KR102636363B1 - Vehicle control apparatus and operating method thereof - Google Patents

Abstract

A vehicle control device and method of operating the same are disclosed. One embodiment calculates the speed change of the vehicle based on input information, predicts the average speed of the vehicle based on the calculated speed change, and generates a first speed profile based on the predicted average speed, A second speed profile is generated by applying speed noise information to the first speed profile.

Description

Vehicle control device and operating method thereof {VEHICLE CONTROL APPARATUS AND OPERATING METHOD THEREOF}

The embodiments below relate to vehicle control devices.

As environmental issues and energy resource issues become more important, electric vehicles are attracting attention as a future means of transportation.

Electric vehicles can generate speed profiles based on their current driving speed. The speed profile generated by this calculation method does not take into account the external environment information and traffic information of the electric vehicle, so the generated speed profile may have a large difference from the actual driving speed profile of the electric vehicle.
As related prior art, there is Korean Patent Publication No. 10-2016-0073899 (Title of the invention: Apparatus and method for estimating battery charging information of an electric vehicle, Applicant: Samsung Electronics Co., Ltd. and North Carolina State University).

A method of operating a vehicle control device according to one aspect includes calculating a change in speed of a vehicle based on input information; predicting the average speed of the vehicle based on the calculated speed change; generating a first speed profile based on the predicted average speed; and generating a second speed profile by applying speed noise information to the first speed profile.

The step of calculating the amount of change in speed of the vehicle may include calculating the amount of change in speed corresponding to each point on the path of the vehicle based on input information related to each point.

The input information may include weather information, traffic flow information, and road type information.

Predicting the average speed of the vehicle may include predicting the average speed of the vehicle at each point using the speed change amount corresponding to each point on the path of the vehicle and the reference speed of each point. You can.

Generating the first speed profile may include generating the first speed profile based on an average speed predicted for each point on the path of the vehicle.

The operating method may further include predicting power to be consumed by the vehicle based on the second speed profile.

The operating method includes predicting power to be delivered to the power train of the vehicle based on the second speed profile; And it may further include predicting the power to be consumed by the air conditioning system of the vehicle based on at least one of solar radiation information and outside temperature information.

The operating method may further include determining a driving range of the vehicle based on at least one of current state information of the battery unit of the vehicle and the current fuel amount of the vehicle and a predicted value for power to be consumed by the vehicle. You can.

Determining the driving range of the vehicle may include predicting at least one of state information and fuel amount of the battery unit at the destination based on the predicted value for the power; And it may include determining whether the vehicle can drive to the destination through at least one of the predicted state information and the predicted fuel amount.

generating guide information for driving of the vehicle based on the second speed profile; And it may further include visually outputting the guide information.

Generating the guide information includes comparing a predicted average speed derived from the second speed profile and a target speed derived from driving history information of the vehicle; and generating the guide information based on the comparison result.

Generating the guide information includes identifying a speed section that satisfies a predetermined standard in the second speed profile; And it may include generating the guide information for driving on a path corresponding to the identified speed section.

A vehicle control device according to one aspect includes a controller; and a memory including at least one instruction executable by the controller, and when the at least one instruction is executed by the controller, the controller calculates a change in speed of the vehicle based on input information, and calculates the calculated amount of change in speed of the vehicle. The average speed of the vehicle is predicted based on the speed change, a first speed profile is generated based on the predicted average speed, and speed noise information is applied to the first speed profile to generate a second speed profile.

The controller may calculate a speed change corresponding to each point on the vehicle's path based on input information related to each point.

The input information may include weather information, traffic flow information, and road type information.

The controller may predict the average speed of the vehicle at each point using the speed change amount corresponding to each point on the path of the vehicle and the reference speed of each point.

The controller may generate the first speed profile based on the average speed predicted for each point on the vehicle's path.

The controller may predict power to be consumed by the vehicle based on the second speed profile.

The controller predicts power to be delivered to the power train of the vehicle based on the second speed profile, and predicts power to be consumed by the air conditioning system of the vehicle based on at least one of solar radiation information and outside temperature information. You can.

The controller may determine the driving range of the vehicle based on at least one of current state information of the vehicle's battery unit and the current fuel amount of the vehicle and a predicted value for power to be consumed by the vehicle.

The controller predicts at least one of state information and fuel amount of the battery unit at the destination based on the predicted value for the power, and drives the vehicle to the destination through at least one of the predicted state information and the predicted fuel amount. You can decide whether it is possible or not.

The controller may generate guide information for driving of the vehicle based on the second speed profile and visually output the guide information.

The controller may compare a predicted average speed derived from the second speed profile with a target speed derived from driving history information of the vehicle, and generate the guide information based on the comparison result.

The controller may identify a speed section that satisfies a predetermined standard in the second speed profile and generate the guide information for driving on a path corresponding to the identified speed section.

1 is a flowchart for explaining the operation of a vehicle control device according to an embodiment.
FIG. 2 is a diagram illustrating how a vehicle control device calculates a speed change amount according to an embodiment.
3A to 3C are diagrams for explaining a membership function according to an embodiment.
FIG. 4 is a diagram illustrating how a vehicle control device generates first and second speed profiles according to an embodiment.
5 and 6 are diagrams for explaining an example of driving-related information generated based on a second speed profile according to an embodiment.
FIG. 7 is a diagram illustrating another example of driving-related information generated based on a second speed profile according to an embodiment.
Figure 8 is a block diagram for explaining a vehicle control device according to an embodiment.

Hereinafter, embodiments will be described in detail with reference to the attached drawings.

Various changes may be made to the embodiments described below. The embodiments described below are not intended to limit the embodiments, but should be understood to include all changes, equivalents, and substitutes therefor.

Terms used in the examples are merely used to describe specific examples and are not intended to limit the examples. Singular expressions include plural expressions unless the context clearly dictates otherwise. In this specification, terms such as “comprise” or “have” are intended to designate the presence of features, numbers, steps, operations, components, parts, or combinations thereof described in the specification, but are not intended to indicate the presence of one or more other features. It should be understood that this does not exclude in advance the possibility of the existence or addition of elements, numbers, steps, operations, components, parts, or combinations thereof.

Unless otherwise defined, all terms used herein, including technical or scientific terms, have the same meaning as generally understood by a person of ordinary skill in the technical field to which the embodiments belong. Terms defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related technology, and unless clearly defined in this specification, should not be interpreted in an idealized or overly formal sense. No.

Additionally, when describing an embodiment, if it is determined that a detailed description of a related known technology may unnecessarily obscure the gist of the embodiment, the detailed description is omitted.

1 is a flowchart for explaining the operation of a vehicle control device according to an embodiment.

Referring to FIG. 1, a vehicle control unit (VCU) calculates the speed variation of the vehicle based on input information (110). The vehicle control device may calculate the amount of speed change corresponding to each point on the route based on input information (e.g., weather information, traffic flow information, road type information) related to each point on the route on which the vehicle will travel.

In one embodiment, the speed change amount may be calculated through a speed change calculation model. The amount of change in speed is explained in detail in Figure 2.

The vehicle control device predicts the average speed of the vehicle based on the calculated speed change (120). For example, the vehicle control device can predict the average speed of the vehicle at each point using the speed change amount corresponding to each point on the route and the reference speed information at each point on the route. For example, the vehicle control device can predict the average speed of the vehicle at each point as “the amount of speed change corresponding to each point + the reference speed of each point.” If the speed change amount corresponding to each point and/or the reference speed of each point is different, the average speed of the vehicle at each point may be predicted differently.

The vehicle control device generates a first speed profile based on the predicted average speed (130). For example, the vehicle control device may generate a first speed profile for the route based on the average speed predicted for each point on the route. The first speed profile may be generated by considering the predicted average speed, so acceleration and/or deceleration of the vehicle may not be accurately expressed in the first speed profile.

Although not shown in FIG. 1, the vehicle control device may generate speed noise information. For example, a vehicle control device may generate speed noise information through a noise generation function. The noise generation function may be, for example, a Gaussian function for Additive White Gaussian Noise (AWGN). The noise generation function is not limited to the functions described above.

The vehicle control device generates a second speed profile by applying speed noise information to the first speed profile (140). Speed noise information may be information for expressing acceleration and/or deceleration of a vehicle. Accordingly, the second speed profile may be expressed similarly to the actual speed profile reflecting the acceleration and/or deceleration of the vehicle.

The creation of the first and second velocity profiles will be explained with reference to FIG. 4.

The vehicle control device determines driving-related information of the vehicle based on the second speed profile (150). For example, the vehicle control device may predict the power to be consumed by the vehicle to drive to the destination (or the power required to drive the vehicle to the destination) based on the second speed profile. Accordingly, prediction accuracy for the power consumed by the vehicle can be further increased. The power consumed by the vehicle will be explained through FIGS. 5 and 6. As another example, the vehicle control device may generate guide information for driving of the vehicle based on the second speed profile. Accordingly, the vehicle control device can allow the user to use the vehicle more efficiently and allow the user to use the battery longer. Guide information is explained with reference to FIG. 7.

The vehicle control device may determine whether driving of the vehicle has been completed (160). For example, the vehicle control device can determine whether the vehicle has arrived at its destination.

When the driving of the vehicle is not completed, the vehicle control device may operate according to the update cycle. In other words, the vehicle control device may perform steps 110 to 150 when the update cycle arrives. Depending on implementation, the vehicle control device may perform steps 110 to 150 when a user requests an update.

When driving of the vehicle is completed, the vehicle control device may end the operation.

FIG. 2 is a diagram illustrating how a vehicle control device calculates a speed change amount according to an embodiment.

Referring to Figure 2, a path 210 and a vehicle 220 are shown.

A vehicle control device (not shown) in the vehicle 220 may obtain input information related to each of the points (x, x+1, x+2,..., N) on the path 210. Input information may include, for example, any one or a combination of weather information 230, traffic flow information 231, and type information 232. In other words, the vehicle control device can obtain weather information 230, traffic flow information 231, and road type information 232 at each point on the route 210. First, each of the weather information 230, traffic flow information 231, and type information 232 will be described.

Weather information 230 may include precipitation (P) information. The vehicle control device may receive precipitation information at each point on the route 210 from an external server (for example, a Korea Meteorological Administration server or a precipitation information providing server) through a communication interface. For example, the vehicle control device may receive precipitation information such as P=0.2mm at point x from the Korea Meteorological Administration server.

Traffic flow information 231 may include a traffic index (T) determined based on the degree of traffic congestion and delay time of the route. The vehicle control device may receive the degree of traffic congestion and delay time on the route 210 from an external server (eg, a traffic information providing server) through a communication interface. The vehicle control device may determine the traffic index (T) based on the degree of traffic congestion and delay time. In the example shown in FIG. 2 , the vehicle control device may receive the traffic congestion degree and delay time at each point of the route 210, and create a traffic index for each point based on the traffic congestion degree and delay time at each point. (T) can be determined. The traffic index (T) may be a value within a predetermined range (eg, 0 to 10). For example, if the traffic congestion degree at point Depending on the implementation, the vehicle control device may receive a traffic index (T) for each point on the route 210 from an external server.

Type information 232 may indicate the type (R) of the road to which each point on the route 210 belongs. Types of roads may include, for example, city streets, local roads, and freeways. The types of roads are not limited to the foregoing. In the example shown in FIG. 2, the road corresponding to point x is Street, and the road corresponding to point x+1 is Freeway. The vehicle control device may receive type information 232 from the vehicle's navigation system.

Hereinafter, weather information 230, traffic flow information 231, and type information 232 are expressed as P, T, and R, respectively.

P, T, and R of each point on the path 210 may be input into the speed change calculation model 240. The speed change calculation model 240 shown in FIG. 2 may be a model based on a fuzzy inference system. The speed change calculation model 240 is not limited to this and may be a model learned using machine learning techniques. For example, the speed change calculation model 240 may be based on a neural network model, a recurrent neural network (RNN) model, or a long short term memory (LSTM) RNN model.

The speed change calculation model 240 can fuzzify (241) P, T, and R of each point on the path 210 through the membership functions of P, T, and R of each point on the path 210. . Hereinafter, fuzzing 241 will be described with reference to FIGS. 3A to 3C.

3A to 3C are diagrams for explaining a membership function according to an embodiment.

Referring to Figure 3A, the membership function of P is shown.

The membership function of P can be expressed, for example, as Equation 1 below.

[Equation 1]

In equation 1, a and b are constants. For example, a=0.8 and b=1.1. a and b are not limited to the examples described above.

indicates to what extent P belongs to the set corresponding to I _P = NR (No Rain). To put it another way, represents the degree of membership of P to the set corresponding to I _P =NR. Likewise, represents the degree of membership of P to the set corresponding to I _P =WR(Rain). For example, if P=1 at point x, =2/3, =1/3. The fuzzification result of P at point x indicates that P at point x belongs to 2/3 of the set corresponding to I _P =NR and 1/3 of it belongs to the set corresponding to I _P =WR.

Referring to Figure 3b, the membership function of T is shown.

The membership function of T can be expressed, for example, as Equation 2 below.

[Equation 2]

In equation 2, a ₁ to a ₄ are constants. For example, a ₁ =1, a ₂ =2, a ₃ =3.5, and a ₄ =4.5. a ₁ to a ₄ are not limited to the above examples.

represents the degree of membership of T to the set corresponding to I _T =GR(Green), represents the degree of membership of T in the set corresponding to I _T =YW(Yellow), represents the degree of membership of T in the set corresponding to I _T =RD(Red). Here, GR represents clear traffic, YW represents mild traffic, and RD represents heavy traffic. For example, if T=3 at point x, then T at point x corresponds to a ₂ <T<a ₃ , =0, =1, =0. The result of fuzzing T of _point x is _{that T of} point It indicates that 0 belongs to .

Referring to Figure 3c, the membership function of R is shown.

The membership function of R can be expressed, for example, as Equation 3 below.

[Equation 3]

For example, if R=Street at point x, the fuzzification result of R at point x is that _R at point x belongs to the set corresponding to _I It represents 0 membership and 0 membership in the set corresponding to I _R = FW.

Returning to FIG. 2, when the fuzzification 241 results for P, T, and R of each point on the path 210 are generated, the speed change calculation model 240 calculates P, T, and R of each point on the path 210. Fuzzy inference 242 can be performed based on the fuzzification 241 results for T, and R, the fuzzy rule, and the output membership function.

Table 1 below shows an example of a fuzzy rule. The fuzzy rules are not limited to Table 1 below.

r1 = 'If I _R is Local and I _P is No-Rain and I _T is Green then I _out is lc1';
r2 = 'If I _R is Local and I _P is No-Rain and I _T is Yellow then I _out is lc2';
r3 = 'If I _R is Local and I _P is No-Rain and I _T is Red then I _out is lc3';
r4 = 'If I _R is Local and I _P is Rain and I _T is Green then I _out is lc4';
r5 = 'If I _R is Local and I _P is Rain and I _T is Yellow then I _out is lc5';
r6 = 'If I _R is Local and I _P is Rain and I _T is Red then I _out is lc6';
r7 = 'If I _R is Street and I _P is No-Rain and I _T is Green then I _out is st1';
r8 = 'If I _R is Street and I _P is No-Rain and I _T is Yellow then I _out is st2';
r9 = 'If I _R is Street and I _P is No-Rain and I _T is Red then I _out is st3';
r10 = 'If I _R is Street and I _P is Rain and I _T is Green then I _out is st4';
r11 = 'If I _R is Street and I _P is Rain and I _T is Yellow then I _out is st5';
r12 = 'If I _R is Street and I _P is Rain and I _T is Red then I _out is st6';
r13 = 'If I _R is Freeway and I _P is No-Rain and I _T is Green then I _out is fw1';
r14 = 'If I _R is Freeway and I _P is No-Rain and I _T is Yellow then I _out is fw2';
r15 = 'If I _R is Freeway and I _P is No-Rain and I _T is Red then I _out is fw3';
r16 = 'If I _R is Freeway and I _P is Rain and I _T is Green then I _out is fw4';
r17 = 'If I _R is Freeway and I _P is Rain and I _T is Yellow then I _out is fw5';
r18 = 'If I _R is Freeway and I _P is Rain and I _T is Red then I _out is fw6';

The output membership function may be, for example, a Gaussian function. Equation 4 below shows an example of the output membership function. The output membership function is not limited to Equation 4 below.

[Equation 4]

In equation 4, x is a variable and m and σ are constants.

The number of output membership functions may correspond to the number of fuzzy rules. For example, the output membership function for each of the 18 fuzzy rules in Table 1 above may be 18, as shown below.

The speed change calculation model 240 applies the Mamdani Type method to the fuzzification 241 results for P, T, and R at each point on the path 210, the fuzzy rule, and the output membership function. Fuzzy inference 242 can be performed. The Mamdani-type method is only an example for fuzzy inference 242, and fuzzy inference 242 is not limited to the above-mentioned matters.

Output information corresponding to the result of fuzzification (241) may be generated through fuzzy inference (242).

The speed change calculation model 240 may defuzzify output information (243). For example, the speed change calculation model 240 may defuzzify output information 243 using the center of gravity method. The center of gravity method is only an example for defuzzification 243, and defuzzification 243 is not limited to the above-mentioned matters.

The speed change calculation model 240 can calculate the speed change amount corresponding to each point on the path 210 by defuzzifying the output information (243).

The vehicle control device may determine whether the speed change amount corresponding to each point on the path 210 will be a positive number or a negative number. The vehicle control device may determine whether the speed change amount will be positive or negative by referring to the vehicle's driving history information (eg, driving pattern, previous speed profile, etc.). For example, the vehicle control device may use driving history information to determine whether the driver mainly drives at low speeds (e.g., 20 km/h to 50 km/h) or medium speeds (e.g., 50 km/h to 70 km/h). You can. If the driver primarily drives at low or medium speeds, the vehicle control device may determine the speed change amount to be a negative number. If the driver primarily drives at high speeds (e.g., 70 km/h or higher), the vehicle control device may determine the speed change amount to be a positive number.

Table 2 below shows an example of input information related to each point on the path 210 and the speed change amount corresponding to each point on the path 210. Here, let us assume that the vehicle control device determines the speed change amount corresponding to each point on the path 210 to be a negative number.

Point input information Speed change (km/h) x P _x =1, T _x =3, R _x =Street -5 x+1 P _x+1 =1, T _x+1 =4, R _x+1 =Freeway -10 x+2 P _x+2 =1, T _x+2 =4, R _x+2 =Freeway -10 x+3 P _x+3 =1.1, T _x+3 =4, R _x+3 =Freeway -10 x+4 P _x+4 =1.1, T _x+4 =4, R _x+4 =Freeway -10 x+5 P _x+5 =0.95, T _x+5 =4, R _x+5 =Freeway -10 … … … N-1 P _N-1 =1, T _N-1 =5, R _N-1 =Local -20 N P _N =1.5, T _N =7, R _N = Street -40

The vehicle control device may generate a first speed profile based on the speed change amount corresponding to each point on the path 210, and may generate a second speed profile by applying speed noise information to the first speed profile. Hereinafter, the generation of the first and second velocity profiles will be described with reference to FIG. 4.

FIG. 4 is a diagram illustrating how a vehicle control device generates first and second speed profiles according to an embodiment.

Referring to Figure 4, a path 410 and a vehicle 420 are shown.

As described above, the vehicle control device uses the speed change amount corresponding to each point on the path 410 and the reference speed of each point on the path 410 to calculate the average of the vehicle 420 at each point on the path 410. Speed can be predicted. Table 3 below shows an example of the predicted average speed for each point on the path 410.

Point Speed change (km/h) Reference speed (km/h) Average speed (km/h) x -5 60 55 x+1 -10 110 100 x+2 -10 110 100 x+3 -10 110 100 x+4 -10 110 100 x+5 -10 110 100 … … … … N-1 -20 60 40 N -40 60 20

The vehicle control device may generate the first speed profile 430 based on the average speed predicted for each point on the route 410.

The vehicle control device may generate the second speed profile 440 by applying speed noise information to the first speed profile 430.

In the example shown in FIG. 4, let's say an accident occurs between points x+5 and points x+6. Traffic flow information at point x+6 may indicate congestion. If the vehicle control device obtains input information including traffic flow information at point x+6 at the current location of the vehicle 420, the speed change amount at each point can be calculated. Here, the vehicle control device can calculate the speed change at point x+6 as -90 km/h by considering the traffic flow information at point x+6, etc. The vehicle control device can predict the average speed of the vehicle 420 at each point. Here, the vehicle control device can predict the average speed at point x+6 to be 20 km/h. The vehicle control device may generate a first speed profile based on the average speed predicted for each point and generate a second speed profile by applying speed noise information to the first speed profile. Accordingly, real-time traffic flow information may be reflected in the second speed profile.

5 and 6 are diagrams for explaining an example of driving-related information generated based on a second speed profile according to an embodiment.

An example of driving-related information may indicate the power the vehicle will consume while driving.

In one embodiment, the power that the vehicle will consume while driving is and/or may include. may represent a predicted value for the power that the vehicle's battery pack will deliver to the power train while the vehicle is running, may represent a predicted value for the power that the vehicle's air conditioning system will consume while the vehicle is running. Hereinafter, with reference to Figure 5, Explain. The presidential election is explained through Figure 6.

Referring to FIG. 5 , a vehicle 520 travels along a path 510 .

Let us assume that vehicle 520 currently passes point x. The vehicle control unit based on the second speed profile can be calculated. For example, the vehicle control device applies the second speed profile to the power consumption calculation function to can be calculated. In other words, the vehicle control device calculates the power that the vehicle 520 will consume to drive from the current point x to the destination. It can be predicted with The power consumption calculation function is explained below.

Additionally, the vehicle control device further considers predicted values for one or more of wind direction, wind speed, and altitude at a subsequent point. can be calculated. The predicted value of the wind direction and wind speed of the subsequent point may be calculated based on the wind direction and wind speed information of the current point, and the predicted value of the altitude of the subsequent point may be calculated based on the altitude information of the current point. The vehicle control device, for example, according to equation 5 below: can be calculated.

[Equation 5]

In equation 5, represents the vehicle speed at point i, calculated at time t. In other words, may represent the second velocity profile described above. represents the predicted values for the wind direction and wind speed at point i, calculated at time t. represents the predicted value for the altitude of point i in the future, calculated at time t. represents the power consumption calculation function. For example, may represent a function that calculates the power to be delivered to the power train between the current point i-1 and the subsequent point i.

In the example shown in FIG. 5 , the vehicle control device may calculate one or more of wind direction (predicted value), wind speed (predicted value), and altitude (predicted value) at point x to point x+1. The vehicle control device determines one or more of wind direction (predicted value), wind speed (predicted value), and altitude (predicted value) at point x+1 and vehicle speed (predicted value) at point x+1. By applying , it is possible to calculate a predicted value for the power to be delivered to the power train during x~x+1. The vehicle control device may calculate a predicted value for power to be delivered to the power train for different sections. The vehicle control device sums the predicted values calculated for each of the sections (x~x+1, x+1~x+2, …, N-1~N) can be calculated.

Depending on the implementation, the vehicle control device may To increase the accuracy, various variables can be further considered. For example, the vehicle control device can be calculated according to Equation 6 below: can be calculated.

[Equation 6]

Table 4 below shows a description of the variables and functions in Equation 6.

explanation L _i Reference velocity at point i F _i Travel speed at point i El _i altitude of point i C _i precipitation at point i W _i Wind speed/direction at point i P _i Power delivered to the powertrain instantaneously at point i S _i SOC calculated at point i Velocity-related information at point i Forecast calculated at time t Driving record function for each type of road Driving record function for each driver Function to calculate predicted value for vehicle speed at point i Power consumption calculation function

In Equation 6, speed-related information at the current point x is the reference speed of the current point x, the running speed of the vehicle 520 at the current point x, the amount of precipitation at the current point x, the wind speed/wind direction at the current point Contains the SOC at point x. This is only an example according to one embodiment, The matters included are not limited to the foregoing. Depending on implementation, is the reference speed of the current point x, the running speed of the vehicle 520 at the current point x, the amount of precipitation at the current point x, the wind speed/wind direction at the current point It may contain one or more of the SOC at point x.

In equation 6, represents the predicted value calculated at the current time t for the speed-related information at point i. for example, is one of the precipitation at point i, the driving speed of the vehicle 520 at point i, the wind speed/wind direction at point i, the power to be instantaneously delivered to the power train at point i, and the SOC at point i. For the above, a predicted value calculated at time t may be included.

In equation 6, Is It will be explained through the information in and Figure 6. It may contain one or more of the information within.

In Equation 6, driving records recorded for each type of road and each driver can then be used to calculate a predicted value for the vehicle speed at point i. More specifically, the vehicle control device can record the vehicle's driving by type of road, and a driving record function for each type of road. can be created. For example, the vehicle control device may generate a driving record function for Street, a driving record function for Freeway, and a driving record function for Local. In addition, the vehicle control device can record the driving of the vehicle for each driver, and has a driving record function for each driver. can be created. The vehicle control unit then calculates a predicted value for the vehicle speed at point i. and can be used.

In the example shown in Figure 5, the vehicle control device receives speed-related information at point x. , then the predicted value for speed-related information at point i, i.e., point x+1 , the driving record for the Freeway to which point x+1 belongs, and the driving history for the current driver. You can calculate the predicted value of the vehicle speed at point x+1 by applying . various variables can be applied to, the vehicle speed at x+1 can be predicted more accurately.

Additionally, the vehicle control device may generate a predicted value for one or more of wind direction (predicted value), wind speed (predicted value), and altitude (predicted value) at point x+1 and the vehicle speed at point x+1. By applying , it is possible to calculate a predicted value for the power to be delivered to the power train during x~x+1. Likewise, the vehicle control device can calculate a predicted value for the power to be delivered to the power train for different sections. The vehicle control device sums the predicted values calculated for each of the sections (x~x+1, x+1~x+2, …, N-1~N) can be calculated. Various environmental variables can be considered in calculating, Accuracy can be increased.

Vehicle 520 may operate an air conditioning system. When the air conditioning system is activated, the power consumed by the vehicle 520 may increase. Accordingly, the power that the air conditioning system will consume while driving the vehicle 520 If is predicted, prediction accuracy for the power to be consumed by the vehicle 520 can be further increased. Hereinafter, with reference to FIG. 6, The calculation is explained.

6, a vehicle 610 and a sun 620 are shown.

Let vehicle 610 pass the current point x.

Solar radiation and the outside temperature of the vehicle 610 may affect the power consumption of the air conditioning system. The vehicle control device is based on at least one of solar radiation information and outside temperature information. can be calculated. For example, the vehicle control unit may provide a forecast for the weather-related information at a future point (e.g., point can be calculated, based on the weather-related information at the current point and the predicted value of the weather-related information at future points. can be calculated. The vehicle control device, for example, according to equation 7 below: can be calculated.

[Equation 7]

Table 5 below shows an explanation of the variables and functions in Equation 7.

explanation T _i Outside temperature at point i R _i Sun's orientation and solar radiation at point i Weather-related information at point i Auxiliary power consumption calculation function

is an auxiliary power consumption calculation function. For example, may represent a function that calculates a predicted value for auxiliary power to be consumed during the interval between point i-1 and point i (e.g., power to be consumed by the air conditioning system).

In the example shown in FIG. 6 , the vehicle control device controls the outside temperature, orientation of the sun, and solar radiation of the vehicle 610 at point x and the outside temperature of the vehicle 610 at point ), and solar radiation (predicted value) By applying , you can calculate the predicted value for the power that the air conditioning system will consume during x~x+1. The vehicle control device may calculate a predicted value for power to be consumed by the air conditioning system for different sections. The vehicle control device sums the predicted values calculated for each of the sections (x~x+1, x+1~x+2, …, N-1~N) can be calculated.

Depending on the implementation, the vehicle control device may In order to increase accuracy, the heat generated inside the vehicle 630 can be further considered. This is explained in detail below.

There are various causes of heat generated inside the vehicle 610. For example, direct solar radiation, diffuse solar radiation, reflected solar radiation, exterior (or surrounding the vehicle) (ambient), ventilation (630), and people (drivers and/or Heat may be generated inside the vehicle 610 by one or more of the vehicles 640 (or passengers).

Table 6 below shows the heat generated inside the vehicle and shows.

Heat from direct solar radiation

-
-
-
- , A=1018, B=0.207, and β=sun altitude angle.
- Heat from scattered solar radiation

=수평면에 대한 각도(angle with the horizontal surface). 달리 표현하면, 차량의 위치의 수평면과 하늘 사이의 각도

-
- C = 0.136 and

=angle with the horizontal surface. In other words, the angle between the horizontal plane of the vehicle's position and the sky. Heat from reflected solar radiation

-
- , (ground reflectivity coefficient) heat from outside

- U=heat transfer coefficient (W/m ² -K), 10≤U≤100
- T _s = surface temperature of the vehicle
- T=cabin temperature Heat caused by ventilation

-
- c _p =specific heat=1005
- T _init = initial cabin temperature
- T=temperature inside vehicle human-generated fever

- H _pr =heat production rate (W/m ² )=58.2
H _pr can be divided into H _pr (for driver)=85 and H _pr (for passenger)=55.
- A _Du = Du Bois area (m ² )
Average Du Bois area for adults = 1.8 m ²
A more accurate Du Bois area is:
. Here, W=mass, H=height.

The temperature inside the vehicle (or the temperature in the driver's seat) can be determined based on Equation 8 below.

[Equation 8]

In Equation 8, m is the mass of air, and C _room represents the specific heat of air.

If heat transfer efficiency is considered in Equation 8, the power or energy required to maintain the optimal temperature within the vehicle can be derived. The derived power is can represent.

In one embodiment, the vehicle control device determines the power to be consumed by the vehicle 610. + can be predicted. In other words, the vehicle control device calculates the power that the vehicle 610 will consume to drive from the current point x to the destination. + can be predicted.

The vehicle control device may determine the driving range of the vehicle based on the predicted power. Here, the predicted power is or + It can be. The predicted power is not limited to the foregoing. Below, determination of the vehicle's drivable range will be explained.

The vehicle control device may determine the drivable range of the vehicle based on the predicted power and current state information of the battery (eg, State of Charge (SOC)). For example, the vehicle control device can predict the SOC at the destination by subtracting the SOC corresponding to the predicted power from the current SOC. In other words, the vehicle control device can predict the remaining SOC corresponding to the SOC when the vehicle arrives at the destination. If the SOC at the destination is less than a predetermined standard (e.g., a value within 0 to 1%), the vehicle control device may determine that the vehicle cannot drive to the destination with the current SOC. In this case, the vehicle control device can display information about charging stations located on the route on the vehicle's display. If the SOC at the destination is more than a predetermined standard, the vehicle control device may display a message on the display indicating that the vehicle can drive to the destination with the current SOC. Additionally, if the SOC at the destination is greater than or equal to a predetermined standard, the vehicle control device may determine whether round-trip driving with the current SOC is possible. If round-trip driving is not possible with the current SOC, the vehicle control device may display information about charging stations located on the return route on the display.

Depending on the implementation, the vehicle control device may predict the amount of fuel the vehicle will consume based on the second speed profile. The vehicle control device may determine the driving range of the vehicle based on the predicted fuel amount and the current fuel amount. For example, the vehicle control device can predict the fuel amount at the destination by subtracting the predicted fuel amount from the current fuel amount. If the fuel amount at the destination is less than a predetermined standard (e.g., a value within 0 to 1L), the vehicle control device may determine that the destination cannot be reached with the current fuel amount. If the vehicle cannot drive to the destination with the current amount of fuel, the vehicle control device may display a message indicating that refueling is necessary and/or gas station information (eg, gas station location information) on the display. If the amount of fuel at the destination is more than a predetermined standard, the vehicle control device may determine whether a round trip is possible with the current amount of fuel. If a round trip is not possible with the current fuel amount, the vehicle control device may display information on a gas station located on the return route on the display.

FIG. 7 is a diagram illustrating another example of driving-related information generated based on a second speed profile according to an embodiment.

Another example of driving-related information may be guide information for driving.

The vehicle control device may generate guide information 710 based on the second speed profile and display the guide information 710 on the display.

In one embodiment, the vehicle control device may derive a predicted average speed in a subsequent section of the current driving section from the second speed profile. For example, assuming that the vehicle is currently traveling in the first section of the freeway, the vehicle control device may derive the predicted average speed in the section after the first section of the freeway from the second speed profile. Referring to the example explained in FIG. 4, when a vehicle is said to be driving in a section (x+1 to x+2) of a freeway, the vehicle control device operates in a section (for example, after the section (x+1 to , the predicted average speed at x+2~x+3 or x+2~x+6) can be derived. Additionally, the vehicle control device may derive the target speed for the current driving section from driving history information (eg, previous speed profile, battery charge/discharge number, accident history, etc.). For example, the vehicle control device can derive the target speed for the freeway through driving history information. The vehicle control device may compare the predicted average speed to the target speed. If the predicted average speed is greater than the target speed, the vehicle control device may generate guide information 710 including information about the speed reduction and the target speed. If the predicted average speed is less than or equal to the target speed, the vehicle control device may generate guide information 710 for maintaining the current driving speed.

In another embodiment, the vehicle control device may identify a speed section that satisfies a predetermined criterion in the second speed profile. A speed section that satisfies a predetermined standard may include, for example, a speed section that may affect the lifespan of the battery. The lifespan of the battery may deteriorate rapidly due to rapid acceleration and/or rapid deceleration of the vehicle. Accordingly, the speed section that can affect the life of the battery may represent a section where rapid acceleration or rapid deceleration of the vehicle is expected. The speed range that can affect the life of the battery is not limited to the above. The vehicle control device may generate guide information 710 for driving on a path corresponding to the identified speed section. For example, the vehicle control device may display guide information 710 to drive safely on the path corresponding to the identified speed section. Accordingly, the vehicle control device can guide driving according to the life status of the battery.

Since the matters described through FIGS. 1 to 6 can be applied to the matters described through FIG. 7, detailed description is omitted.

Figure 8 is a block diagram for explaining a vehicle control device according to an embodiment.

Referring to FIG. 8, the vehicle control device 800 includes a controller 810 and a memory 820.

The controller 810 calculates the amount of change in speed of the vehicle based on the input information.

The controller 810 predicts the average speed of the vehicle based on the calculated speed change.

Controller 810 generates a first speed profile based on the predicted average speed.

The controller 810 generates a second speed profile by applying speed noise information to the first speed profile.

Memory 820 stores one or more instructions related to the operation of controller 810. Additionally, the memory 820 may store the speed change calculation model described with reference to FIG. 2 above.

Since the matters described through FIGS. 1 to 7 can be applied to the matters described through FIG. 8, detailed description will be omitted.

The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., singly or in combination. Program instructions recorded on the medium may be specially designed and configured for the embodiment or may be known and available to those skilled in the art of computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. -Includes optical media (magneto-optical media) and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, flash memory, etc. Examples of program instructions include machine language code, such as that produced by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc. The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the embodiments, and vice versa.

Although the embodiments have been described with limited drawings as described above, those skilled in the art can apply various technical modifications and variations based on the above. For example, the described techniques are performed in a different order than the described method, and/or components of the described system, structure, device, circuit, etc. are combined or combined in a different form than the described method, or other components are used. Alternatively, appropriate results may be achieved even if substituted or substituted by an equivalent.

Therefore, other implementations, other embodiments, and equivalents of the claims also fall within the scope of the following claims.

Claims (24)

calculating a change in speed of the vehicle based on input information;
predicting the average speed of the vehicle based on the calculated speed change;
generating a first speed profile based on the predicted average speed; and
Generating a second speed profile by applying speed noise information for expressing acceleration or deceleration of the vehicle to the first speed profile.
Including,
How a vehicle control device operates.
According to paragraph 1,
The step of calculating the change in speed of the vehicle is,
Calculating a speed change corresponding to each point on the vehicle's path based on input information related to each point.
Including,
How a vehicle control device operates.
According to paragraph 1,
The input information above is,
including weather information, traffic flow information, and road type information,
How a vehicle control device operates.
According to paragraph 1,
The step of predicting the average speed of the vehicle is,
Predicting the average speed of the vehicle at each point using the speed change amount corresponding to each point on the route of the vehicle and the reference speed of each point.
Including,
How a vehicle control device operates.
According to paragraph 1,
The step of generating the first speed profile is,
generating the first speed profile based on the average speed predicted for each point on the vehicle's path.
Including,
How a vehicle control device operates.
According to paragraph 1,
Predicting power to be consumed by the vehicle based on the second speed profile
Containing more,
How a vehicle control device operates.
According to paragraph 1,
predicting power to be delivered to the power train of the vehicle based on the second speed profile; and
Predicting the power to be consumed by the air conditioning system of the vehicle based on at least one of solar radiation information and outside temperature information.
Containing more,
How a vehicle control device operates.
According to paragraph 1,
Determining the driving range of the vehicle based on at least one of current state information of the battery unit of the vehicle and the current fuel amount of the vehicle and a predicted value for power to be consumed by the vehicle.
Containing more,
How a vehicle control device operates.
According to clause 8,
The step of determining the driving range of the vehicle is,
predicting at least one of state information and fuel amount of the battery unit at a destination based on the predicted value for power; and
Determining whether the vehicle can drive to the destination through at least one of the predicted state information and the predicted fuel amount
Including,
How a vehicle control device operates.
According to paragraph 1,
generating guide information for driving of the vehicle based on the second speed profile; and
Step of visually outputting the guide information
Containing more,
How a vehicle control device operates.
According to clause 10,
The step of generating the guide information is,
Comparing a predicted average speed derived from the second speed profile and a target speed derived from driving history information of the vehicle; and
Generating guide information based on a comparison result between the derived predicted average speed and the derived target speed.
Including,
How a vehicle control device operates.
According to clause 10,
The step of generating the guide information is,
identifying a speed section that satisfies a predetermined standard in the second speed profile; and
Generating guide information for driving on a path corresponding to the identified speed section
Including,
How a vehicle control device operates.
controller; and
Memory containing at least one instruction executable by the controller
Including,
When the at least one command is executed in the controller, the controller calculates a change in speed of the vehicle based on input information, predicts an average speed of the vehicle based on the calculated change in speed, and predicts the average speed of the vehicle. Generating a first speed profile based on and generating a second speed profile by applying speed noise information for expressing acceleration or deceleration of the vehicle to the first speed profile,
Vehicle control device.
According to clause 13,
The controller is,
Calculating the amount of change in speed corresponding to each point on the path of the vehicle based on input information related to each point,
Vehicle control device.
According to clause 13,
The input information above is,
including weather information, traffic flow information, and road type information,
Vehicle control device.
According to clause 13,
The controller is,
Predicting the average speed of the vehicle at each point using the speed change amount corresponding to each point on the path of the vehicle and the reference speed of each point,
Vehicle control device.
According to clause 13,
The controller is,
Generating the first speed profile based on the average speed predicted for each point on the vehicle's path,
Vehicle control device.
According to clause 13,
The controller is,
Predicting power to be consumed by the vehicle based on the second speed profile,
Vehicle control device.
According to clause 13,
The controller is,
Based on the second speed profile, predicting power to be delivered to the power train of the vehicle, and predicting power to be consumed by the air conditioning system of the vehicle based on at least one of solar radiation information and outside temperature information,
Vehicle control device.
According to clause 13,
The controller is,
Determining the driving range of the vehicle based on at least one of the current state information of the battery unit of the vehicle and the current fuel amount of the vehicle and a predicted value for power to be consumed by the vehicle,
Vehicle control device.
According to clause 20,
The controller is,
Predict at least one of the state information and fuel amount of the battery unit at the destination based on the predicted value for the power, and determine whether the vehicle can drive to the destination through at least one of the predicted state information and the predicted fuel amount. doing,
Vehicle control device.
According to clause 13,
The controller is,
Generating guide information for driving of the vehicle based on the second speed profile and visually outputting the guide information,
Vehicle control device.
According to clause 22,
The controller is,
The predicted average speed derived from the second speed profile is compared with the target speed derived from the driving history information of the vehicle, and based on the comparison result between the derived predicted average speed and the derived target speed, guide information is provided. generating,
Vehicle control device.
According to clause 22,
The controller is,
Identifying a speed section that satisfies a predetermined standard in the second speed profile and generating guide information for driving on a path corresponding to the identified speed section,
Vehicle control device.

Images