degree DD_IP, an engine speed N_Eng_IP, a vehicle speed VS_IP, and a brake switch Brake_IP. A motor assisted control method for a hybrid electric vehicle, characterized in that for determining. delete delete The method of claim 4, wherein the driver's intention is divided into economy, normal, and sport according to the acceleration will by the fuzzy rule. 5. .

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