KR20140003890A - Power control method and system of hybrid vehicle using driving information - Google Patents

Abstract

The present invention relates to a dynamic power control method and a dynamic power control system of a hybrid vehicle using driving information. More particularly, the dynamic power control method of the present invention includes the steps of: acquiring driving information including at least one of altitude information about speed profile or driving information about a section for a vehicle to travel; calculating a dynamic power value required during driving of the vehicle on the basis of the acquired speed profile; calculating a parameter to perform power distribution of an engine or a motor of the vehicle according to the dynamic power value; and distributing the dynamic power of the vehicle by applying the parameter to Pontryagin's minimum principle (PMP) theory. By the above configuration, the dynamic power control method and the dynamic power control system using driving information of the present invention can control the dynamic power of the hybrid vehicle having an engine and a motor as a dynamic power source easily, by predicting the driving speed of the vehicle in advance. [Reference numerals] (120) Driving information acquisition part; (122) Position information acquisition module; (124) Driving section determining module; (126) Traffic information acquisition module; (128) Driving speed prediction module; (140) Dynamic power calculation part; (160) Parameter calculation part; (162) Braking amount calculation module; (164) Valid discharge amount calculation module; (166) Parameter calculation module; (180) Dynamic power control part

Description

BACKGROUND OF THE INVENTION 1. Field of the Invention [0001] The present invention relates to a hybrid vehicle,

The present invention relates to a method and system for controlling power of a hybrid vehicle using traveling information, and particularly relates to a method and system for controlling the power of a hybrid vehicle by predicting a traveling speed of a section to be traveled and distributing the power of the hybrid vehicle accordingly, To a method and system for controlling power of a hybrid vehicle.

In recent years, environmental and resource problems have become very serious problems, and the development of environmentally friendly vehicles is rapidly spreading in the automobile industry. As a result of these developments, electric vehicles (EV), plug-in hybrid vehicles (PHEV), general hybrid vehicles (HEV) and hybrid vehicles are being studied and marketed for environmentally friendly automobiles.

The hybrid vehicle is a next-generation environmental automobile that significantly reduces the amount of harmful gas emissions compared to conventional vehicles. The hybrid vehicle is equipped with an internal combustion engine and a battery engine of an electric vehicle at the same time, It is possible to convert the gasoline engine and the electric engine automatically in accordance with the road and the surrounding environment while driving the engine by merely combining the advantages of the engine and the electric engine.

In addition, the plug-in hybrid vehicle refers to a vehicle capable of increasing the battery capacity of a general hybrid vehicle so that the hybrid vehicle can be charged by a domestic power source and can travel at a certain distance in an electric vehicle mode.

This eco-friendly automobile has the advantage of being able to mount a large-capacity battery due to the rapid development of battery technology, thereby reducing the running cost of the vehicle by applying it to a conventional hybrid vehicle or a new power transmission structure vehicle.

However, in spite of these advantages, there is a problem that it is difficult to efficiently manage the energy of each power source as a single vehicle uses the engine and the battery as a power source.

In order to solve the problems of the prior art as described above, the present invention provides a method and system for controlling power of a hybrid vehicle using travel information that can easily perform power control of an engine and a motor of a vehicle using travel information of a hybrid vehicle .

According to another aspect of the present invention, there is provided a method of controlling power of a hybrid vehicle using traveling information according to another embodiment of the present invention. The method includes: determining a traveling speed of the vehicle, Acquiring information; Calculating a power value required for driving the vehicle based on the acquired speed profile; Calculating a parameter for performing power distribution of the motor or the engine of the vehicle according to the power value; And applying the parameter to a PMP (Pontryagin's Minimum Principle) theory to distribute the power of the vehicle.

More preferably, receiving the destination information to which the vehicle intends to arrive and obtaining current position information of the vehicle by receiving GPS (Global Positioning System) information; Determining a traveling section in which the vehicle travels based on current position information of the vehicle and the destination information; Obtaining at least one traffic information occurring in the traveling section; And estimating a traveling speed of the vehicle in the traveling section according to a predetermined period based on the at least one traffic information.

Particularly, it may include a process of predicting a traveling speed of a vehicle that calculates a traveling speed according to a traveling section based on a dynamic programming technique.

More preferably, a step of checking a stop state or a running state of the vehicle according to the traffic information acquired in the travel section; And obtaining an initial starting speed and a terminating speed of the vehicle in the traveling section.

More preferably, a look-up table including a weight for the acceleration or deceleration of the vehicle and a weight for the running time of the vehicle is formed according to the average speed of the traveling section, the cruising speed, and the traffic volume per unit time And estimating a traveling speed of the vehicle including the traveling speed of the vehicle.

In particular, the information may include GPS information including at least one of a current position of the vehicle, a mileage, an acceleration, a deceleration, and a ground slope of the road.

In particular, it may include traffic information including at least one of the number of traffic lights existing in the travel section, the distance between the traffic lights, the signal period, the limited speed per section, and the average speed per section.

Calculating a braking amount of the vehicle from the running information; Calculating an effective discharge amount for the motor of the vehicle through a vector analysis on the calculated braking amount; And calculating a parameter for power control of the vehicle from the calculated effective discharge amount.

According to an aspect of the present invention, there is provided a system for controlling a hybrid vehicle using traveling information according to an embodiment of the present invention. The system includes at least one of a speed profile of a section to be traveled by the vehicle, A driving information acquiring unit for acquiring information; A power operation unit for calculating a power value required for driving the vehicle based on the obtained speed profile; A parameter calculator for calculating a parameter for performing power distribution of the motor or the engine of the vehicle according to the power value; And a power control unit for distributing the power of the vehicle by applying the parameter to a PMP (Pontryagin's Minimum Principle) theory.

More preferably, the location information acquisition module receives destination information to which the vehicle desires to arrive and receives current position information of the vehicle by receiving GPS (Global Positioning System) information; A traveling section determining module that determines a traveling section on which the vehicle travels based on current position information of the vehicle and the destination information; A traffic information acquisition module for acquiring at least one traffic information generated in the traveling section; And a running speed prediction module for predicting a running speed of the vehicle in the running section based on the acquired at least one traffic information according to a predetermined period.

In particular, it may include a traveling speed prediction module that calculates a traveling speed according to a traveling section based on a dynamic programming technique.

More preferably, it may include a traveling speed prediction module for confirming a vehicle's stop state or running state according to the traffic information acquired in the traveling section, and acquiring the initial starting speed and the ending section speed of the vehicle in the traveling section have.

In particular, in the case of a vehicle traveling in a form of a look-up table including a weight for acceleration or deceleration of the vehicle and a weight for the traveling time of the vehicle according to an average speed of the traveling section, a cruising speed, Speed prediction module.

In particular, the information may include GPS information including at least one of a current position of the vehicle, a mileage, an acceleration, a deceleration, and a ground slope of the road.

In particular, it may include traffic information including at least one of the number of traffic lights existing in the travel section, the distance between the traffic lights, the signal period, the limited speed per section, and the average speed per section.

More preferably, a braking amount calculating module for calculating a braking amount of the vehicle from the running information; An effective discharge amount calculation module for calculating an effective discharge amount of the vehicle with respect to the motor through vector analysis with respect to the calculated braking amount; And a parameter operation module for calculating a parameter for power control of the vehicle from the calculated effective discharge amount.

A method and system for controlling power of a hybrid vehicle using travel information of the present invention receives a final destination from a driver through vehicle navigation and confirms a travel section and then determines whether or not the travel section There is an effect that the traveling speed of the vehicle can be predicted in advance.

Further, the method and system for controlling the power of the hybrid vehicle using the running information of the present invention have the effect of easily controlling the power of the hybrid vehicle having the engine and the motor as the power source, by predicting the running speed of the vehicle in advance.

In addition, the method and system for controlling the power of the hybrid vehicle using the running information of the present invention have the effect of improving the fuel efficiency of the vehicle and thus improving the satisfaction of the driver as the power of the hybrid vehicle is easily controlled .

1 is a block diagram of a power control system for a hybrid vehicle using travel information according to an embodiment of the present invention.
2 is a flowchart of a power control method of a hybrid vehicle using travel information according to another embodiment of the present invention.
3 is a flowchart showing a detailed procedure for predicting a velocity profile.
Fig. 4 is a schematic diagram showing a plurality of running information necessary for predicting the running speed.
5 is a diagram showing a blinking period of a traffic light.
6 is a diagram illustrating an example of measuring a blinking period of a traffic signal for each driving section.
FIG. 7 is a flowchart showing a process of converting the acquired traffic information to be applied to dynamic programming.
8 is a graph for predicting the traveling time by traffic condition.
9 is a diagram illustrating grid generation for generating a velocity profile in one subdivision.
10 is a flowchart showing dynamic programming.
11 is a graph showing an optimal direction for the next state according to the cost for each state.
12 is a graph showing the power value profile.
13 is a graph showing the effective discharge rate.
14 is a graph showing the rate of change of the effective discharge amount by the mileage according to the battery capacity.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT Hereinafter, the present invention will be described in detail with reference to preferred embodiments and accompanying drawings, which will be easily understood by those skilled in the art. The present invention may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein.

Hereinafter, a power control system for a hybrid vehicle using travel information according to the present invention will be described in detail with reference to FIG.

1 is a block diagram of a power control system for a hybrid vehicle using travel information according to an embodiment of the present invention.

1, a power control system 100 for a hybrid vehicle using travel information according to the present invention includes a travel information obtaining unit 120, a power calculating unit 140, a parameter calculating unit 160, and a power control unit 180 .

The travel information acquisition unit 120 includes a location information acquisition module 122, a travel section determination module 124, a traffic information acquisition module 126, and a travel speed prediction module 128.

The position information acquisition module 122 receives destination information to be moved from the driver through navigation attached to the vehicle, receives GPS (Global Positioning System) information about the vehicle, and obtains current position information of the vehicle . At this time, the GPS information includes at least one of the driving distance of the vehicle, the acceleration, the deceleration, and the ground surface inclination of the driving road, as well as the current position of the vehicle.

The travel section determining module 124 determines a travel section that the vehicle wishes to travel based on the current position information of the vehicle and the destination information.

The traffic information acquisition module 126 acquires at least one traffic information corresponding to the travel section. At this time, the traffic information includes at least one of the number of traffic lights existing in the travel section, the distance between the traffic lights, the signal period, the limited speed per section, and the average speed per section.

The traveling speed prediction module 128 repeatedly predicts the traveling speed of the vehicle in the traveling section based on at least one traffic information according to a predetermined period. The running speed predicting unit 180 calculates a running speed according to a running section on the basis of a dynamic programming technique and confirms a vehicle's stopping state or running state according to the next signal of a signal lamp in the running section, And obtains an initial start speed and a termination speed of the vehicle. In addition, the traveling speed predicting unit 180 estimates the traveling speed of the vehicle based on the average speed in the traveling section, the cruising speed, and the traffic amount per unit time, and also includes a weight for the acceleration or deceleration of the vehicle, up table.

Dynamic programming is used to analyze the collected data so as to reduce the execution time of the algorithm and to perform a corresponding action when an algorithm has characteristics of partial problem repetition and optimal basic structure .

The power operation unit 140 calculates a power value required for driving the vehicle based on the acquired speed profile.

The parameter calculation unit 160 calculates a parameter for performing power distribution of the motor or the engine of the vehicle according to the power value. The parameter calculation unit 160 may include a braking amount calculation module 162, an effective discharge amount calculation module 164, and a parameter calculation module 166.

The braking amount calculation module 162 calculates the braking amount of the vehicle from the running information.

The effective discharge amount calculation module 164 calculates the effective discharge amount for the motor of the vehicle through the vector analysis with respect to the calculated braking amount.

The parameter calculation module 166 calculates a parameter for power control of the vehicle from the calculated effective discharge amount.

The power control unit 180 applies the parameter to a PMP (Pontryagin's Minimum Principle) theory to distribute the power of the vehicle. The above PMP theory is a generalized form of Euler-Lagrange equations, which suggests a requirement to satisfy the optimal solution satisfying the optimal control problem.

Hereinafter, a method of controlling power of a hybrid vehicle using travel information according to another embodiment of the present invention will be described in detail with reference to FIG.

2 is a flowchart of a power control method of a hybrid vehicle using travel information according to another embodiment of the present invention.

As shown in FIG. 2, the hybrid vehicle power control method using travel information according to the present invention acquires travel information including at least one of a speed profile of a section to be traveled by the vehicle or altitude information of the travel distance S210).

Hereinafter, the process of acquiring the running information of the hybrid vehicle will be described in more detail with reference to FIG.

3 is a flowchart showing a detailed procedure for predicting a velocity profile.

As shown in FIG. 3, the location information acquisition module 122 receives destination information to which the vehicle is to be moved from the driver through navigation attached to the vehicle, receives GPS (Global Positioning System) information, Location information is obtained (S211). At this time, the GPS information includes at least one of a current position of the vehicle, a travel distance, an acceleration, a deceleration, and a ground surface inclination of the road.

(S212), based on the present position information of the vehicle and the destination information, to determine a predicted travel section that the vehicle is expected to travel.

Then, at least one piece of traffic information about the traveling section that the vehicle wants to travel is obtained (S213). In this case, the traffic information includes not only the number of traffic lights existing on the road, the distance between the traffic lights, and the signal period through the intelligent transport system but also the speed limit per section indicating traffic volume of the road, And an average rate of stars.

In this manner, the at least one traffic information obtained is substituted into the dynamic programming technique represented by Equation (1) to estimate the traveling speed of the vehicle traveling on the road in the traveling section (S214).

[Equation 1]

In this case, E _driving (k) is the running energy of the vehicle, T (k) is the running time, a is the acceleration of the vehicle according to the traffic, d is the deceleration of the vehicle according to the traffic, Is a weight assigned to acceleration, and v is a weight assigned to deceleration.

Particularly, the stop state or the running state of the vehicle is confirmed according to the generation of the next signal of the traffic light from the traffic information obtained for the traveling road in the traveling region.

In addition, an initial start speed and a termination speed of the vehicle in the traveling section are obtained.

In addition to this, the average speed of the vehicle traveling in the traveling section obtained from the traffic information, the weight given to the acceleration or deceleration of the vehicle generated according to the cruising speed when the flow of the vehicle is smooth and the traffic volume per unit time, Up table including a weight given to a running time of a desired vehicle.

Hereinafter, the step of predicting the velocity profile will be described in more detail.

In particular, the information necessary for predicting the velocity profile will be described with reference to FIG.

Fig. 4 is a schematic diagram showing a plurality of running information necessary for predicting the running speed.

First, a destination information of a vehicle to which a vehicle is to be received is received, information on the current position of the vehicle is obtained by receiving GPS (Global Positioning System) information from the outside, and based on the current position information of the vehicle and the destination information And determines a traveling section in which the vehicle travels.

는 교통신호의 초록불이 점등되는 지속시간이고,

는 교통신호의 노란불이 점등되는 지속시간이며,

는 교통신호의 빨간불이 점등되는 지속시간이고, d_i는 교통정보 전송기와 수신기 사이의 거리이며, Signal_i(t)는 i번째 구간의 교통신호에 교통신호 타이밍을 나타낸다. Accordingly, at least one traffic information occurring in the traveling section is obtained. E.g,

Is the duration time during which the green light of the traffic signal is turned on,

Is the duration of the yellow light of the traffic signal,

D _i is the distance between the traffic information transmitter and the receiver, and Signal _i (t) is the traffic signal timing of the i th traffic signal.

Subsequently, the driving section determined according to the input of the destination information of the driver is divided into a plurality of sub-sections, and the sub-section traffic information is input. Δd _i is the distance of the detail section i, V _{ss, I} is a running speed of the normal state of the vehicle in the detailed section i, V _{avg, I} is the average speed of the vehicle in details interval i, V _{lim, i} is The speed limit of the detailed interval i, and Q _{veh , i} receives the vehicle traffic of the detailed interval i, respectively.

In this manner, the information necessary for applying the received traffic information to dynamic programming is changed and extracted. That is, Δd _i is the distance of the detail section i, V _{ss, I} is a running speed of the normal state of the vehicle in the detailed section i, V _{avg, I} is the average speed of the vehicle in details interval i, V _{lim, i} is the speed limit of sub-interval i, Q _{veh , i} is the traffic flow of sub-interval i, V _{0 , i} is the initial velocity of sub-interval i, V _{f , i} is the end velocity of sub- _{pred , i} is the expected time at the end of the sub-section i, and? t _{wait , i} is the stop time in the traffic signal of the previous sub-section i-1.

At this time, the traffic information related to the traffic signal may be as shown in FIG. 5 below.

5 is a diagram showing a blinking period of a traffic light.

는 교통신호의 초록불이 점등되는 지속시간을 나타내고,

는 교통신호의 노란불이 점등되는 지속시간,

는 교통신호의 빨간불이 점등되는 지속시간,

는 노란불의 휴지시간,

는 빨간불의 휴지시간을 나타내는 것으로, 교통 신호등의 점멸주기를 확인할 수 있다. As shown in Figure 5,

Represents the duration of the green light of the traffic signal being turned on,

The duration of the yellow light of the traffic signal,

The duration of the red light of the traffic light,

A yellow fire downtime,

Indicates the rest time of the red light, and the flashing cycle of the traffic light can be confirmed.

In order to actually measure the traffic information, the total traveling section is 7.5 km, and a total of 13 traffic lights are installed in the traveling section, so that the blinking period of the traffic signal according to the traveling section as shown in FIG. 6 can be confirmed.

In order to apply the acquired traffic information to the dynamic programming technique, the conversion process will be described in detail.

FIG. 7 is a flowchart showing a process of converting the acquired traffic information to be applied to dynamic programming.

As shown in FIG. 7, traffic information for a specific sub-section i among a plurality of detailed sub-sections of the entire travel section is input from the obtained traffic information at step S310.

At this time, it is checked whether the initial speed of the extracted traffic information is 0 (S320).

If the initial velocity is 0, the lighting signal of the traffic signal of the previous detailed section i-1 with respect to the expected time? _{T pred , i-1} at the time of arrival at the end point for the previous detailed section i-1 of the detailed section i (S330).

At this time, when the lighting signal of the traffic signal of the previous detailed section i-1 is green, the driving time? T _{drv , i} of the detailed section i is obtained by subtracting the driving start time s from the distance? D _i of the detailed section i, And a value obtained by dividing the running speed according to the steady state of the vehicle by twice the acceleration a in the sub-section i, and the value obtained by dividing the running speed V _{ss , i} according to the steady state of the vehicle. In addition, the braking time? T _{brk , i} of the detailed section i is calculated by dividing the running start time s by the running speed V _{ss, i} according to the steady state of the vehicle in the detailed section i (S331).

과 동일하다고 판단한다(S332). Or the turn-on signal of the traffic signal of the previous detailed section i-1 is red, the stop time? T _{wait , i} in the traffic signal of the detailed section i is the stop time of the red light of the traffic signal

(S332).

에 이전 세부구간 i-1에서의 빨간불이 점등되는 시간인

를 더하여 획득할 수 있다(S333). On the other hand, when the lighting signal of the traffic signal of the previous detailed section i-1 is yellow, the stopping time? T _{wait , i} in the traffic signal of the detailed section _i is the rest time of the yellow fire

Is the time at which the red light in the previous detail section i-1 is lit

(Step S333).

Subsequently, the stop time? T _{wait , i} in the traffic signal of the detailed section i, the running time? T _{d rv, i} of the detailed section i, the braking time? _{Brk , i} of the detailed section i and the previous detailed section i 1, the lighting signal of the traffic signal of the previous detailed section i-1 with respect to the expected time? _{T pred , i-1} at the time of arrival at the end point with respect to i-1 is checked (S340).

At this time, when the lighting signal of the traffic signal of the detailed section i is green, the expected time? _{T pred , i,} when arriving at the end point of the detailed section i, is the distance? D _i of the detailed section i from the steady state the traveling speed V _ss, stop time at the divided by _i, and a traffic signal of double the divided value of the detail section i acceleration a running speed V _{ss, i} of the normal state of the vehicle in a, a detail section i along Δt _wait, by adding a _i and a time when the expected arrival at the end point of the previously detailed interval Δt _{pred 1-i, i-1,} can be calculated (S341).

However, if the lighting signal of the traffic signal of Detail section i in red or yellow, is expected on arrival at the end point of the detail section _i Δt _pred, i is obtained by subtracting the running start time s in the distance Δd _i of detail interval i A value obtained by dividing the running speed V _{ss , i} according to the steady state of the vehicle in the detailed section i and a value obtained by dividing the running speed according to the steady state of the vehicle by twice the acceleration a in the detailed section i are added, , Subtracts the value obtained by dividing the traveling speed V _{ss , i} according to the steady state of the vehicle by the distance between the transmitter and the receiver of the traffic information in the detailed section i and then calculates the stopping time Δt _wait in the traffic signal of the detailed section i _{, i} and the expected time? t _{pred , i-1} at the end of the previous detailed section i-1 (S342).

If the initial speed is not 0, the stop time? T _{wait , i} in the traffic signal of the detailed section i is set to 0, and the driving time? T _{drv , i} of the detailed section _i is set to 0 i is set to a value obtained by subtracting the running start time s from the distance? d _i of the detailed section _i and dividing the running speed V _{ss , i} according to the steady state of the vehicle in the detailed section i, and the braking time? _{brk ,} The start time s is set to a value obtained by dividing the starting speed V _{ss , i} according to the steady state of the vehicle in the detailed section i (S350).

Subsequently, the stop time? T _{wait , i} in the traffic signal of the detailed section i, the running time? T _{drv , i} of the detailed section i, the braking time? _{Brk , i} of the detailed section i and the previous detailed section i- 1, the lighting signal of the traffic signal of the previous detailed section i-1 with respect to the estimated time? _{T pred , i-1} when arriving at the end point with respect to i-1 is checked (S360).

At this time, when the lighting signal of the traffic signal of the detailed section i is green, the expected time? _{T pred , i,} when arriving at the end point of the detailed section i, is the distance? D _i of the detailed section i from the steady state the traveling speed V _ss, is calculated by adding the time Δt _{pred, i-1} is expected on arrival at the end point of the value and the previous detailed interval i-1, divided by _i (S361) in accordance with.

However, if the lighting signal of the traffic signal of Detail section i in red or yellow, is expected on arrival at the end point of the detail section _i Δt _pred, i is obtained by subtracting the running start time s in the distance Δd _i of detail interval i The driving speed V _{ss , i} according to the steady state of the vehicle is divided by the distance d _i of the detailed section i in the detailed section i from the value obtained by dividing the driving speed V _{ss , i} according to the steady state of the vehicle in the detailed section i And subtracts the estimated time Δt _{pred , i-1} from the expected time at the end of the previous detailed section i-1 (S362).

As a result, the time that is expected on arrival at the end point of a detail section i calculated through the above process S342 Δt _{pred, i,} and a process time that is expected on arrival at the end point of a detail section i calculated through S362 Δt _{pred, i} The lighting signal of the traffic signal of the detailed section i is checked (S370).

Accordingly, when the lighting signal of the traffic signal is green, the termination speed _{Vf , i} of the detailed section i is the driving speed _{Vss , i} according to the steady state of the vehicle in the detailed section i (S371).

However, if the on-signal of the traffic signal is red or yellow, of a detail section i terminal velocity V _{f, i} is a 0 (S372).

As a result, the initial velocity V _{0 , i + 1} of the next detailed interval i + 1 becomes the final velocity V _{f , i} of the detailed interval i (S380).

The traffic information converted or extracted so as to be applicable to the dynamic programming is stored through the above-described process (S390).

Based on the calculated at least one traffic information, the traveling speed of the vehicle in the traveling section is predicted according to a predetermined period.

8 is a graph for predicting the traveling time by traffic condition.

As shown in FIG. 8, Δt _{pred , i} is the time expected when arriving at the end point of sub-section i, Δt _{wait , i} is the stopping time in the previous traffic signal and Δt _{drv ,} And? T _{brk , i} is the vehicle deceleration time in the sub-section i. Accordingly, the details of the stopping time and the deceleration time of the vehicle can be obtained in detail according to traffic conditions.

와, 다음 과정으로 최적 방향을 나타내는

및 최적방향으로의 주행시간

이 출력된다. The traffic information thus generated is applied to the dynamic programming to generate the speed profile in succession in the subdivided detail sections for the entire travel section. That is, the distance of the detail section i Δd _i, of the detailed section i running speed according to the normal state of the vehicle V _ss, from _i, details interval i the average speed of the vehicle V _avg, at the _i, details interval i the speed limit V _{lim, i} , the vehicle speed Q _{veh , i} of the detailed section i, the initial speed V _{0 , i} of the detailed section i, and the termination speed V _{f , i} of the detailed section i are applied to the dynamic programming, Optimized Cost

And the next step is to show the optimal direction

And the travel time in the optimum direction

Is output.

Hereinafter, a lattice generation process for generating a velocity profile in one sub-section will be described in detail with reference to FIG.

9 is a diagram illustrating grid generation for generating a velocity profile in one subdivision.

As shown in FIG. 9, when information of a specific sub-section i is input among the entire travel sections, a grid of x and y axes is generated. At this time, the x-axis represents the distance and the y-axis represents the speed. The lattice of the x-axis is defined as a stage stage, and the lattice of the y-axis is defined as a state state, and the distance s of each stage on the x-axis is set to vary according to the distance d of the detailed section i.

가 200m 이하일 경우에 x축 상의 각 스테이지의 거리

, 200m를 초과하고 1000m 이하인 경우에는 x축 상의 각 스테이지의 거리

, 1000m초과하는 경우에는 x축 상의 각 스테이지의 거리

가 되도록 설정되며, 또한 y축 격자의 경우에는 0.2m/s 간격으로 설정된다.Therefore, the distance of the sub-

The distance of each stage on the x axis

, And when it is more than 200m but not more than 1000m, the distance of each stage on the x axis

, And if it exceeds 1000 m, the distance of each stage on the x axis

And in the case of the y-axis lattice, it is set at an interval of 0.2 m / s.

The dynamic programming technique computes the cost to go from a state state on a particular stage stage to an arbitrary state state on the next stage stage and iteratively repeats this operation from the distance S _N to S _{0 in} the reverse direction, . Thus, all grids store local costs.

Then, when the initial velocity v _initial at the distance S ₀ and the final velocity v _final at the distance S _N are determined, a path having the minimum cost to go from the initial velocity v _initial to the final velocity v _final is determined. The path determination with minimum cost is expressed by the following equation (2).

&Quot; (2) "

In other words, the path L (k) having the minimum cost is obtained by multiplying the driving energy E _drv (k) of the vehicle by w _t , which represents the weight assigned to the running time, by T (k) of the Acc ⁴ (k) and the multiplied value and, Dec ⁴ (k) and the multiplied value of w _b represents the reduced amount representing the weight assigned to the reduction represents the acceleration amount to w _a represents the weight both can be obtained by the sum of have. At this time, the weight w _t Can be obtained through a function calculation on the traveling speed V _{ss , i} according to the steady state of the vehicle and the distance d _i between the detailed section i in the detailed section i, as shown in the following equation (3).

&Quot; (3) "

Further, w _a representing the weight assigned to the acceleration And w _b representing the weight assigned to the deceleration can be obtained through a functional operation on the average traveling speed V _{avg , i} of the detailed section _i and the limiting speed V _{lim , i} .

&Quot; (4) "

As a result, when the path where the total cost J consumed for traveling the distance is minimum is a state variable represented by x (s) in the process s and a control variable represented by u (s), the following equation . ≪ / RTI >

&Quot; (5) "

Thus, the generated path J is the result of the velocity profile for the running information of sub-section i.

Hereinafter, the dynamic programming technique will be described in detail with reference to FIG.

10 is a flowchart showing dynamic programming.

As shown in Fig. 10, first, driving information is inputted (S410).

Thereafter, a grid consisting of an x-axis (stage stage) and a y-axis (state) is generated (S420). At this time, the number of stages is N, the number of states is M, the stage distance s on the x-axis is set to N-1, the number of stages, and the number of states k and The number of states j currently displayed on the stage s is set to 0, respectively.

Accordingly, the running time T, the cost Cost, and the cumulative cost C between j and k are calculated using the following Equations 4 to 6 (S430).

는 하기의 수학식 6을 통해 연산할 수 있다. First, the running time when j of the current stage s moves to k of the next stage s + 1

Can be calculated by the following equation (6).

&Quot; (6) "

는 스테이지간 거리이고, 상기

는 다음 스테이지에서 k의 속도이고, 상기

는 현재 스테이지 s의 j에서 속도를 나타낸다. At this time,

Is a distance between stages,

Is the velocity of k at the next stage,

Represents the velocity at j of the current stage s.

는 하기의 수학식 7을 통해 연산할 수 있다. Further, the cost required when j of the current stage s moves to k of the next stage s + 1

Can be calculated by the following equation (7).

[Equation 7]

는 현재 스테이지 s의 j가 다음 스테이지 s+1의 k로 이동할 때 주행에너지

와, 주행시간에 할당된 가중치를 나타내는 w_t에 현재스테이지 s에서 j가 다음 스테이지 s+1에서 k로 이동할 때 주행시간을 나타내는

를 곱한 값과, 가속에 할당된 가중치를 나타내는 w_a를 현재 스테이지 s에서 j가 다음 스테이지 s+1에서 k로 이동할 때 가속량을 나타내는

의 4제곱과 곱한 값, 및 감속에 할당된 가중치를 나타내는 w_b를 현재 스테이지 s에서 j가 다음 스테이지 s+1에서 k로 이동할 때 감속량을 나타내는

의 4제곱과 곱한 값을 합산하여 획득할 수 있다. That is, the cost of moving j in the current stage s to k in the next stage s + 1

When the j of the current stage s moves to k of the next stage s + 1,

And w _t , which represents the weight assigned to the running time, represents the running time when j moves from the next stage s + 1 to k in the current stage s

And w _a , which represents the weight assigned to acceleration, representing the amount of acceleration when j moves from the next stage s + 1 to k in the current stage s

And w _b , which represents the weight assigned to deceleration, is expressed as a deceleration amount when j moves from the next stage s + 1 to k in the current stage s

And then multiplying the product by the fourth power of the product

는 하기의 수학식 8과 같이, 현재 스테이지 s의 j가 다음 스테이지 s+1의 k로 이동할 때 주행 파워

와, 현재스테이지 s에서 j가 다음 스테이지 s+1에서 k로 이동할 때 주행시간을 나타내는

를 곱한 값을 나타낸다. At this time, when j of the current stage s moves to k of the next stage s + 1,

When the j of the current stage s is moved to k of the next stage s + 1, as shown in Equation (8) below,

And the travel time when j moves from the next stage s + 1 to k in the current stage s

.

[Equation 8]

는 하기의 수학식 9를 통해 연산할 수 있다. Further, in the present stage s, when j moves from the next stage s + 1 to k,

Can be calculated by the following equation (9).

&Quot; (9) "

는 하기의 수학식 10을 통해 연산할 수 있다.In addition, in the present stage s, when j moves from the next stage s + 1 to k,

Can be calculated by the following equation (10).

&Quot; (10) "

는 다음 스테이지에서 현재 스테이지를 뺀 거리로서, 하기의 수학식 11을 통해 연산할 수 있다.In addition,

Is a distance obtained by subtracting the current stage from the next stage and can be calculated by the following equation (11).

&Quot; (11) "

The cumulative cost can be calculated through the following equation (12) for summing the traveling time and the required cost calculated through the equations (6) to (7).

&Quot; (12) "

In operation S440, it is determined whether k is equal to the maximum number of states that can be displayed on the current stage s (S440).

, 인덱스값

및 주행시간

을 연산한다(S450). If j is equal to the maximum number of states that can be represented on the current stage, the cumulative cost (j) representing the state j in the current stage s based on Equations (7) to

, Index value

And travel time

(S450).

는 현재 스테이지 s에서의 스테이트 j가 0 부터 최대 M까지 이동할 때의 각각의 소요비용의 최소값을 산출한다. First, as shown in Equation (13) below, cumulative cost

Calculates the minimum value of each required cost when the state j in the current stage s moves from 0 to the maximum M.

&Quot; (13) "

는 현재 스테이지 s에서 다음 스테이지로의 최적 방향을 나타내는 인덱스값을 말하며, 이는 최대 변수 m으로 표기된다. At this time,

Is the index value indicating the optimal direction from the current stage s to the next stage, which is denoted by the maximum variable m.

&Quot; (14) "

는 스테이지 s에서 j가 다음 스테이지 s+1의 최대 스테이트 수 m으로 이동할 때까지 주행시간과 동일하다고 판단한다. Therefore, as shown in the following equation (15), the running time

Judges that j is the same as the running time until j moves to the maximum state number m of the next stage s + 1 in the stage s.

&Quot; (15) "

Then, the optimized cost, index value, and travel time are stored.

However, if k is not equal to the maximum number M of states that can be displayed on the current stage s in step S440, k is incremented by one (S441), and the step S430 is repeated.

In addition, it is checked whether j is equal to the maximum number M of states that can be displayed on the current stage s (S460). If it is not the same, k is set to 0, j is incremented by 1, and the process of S430 is repeated (S461).

On the other hand, if j is equal to the maximum number M of states that can be represented on the current stage s, it is checked again whether the S is equal to N-1, which is the number of stages (S470).

Thereafter, if S is equal to N-1, which is the number of stages, result data for all stages and states are stored (S480).

Alternatively, if S is not equal to N-1, which is the number of stages, j and k are set to 0, s is decremented by 1, and then step 430 is repeated (S471) .

The optimal direction for the next state according to the above-described equation and the cost for each state calculated through the traffic information can be confirmed through FIG.

11 is a graph showing an optimal direction for the next state according to the cost for each state.

As shown in FIG. 11, a solid line can be confirmed when the initial speed is set to 0, and a speed profile that can be predicted according to traffic conditions for the detailed section i of the driving section can be obtained.

Referring back to FIG. 2, the power calculation unit 140 calculates the demanded power value required for driving the vehicle based on the velocity profile acquired (S220).

The demand power value P _t (t) can be obtained by multiplying the wheel driving force of the vehicle by the vehicle speed through the following equation (16).

 &Quot; (16) "

Here, _Ft (t) is the wheel driving force of the vehicle, and v (t) is the vehicle speed.

At this time, the wheel driving force F _t (t) can be calculated by the following equation (17).

&Quot; (17) "

The parameter operation unit 160 calculates a parameter for performing power distribution of the motor or the engine of the vehicle according to the power value (S230).

In order to calculate these parameters first, the braking amount of the vehicle is calculated from the power value calculated through the running information.

12 is a graph showing the power value profile.

As shown in FIG. 12, the power value computed in step S220 is largely divided into acceleration power (indicated by a red line) required at the time of vehicle acceleration or constant speed running, braking force Quot; line "). When a braking force is generated in a general vehicle, it is regarded as a loss because it is lost as heat due to braking in the brake. In the case of a hybrid vehicle, the braking force is converted into electric energy and used to charge a battery installed in the vehicle.

In this way, an effective discharge rate (SOC) for the motor of the vehicle is calculated through vector analysis of the obtained braking force of the vehicle.

Hereinafter, the process of calculating the effective discharge rate will be described in more detail with reference to FIG.

13 is a graph showing the effective discharge rate.

The total travel time from the demand force value profiles calculated through the step S220 above, as shown in FIG. 13 T _{drv _ tot,} the effective braking time T _{reg _ eff,} equation to stop obtain the time T _stop, and therefrom and calculates the effective running time T _{drv _ eff} by 18.

&Quot; (18) "

_{T drv _ eff = T drv _} tot - T reg _ eff - T stop

Further, the change amount? SOC reg_eff of the braking force is calculated from the previously obtained braking force using the following equations (19) to (20).

&Quot; (19) "

&Quot; (20) "

는 전체 제동력에 대한 전기적 제동력의 비율을 나타낸다. Where Q is the total charge of the battery, R is the average internal resistance of the battery, V is the battery average voltage,

Represents the ratio of the electric braking force to the total braking force.

Thus, the effective discharge rate SOC _{drv _ eff} is as can be seen through Equation (21) below can be obtained by dividing the change amount ΔSOC _{reg _ eff} of the braking force as an effective travel time T _{drv _ eff.}

&Quot; (21) "

The effective discharge rate SOC _{drv _ eff} represents the battery output power that are used on average with respect to the speed profile.

At this time, the amount of change in the braking force ΔSOC _{reg _ eff} is as shown in the running, the initial state of charge SOC, SOC _i and the travel since the last state of charge SOC, SOC _f is when to be given, the following equation 22 and 5 of the vehicle , And can be calculated by a vector operation. For example, in the case of a plug-in hybrid vehicle, SOC _i may be 0.9 or 0.8, and SOC _f may be 0.3 or 0.2.

 &Quot; (22) "

ΔSOC _{drv _ eff = SOC i - SOC f - ΔSOC} reg _ eff

과 사용가능한 배터리의 에너지 용량 E_bat에 대한 함수를 통해 획득할 수 있다. In this manner, a parameter for power control of the vehicle is calculated from the calculated effective discharge amount. That is, the parameter p is calculated by the following equation (23)

And the energy capacity of the available battery, E _bat .

&Quot; (23) "

In this case, the parameter p is, ΔSOC _{drv _ eff} E _bat is the available capacity of the battery installed in the plug-in hybrid vehicle. When the total capacity of the battery is 5 kWh, the usable capacity energy that can actually be used among the total capacity is about 50 to 70%. That is, when the initial state of charge SOC, SOC _i is 0.9 or 0.8, it means that the battery is charged up to 90% or 80% instead of 100%. Similarly, when the final state of charge is SOC and SOC _f is 0.3 or 0.2, the battery is not discharged until the energy is 0%, but when the remaining energy of the battery is 30% or 20% Therefore, it is possible to prevent shortening of the life of the battery and lowering of the output efficiency.

As a result, the parameter can be expressed as a function of the usable capacity of the battery, as shown in Equation 24 below.

&Quot; (24) "

At this time, a (E _bat ) and b (E _bat ) are the same as those which can be calculated through the following equations (25) to (26).

&Quot; (25) "

&Quot; (26) "

The values of the constants C _ai and C _bi applied to the equations (25) to (26) are shown in Table 1 below.

C _a1 C _a2 C _a3 C _a4 C _a5 45.944 -907.16 8778.6 -131289 225126 C _b1 C _b2 C _b3 C _b4 C _b5 -0.0191 0.2721 -1.9148 -138.94 0.7025

As a result, the parameters can be expressed as an effective discharge amount and a battery capacity as in Equation (24), and can be applied not only to a general hybrid vehicle but also to a vehicle equipped with a large capacity battery such as a plug-in hybrid vehicle. In particular, since the predicted state is not a map type and the current state of the battery is calculated as a bivariate function, the capacity of the computer memory can be reduced in actual application.

As such, the equation relating to the parameters can calculate the parameter results from about -250 to -1300 at an error rate of about 0.02% to less than 5% when the battery capacity is variously considered.

Hereinafter, as an example of the expression (24), the rate of change of the effective discharge amount by the mileage distance according to the battery capacity change will be described in detail with reference to FIG.

14 is a graph showing the rate of change of the effective discharge amount by the mileage according to the battery capacity.

14 (a) shows the rate of change of the effective discharge amount by the mileage when the battery capacity is 1.4 kWh, and FIG. 14 (b) shows the rate of change of the effective discharge amount by the mileage when the battery capacity is 3.4 kWh, 14 (c) shows the rate of change of the effective discharge amount by the mileage when the battery capacity is 5.2 kWh.

In the case of FIG. 14A, since the capacity of the battery is relatively small as compared with the case of FIGS. 14B and 14C, the effective SOC use range for the y-axis normalized battery state (State of Charge SOC) It can be reduced from 0 to about -2 according to the number of cycles, and battery energy is recovered at around 0.5 due to effective regenerative braking after completion of running.

In the case of FIG. 14 (b), the final state quantity of battery energy according to the number of times of repeated operation is shown when the battery capacity is 3.4 kWh for the same traveling cycle. That is, since the capacity of the battery can sufficiently supply the drive energy required for one run, the SOC effective line ending at around 1300 seconds ends at -0.4, Indicating that the vehicle can be operated using only electric power. Thereafter, the running cycle is repeated from 2 to 5 times, and the final state result of the SOC shows that most of the final SOC converges to around -0.5.

Also in the case of FIG. 14 (c), since the capacity of the battery is 5.2 kWh, it is possible to supply all of the driving energy for the two repetitive driving, which means that the vehicle can be driven only by the pure electric vehicle. Thereafter, it can be confirmed that the final SOC converges to about -0.5 for the third to fifth runs.

As a result, as shown in FIG. 14, since the battery use state of the hybrid vehicle is changed according to the battery capacity, it is important to consider the remaining amount of battery energy in order to calculate the effective discharge amount. It is possible to quantitatively derive an accurate effective discharge amount with respect to the valve timing.

The power control unit 180 applies the calculated parameters to the PMP (Pontryagin's Minimum Principle) theory to perform power distribution to the motor and the engine of the vehicle at step S240.

Further, the method and system for controlling the power of the hybrid vehicle using such running information may be stored in a computer-readable recording medium on which a program for execution by the computer is recorded. At this time, the computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored. Examples of the computer readable recording medium include ROM, RAM, CD-ROM, DVD 占 ROM, DVD-RAM, magnetic tape, floppy disk, hard disk, optical data storage, and the like. The computer readable recording medium can also be distributed over network coupled computer devices so that the computer readable code is stored and executed in a distributed fashion.

A method and system for controlling power of a hybrid vehicle using travel information of the present invention receives a final destination from a driver through vehicle navigation and confirms a travel section and then determines whether or not the travel section There is an effect that the traveling speed of the vehicle can be predicted in advance.

Further, the method and system for controlling the power of the hybrid vehicle using the running information of the present invention have the effect of easily controlling the power of the hybrid vehicle having the engine and the motor as the power source, by predicting the running speed of the vehicle in advance.

In addition, the method and system for controlling the power of the hybrid vehicle using the running information of the present invention have the effect of improving the fuel efficiency of the vehicle and thus improving the satisfaction of the driver as the power of the hybrid vehicle is easily controlled .

While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, Do.

120: Driving information obtaining unit 140: Power calculating unit
160 Parameter calculation unit 180:

Claims (17)

Obtaining driving information including at least one of a speed profile of the section to which the vehicle intends to travel or altitude information on the driving distance;
Calculating a power value required for driving the vehicle based on the acquired speed profile;
Calculating a parameter for performing power distribution of the motor or the engine of the vehicle according to the power value; And
Applying the parameter to a PMP (Pontryagin's Minimum Principle) theory to distribute the power of the vehicle;
The power control method of the hybrid vehicle using the running information.
The method of claim 1,
The step of acquiring the running information
A step of receiving destination information to which the vehicle wants to arrive and obtaining current position information of the vehicle by receiving GPS (Global Positioning System) information;
Determining a traveling section in which the vehicle travels based on current position information of the vehicle and the destination information;
Obtaining at least one traffic information occurring in the traveling section; And
Estimating a traveling speed of the vehicle in the traveling section according to a predetermined period based on the at least one traffic information to obtain traveling information;
The power control method of the hybrid vehicle using the running information.
3. The method of claim 2,
The process of predicting the traveling speed of the vehicle
Wherein the running speed of the hybrid vehicle is calculated based on a dynamic programming technique.
The method of claim 3,
The process of predicting the traveling speed of the vehicle
A step of checking a stop state or a running state of the vehicle according to the traffic information acquired in the travel section; And
Obtaining an initial start speed and an end speed of the vehicle in the traveling section;
Further comprising the steps of: determining whether the vehicle is traveling on a road;
5. The method of claim 4,
The process of predicting the traveling speed of the vehicle
Up table including a weight for acceleration or deceleration of the vehicle and a weight for the running time of the vehicle according to the average speed of the running section, the cruising speed, and the traffic volume per unit time;
Further comprising the steps of: determining whether the vehicle is traveling on a road;
3. The method of claim 2,
The GPS information
And at least one of a current position of the vehicle, a mileage, an acceleration, a deceleration, and an inclination of the ground of the road.
3. The method of claim 2,
The traffic information
A signal period, a limit speed for each section, and an average speed for each section, based on the driving information of the hybrid vehicle.
The method of claim 1,
The step of computing the parameter
Calculating a braking amount of the vehicle from the running information;
Calculating an effective discharge amount for the motor of the vehicle through a vector analysis on the calculated braking amount; And
Calculating a parameter for power control of the vehicle from the calculated effective discharge amount;
Wherein the driving force information includes at least one of the following:
A computer-readable recording medium having recorded thereon a program for executing the method of claim 1 on a computer.
A driving information acquisition unit for obtaining driving information including at least one of a speed profile of the section to which the vehicle is to travel and altitude information about the driving distance;
A power operation unit for calculating a power value required for driving the vehicle based on the obtained speed profile;
A parameter calculator for calculating a parameter for performing power distribution of the motor or the engine of the vehicle according to the power value; And
A power controller for distributing the power of the vehicle by applying the parameter to a PMP (Pontryagin's Minimum Principle) theory;
Hybrid vehicle power control system using the driving information comprising a.
The method of claim 10,
The traveling information obtaining unit
A location information acquisition module for receiving the destination information to which the vehicle desires to arrive, and receiving current position information of the vehicle by receiving GPS (Global Positioning System) information;
A traveling section determining module that determines a traveling section on which the vehicle travels based on current position information of the vehicle and the destination information;
A traffic information acquisition module for acquiring at least one traffic information generated in the traveling section; And
A traveling speed predicting module for predicting a traveling speed of the vehicle in the traveling section according to a predetermined period based on the acquired at least one traffic information;
And a power control system for controlling the power of the hybrid vehicle.
12. The method of claim 11,
The traveling speed prediction module
Wherein the running speed of the hybrid vehicle is calculated based on a dynamic programming technique.
The method of claim 12,
The traveling speed prediction module
Wherein the controller acquires the vehicle's stopping state or running state according to the traffic information obtained in the running section, and obtains the initial starting speed and the ending section speed of the vehicle in the running section, Control system.
The method of claim 13,
The traveling speed prediction module
Up table including a weight for the acceleration or deceleration of the vehicle and a weight for the running time of the vehicle according to the average speed of the traveling section, the cruising speed, and the traffic volume per unit time, A power control system for a hybrid vehicle using traveling information.
12. The method of claim 11,
The GPS information
Power control system of a hybrid vehicle using the driving information, characterized in that it comprises at least one of the current position of the vehicle, the traveling distance, acceleration, deceleration, the ground slope of the road.
12. The method of claim 11,
The traffic information
A signal period, a limit speed for each section, and an average speed for each section. The power control system for a hybrid vehicle according to claim 1,
The method of claim 10,
The parameter calculation unit
Calculating a braking amount of the vehicle from the running information, calculating an effective discharge amount of the vehicle with respect to the motor by vector analysis with respect to the calculated braking amount, calculating a parameter for power control of the vehicle from the calculated effective discharge amount The power control system of the hybrid vehicle using the running information.

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