Energy consumption prediction device, energy consumption prediction system, energy consumption prediction method, and energy consumption prediction program

Abstract

To provide an energy consumption prediction device for a vehicle capable of more accurately predicting energy consumption of the vehicle.SOLUTION: The travel energy prediction device includes a processor configured to acquire information indicating a scheduled travel route of a vehicle, specify a travel resistance applied to the vehicle when the vehicle travels on the scheduled travel route based on the information indicating the scheduled travel route, specify a travel output required for driving a drive source of the vehicle when the vehicle travels on the scheduled travel route based on the information indicating the scheduled travel route, and output energy consumption when the vehicle travels on the scheduled travel route based on the travel resistance and the travel output.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present invention relates to an energy consumption prediction device, an energy consumption prediction system, an energy consumption prediction method, and an energy consumption prediction program. [Background technology]

[0002] Vehicles require prediction of energy consumption for operation planning and charge management. Patent Document 1 discloses that the amount of energy consumed by an EV vehicle while traveling is calculated based on acceleration usage rate data corrected with route information that changes during travel and energy consumption data. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2014-202643 Summary of the Invention [Problem to be solved by the invention]

[0004] A vehicle encounters various resistances while traveling. The amount of power consumed by the vehicle varies depending on the amount of resistance, but the destination arrival estimation device of Patent Document 1 does not take this into consideration sufficiently.

[0005] An object of the present invention is to provide an energy consumption prediction device, an energy consumption prediction system, an energy consumption prediction method, and an energy consumption prediction program that are capable of more accurately predicting the energy consumption of a vehicle. [Means for solving the problem]

[0006] According to one aspect of the present invention, an energy consumption prediction device includes a processor that acquires information indicating a planned driving route of a vehicle, determines, based on the information indicating the planned driving route, the driving resistance that will be exerted on the vehicle when the vehicle travels along the planned driving route, determines, based on the information indicating the planned driving route, the driving output required to drive the vehicle's drive source when the vehicle travels along the planned driving route, and outputs, based on the driving resistance and the driving output, the energy consumption when the vehicle travels along the planned driving route. [Effects of the Invention]

[0007] According to the present invention, it is possible to provide an energy consumption prediction device, an energy consumption prediction system, an energy consumption prediction method, and an energy consumption prediction program that are capable of more accurately predicting the energy consumption of a vehicle. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a schematic diagram showing a vehicle energy consumption prediction system according to an embodiment; [Figure 2] 1 is a schematic diagram showing a garbage truck (compactor truck) as an example of a vehicle. [Figure 3] Graphs showing the relationship between the vehicle's body operation time and the weight of garbage, the relationship between the vehicle's body operation time and the amount of energy consumed by the body when collecting garbage, and the relationship between the vehicle's body operation time and the amount of energy consumed by the body when discharging garbage. [Figure 4] FIG. 2 is a diagram showing a processing flow of the system shown in FIG. [Figure 5] FIG. 5 is a schematic diagram for explaining the processing flow shown in FIG. 4. DETAILED DESCRIPTION OF THE INVENTION

[0009] FIG. 1 is a schematic diagram of a system (hereinafter mainly referred to as the system) 1 for predicting energy consumption of a vehicle 2 according to an embodiment of the present invention. FIG. 2 is a schematic diagram showing an example of a vehicle 2 having a body. FIG. 3(A) is a graph showing the relationship between the operation time of the body of the vehicle 2 and the weight of garbage, FIG. 3(B) is a graph showing the relationship between the operation time of the body of the vehicle 2 and the amount of energy consumed by the body when collecting garbage, and FIG. 3(C) is a graph showing the relationship between the operation time of the body of the vehicle 2 and the amount of energy consumed by the body when discharging garbage. FIG. 4 is a diagram showing the processing flow of the system 1.

[0010] As shown in FIG. 1, the system 1 includes n vehicles 2a to 2n (n is an integer equal to or greater than 1) and an information processing server (vehicle energy consumption prediction device) 3 configured to be able to communicate with the vehicles 2a to 2n via a network N.

[0011] In the following description, when the n vehicles 2a to 2n are described without distinction, some of the reference numerals will be omitted and they will simply be referred to as "vehicle 2." It should be noted that the vehicles 2a to 2n are preferably vehicles of the same model with the same mounting, but may also be vehicles of different models with the same mounting, for example.

[0012] The vehicle 2 is preferably a vehicle having a body in addition to the cab 12 and chassis 14. The vehicle 2 is, for example, a cargo truck or a garbage truck. Cargo trucks include, for example, flatbeds, vans, dump trucks, tractor-trailers, etc. The total weight of these vehicles 2 can change due to, for example, loading and unloading of luggage, garbage, etc.

[0013] In this embodiment, the vehicle 2 is mainly described as a refuse truck, but it may be a delivery truck or any other vehicle whose total weight can change due to the loading and unloading of goods.

[0014] In this embodiment, what is called dust is referred to as "garbage" or "trash," but these have the same meaning.

[0015] As shown in Figures 1 and 2, the vehicle 2 has, in addition to a cab 12 and a chassis 14, an ECU (Electronic Control Unit) 16, a communication unit 18, a battery 20, a motor 22, a dust storage unit 24, a dust collection unit 26, and an input unit 28.

[0016] The vehicle 2 according to this embodiment may be, for example, an engine vehicle such as a diesel engine vehicle, an HEV vehicle, a PHEV vehicle, or an FCEV vehicle, or an EV vehicle. Here, the vehicle 2 is described as an EV vehicle, and an ECU 16, a communication unit 18, a battery 20, a motor 22, a dust container 24, and a dust collector 26 are arranged on a chassis 14. Of these, the dust container 24 and the dust collector 26 are arranged as truck bodywork.

[0017] The ECU 16 is a computer (control unit) of the vehicle 2 that controls each part of the vehicle 2. The ECU 16 controls the overall operation of the vehicle 2 in accordance with programs stored in a storage unit of the ECU 16. For example, the ECU 16 is configured with electronic circuits such as one or more processors, such as a CPU. The ECU (processor) 16 executes various programs stored in the storage unit of the ECU 16 to realize appropriate functions and perform various operations.

[0018] There may be one ECU 16 in the vehicle 2, or there may be multiple ECUs in the vehicle 2, one for controlling the various parts related to vehicle running and one for controlling the mounted equipment such as the garbage collection unit 26. For simplicity of explanation, the following will explain an example in which there is one ECU 16. Note that even if the ECU 16 is divided into one for controlling the various parts related to vehicle running and one for controlling the mounted equipment such as the garbage collection unit 26, these control the vehicle 2 in the same way as when there is one ECU.

[0019] The communication unit 18 transmits and receives various information signals relating to the vehicle 2 to and from a server (computer) 3 of the system 1 via the network N.

[0020] The battery 20 supplies appropriate power to the ECU 16, the communication unit 18, the motor 22, the dust collection unit 26, etc., as controlled by the ECU 1.

[0021] The motor 22 is used as a drive source for moving the wheels 14 a of the vehicle 2 using electric power from the battery 20 .

[0022] The dust storage section 24 is provided, for example, between the cab 12 and the dust collection section 26, and is formed as a container for storing dust.

[0023] The dust collecting unit 26 operates the hydraulic device of the dust collecting unit 26 using power from the battery 20 to store dust in the dust storage unit 24. The dust collecting unit 26 also operates the hydraulic device of the dust collecting unit 26 using power from the battery 20 to discharge dust from the dust storage unit 24 to the outside of the vehicle 2. For this reason, the dust collecting unit 26 can switch between a mode in which dust is stored in the dust storage unit 24 and a mode in which dust stored in the dust storage unit 24 is discharged to the outside. In this embodiment, for simplicity of explanation, the operation of either mode will be described as the hydraulic device of the dust collecting unit 26 being operated by pressing a switch of the dust collecting unit 26.

[0024] The mechanism of the dust collection unit 26 when storing dust in the dust storage unit 24 may be, for example, a winding type (rotating plate type), a press type (compression plate type), a rotary type using a drum, or the like, and any of these may be used. In this embodiment, the mechanism of the dust collection unit 26 in the collection mode is a rotary type.

[0025] The garbage storage section 24 and the garbage collection section 26 may be arranged at the position shown by the dashed line, for example, in a garbage incineration plant, or the garbage collection section 26 may be arranged at the position shown by the dotted line, for example, in a garbage incineration plant, so that the garbage stored in the garbage storage section 24 can be easily discharged.

[0026] In this embodiment, the bodywork of the vehicle 2 (for example, the hydraulic device of the garbage collection unit 26) is moved to sequentially discharge the garbage stored in the garbage storage unit 24 to the outside of the vehicle 2. The mechanism for discharging garbage from the garbage storage unit 24 may be a rotary type that reverses the rotation of the drum described above, a push type that moves a discharge plate (not shown), or a dump type that lifts the garbage storage unit 24 using, for example, a hoist mechanism (not shown), and any of these may be used.

[0027] For example, when using the dump type, the dust container 24 is tilted using a hoist mechanism, and the dust collection unit 26 is rotated relative to the dust container 24 to open the dust container 24, and the dust can be discharged. Also, when using the dump type, the dust container 24 and the dust collection unit 26 of the vehicle 2 move between the positions shown by the solid lines and the dashed lines in Fig. 2. When using the push type, the dust collection unit 26 is rotated relative to the dust container 24, as shown by the two-dot chain line in Fig. 2, to open the dust container 24, and the dust can be discharged using the discharge plate.

[0028] In this embodiment, the input unit 28 is used for input when selecting a mode from a selection mode (for example, a first mode for collecting household waste, a second mode for collecting waste at an event venue, or a third mode). The input unit 28 may be located, for example, in the cab 12, the waste storage unit 24, or the waste collection unit 26. In addition, an information terminal such as a smartphone carried by the worker can be used as the input unit 28 connected via the communication unit 18, for example.

[0029] In the first mode, the vehicle 2's body (the hydraulic device of the garbage collection unit 26) is repeatedly operated for a period of time in which each operation time is shorter than a predetermined time, and during a series of garbage collection operations, the hydraulic device of the garbage collection unit 26 is operated intermittently to collect garbage at multiple locations.

[0030] In the second mode, the vehicle 2's body (hydraulic device of the garbage collection unit 26) is operated continuously for a predetermined time or more, or the vehicle 2 is moved within a predetermined distance range and the hydraulic device of the garbage collection unit 26 is repeatedly operated intermittently for a period of time that is shorter than the predetermined time, thereby collecting garbage. When the body is operated intermittently in the second mode, the movement of the vehicle 2 is limited to a predetermined amount or less.

[0031] The operator of vehicle 2 drives vehicle 2 to, for example, one or multiple predetermined garbage collection locations, stops vehicle 2, and then operates the hydraulic device of garbage collection unit 26 to store garbage in garbage storage unit 24. The operator also drives vehicle 2 to, for example, a predetermined garbage incineration plant, stops vehicle 2, and then operates the hydraulic device of garbage collection unit 26 to discharge the garbage stored in garbage storage unit 24 to the outside, for example, at the garbage incineration plant. In this way, vehicle 2 consumes power from battery 20, for example, when traveling to one or multiple locations to collect garbage, when traveling to the garbage incineration plant or the like to discharge the garbage after garbage collection, and when garbage collection unit 26 is operating (during collection and discharge).

[0032] Here, the running resistance R total (N) can be expressed as the following equation (1).

[0033]

number

[0034] Rr(N) is the rolling resistance, Ra(N) is the air resistance, Rg(N) is the gradient resistance, and Ri(N) is the acceleration resistance. total As a result, the vehicle 2 consumes power from the battery 20 while running (moving).

[0035] The rolling resistance Rr mainly refers to the resistance generated by energy loss due to deformation of the tires of the vehicle 2. The rolling resistance Rr can be expressed by the following equation (2).

[0036]

number

[0037] where μ r is the rolling resistance coefficient, where g is the gravitational acceleration (m / s 2 ) and rolling resistance coefficient μ r is affected by, for example, road surface conditions (pavement material, wet / dry, etc.), tires (type, air pressure), wheel load, and wheel bearing conditions (grease temperature). test is the total weight (kg) of the vehicle 2 including the bodywork, luggage, and garbage. Note that the total weight preferably includes the weight of the workers who will be riding in the vehicle 2. The rolling resistance Rr increases in proportion to the total weight of the vehicle 2. The rolling resistance Rr is affected not only by the weight of the vehicle 2 itself, but also by the weight of the luggage and garbage.

[0038] The air resistance Ra refers to the resistance generated by friction between the surface of the vehicle 2, including the bodywork, and the air. The air resistance Ra can be expressed by the following formula (3).

[0039]

number

[0040] where μ a is the air resistance coefficient (N m -2 (km / h) -2 ) to the frontal projection area of ​​vehicle 2 (m 2 ) is a coefficient multiplied by μ a varies depending on the shape of the front of the vehicle 2 (cab 12, chassis 14, and bodywork (garbage storage section 24, etc.)). x is the traveling speed (km / h) of vehicle 2. Air resistance Ra increases in proportion to the square of the vehicle speed. Therefore, it can be seen that the faster the speed of vehicle 2, the greater the power consumption while traveling.

[0041] Grade resistance Rg refers to the resistance that occurs when going uphill, for example. Grade resistance Rg can be expressed as the following equation (4).

[0042]

number

[0043] where m test is the total weight (kg) of vehicle 2 including the bodywork, luggage, and garbage of vehicle 2, and g is the weight acceleration (m / s 2 ), where β in sinβ (see Figure 5) is the inclination angle of the road surface relative to the horizontal plane. Grade resistance Rg is proportional to the total weight of vehicle 2 and sinβ of the inclination angle β. Therefore, grade resistance Rg is affected not only by the weight of vehicle 2 itself, but also by the weight of luggage and debris. Furthermore, grade resistance Rg changes according to changes in the gradient at the location where vehicle 2 is traveling. For this reason, it can be seen that as the weight of luggage and debris increases when vehicle 2 is traveling, and as the gradient increases, the power consumption during traveling increases.

[0044] Acceleration resistance Ri refers to the resistance that occurs when accelerating. Acceleration resistance Ri can be expressed as the following equation (5).

[0045]

number

[0046] where m test is the total weight (kg) of vehicle 2 including bodywork, luggage and garbage, and Δm drv+eng is the inertia equivalent weight (kg) of the rotating parts of the drive mechanism. When accelerating, the rotating parts of the drive mechanism must accelerate the engine, transmission, propeller, differential, and rear wheels, and this is converted into weight. x is the vehicle speed (km / h) and indicates acceleration in equation (5). Acceleration resistance Ri is proportional to the acceleration and the weight of vehicle 2. Acceleration resistance Ri is affected not only by the weight of vehicle 2 itself, but also by the weight of luggage, garbage, etc.

[0047] Therefore, the running resistance R totalis affected by the weight of the vehicle 2 itself, the weight of the worker, as well as the weight of the luggage and garbage. total When the value of the electric power consumption (energy) increases, the electric power consumption (energy) of the vehicle 2 increases while the vehicle 2 is moving (driving), and the electric power consumption decreases.

[0048] FIG. 1 is a block diagram showing a schematic configuration example of an information processing server 3 according to this embodiment.

[0049] The server 3 is a computer including a control unit 31, a storage unit 32, and a communication unit 33. The control unit 31, the storage unit 32, and the communication unit 33 are connected to each other via a bus line.

[0050] The control unit 31 controls the overall operation of the information processing server 3 in accordance with the programs stored in the storage unit 32. For example, the control unit 31 is configured with electronic circuits such as one or more processors. The control unit 31 is assumed to be, for example, a CPU. The control unit 31 executes various programs stored in the storage unit 32 to realize appropriate functions and perform various operations.

[0051] The storage unit 32 is composed of a main storage unit and an auxiliary storage unit. For example, the main storage unit is composed of a volatile memory that provides a working area for the processor. For example, the main storage unit is composed of a RAM (Random Access Memory) or the like. For example, the auxiliary storage unit is composed of a non-volatile memory that stores various information and programs for the operation of the information processing server 3. For example, the auxiliary storage unit is composed of an HDD (Hard Disk Drive) or an SSD (Solid State Drive) or the like. The storage unit 32 stores programs that cause the control unit 31 to realize various functions. In this embodiment, for example, the storage unit 32 stores an energy consumption prediction program for the vehicle 2, which is executed by the control unit 31. The server 3 obtains information on the relationships shown in the three graphs in FIG. 3 provided via the network N, and then stores the information in the storage unit 32. After completing a series of garbage collections, the server 3 preferably measures the weight of the vehicle 2, for example, at a garbage incineration plant, and then obtains the relationship between the cumulative operating time of the body and garbage weight information from at least some of the vehicles 2a to 2n, and updates the information in the graphs shown in Figures 3(A) to 3(C) stored in the memory unit 32.

[0052] FIG. 3(A) shows a graph with the horizontal axis representing the operating time of the waste collection unit 26 as a mounted unit and the vertical axis representing the weight of waste. The information shown in FIG. 3(A) is an example of information obtained when actually collecting household waste from multiple locations along a certain route, or when collecting waste after an event at a certain location or facility. For household waste, this information will differ depending on the local government, but it is preferable that it be available for each type of waste that is separated.

[0053] The operating time of the garbage collection unit 26 is the time that the garbage collector presses the switch of the garbage collection unit 26 and the hydraulic device of the garbage collection unit 26 operates using power from the battery 20. For example, when collecting household garbage, the hydraulic device of the garbage collection unit 26 operates continuously at each collection location, but it is rare that it continues to operate while moving to multiple locations; it is often operated intermittently by starting the hydraulic device of the garbage collection unit 26 at each collection location, stopping it, and then moving on. On the other hand, when collecting garbage at an event venue, for example, the hydraulic device of the garbage collection unit 26 often operates continuously.

[0054] Note that the graph in FIG. 3(A) shows that when collecting household waste (first mode), the weight tends to increase over a shorter operating time of the hydraulic device of the waste collection unit 26 compared to when collecting waste at an event venue (second mode). However, this is merely an example, and may vary depending on the type of waste. For example, the types of household waste vary depending on the local government, and can be categorized into, for example, plastic, PET bottles, metals, paper, and other waste. Therefore, the weight of waste collected by vehicle 2 varies depending on the type of waste and collection day. On the other hand, the types of waste at an event venue can be categorized into, for example, PET bottles, paper food and drink containers, plastic food and drink containers, and other waste. The weight of waste collected by vehicle 2 also varies depending on the items for sale at the event venue.

[0055] In addition, the graph shown in Figure 3(B) shows the relationship between the amount of energy consumed when collecting garbage and the operating time of the garbage compactor mounted as vehicle 2, and the graph shown in Figure 3(C) shows the relationship between the amount of energy consumed when discharging garbage and the operating time of the garbage compactor mounted as vehicle 2.

[0056] The communication unit 33 is configured with one or more communication interfaces capable of performing communication in accordance with any wireless communication standard. The communication unit 33 includes one or more communication interfaces capable of performing communication between the information processing server 3 and the vehicle 2 via the network N as described above.

[0057] The hardware configuration of the information processing server 3 is not limited to the above configuration. The information processing server 3 allows the omission or modification of the above components and the addition of new components as appropriate.

[0058] The system 1 is a so-called client-server system. The system 1 is realized by mutual communication between the ECUs 16 of n vehicles 2, which are clients, and the server 3 via a network N and communication units 18 and 33. The network N may be realized by, for example, the Internet, a network such as a mobile phone network, a LAN (Local Area Network), or a network that combines these.

[0059] The server 3 can receive information from, for example, a navigation API and a weather data API via the network N, and use this information in processing using various programs. The server 3 can also selectively obtain the relationships shown in the three graphs in Fig. 3 as additional weight information via the network N, and use this information in processing using various programs.

[0060] The calculation process of the energy consumption required for desired driving of the vehicle 2, which is realized by the control unit 31 of the information processing server 3, will be described with reference to Fig. 4. Note that each process realized by the control unit 31 here can also be said to be realized by a computer including a processor.

[0061] For example, assume that vehicle 2 inputs information to input unit 28 that the vehicle will travel from point A (distance 0) to point B while collecting garbage. ECU 16 of vehicle 2 transmits the information input to input unit 28 to control unit 31 of server 3. Control unit 31 of server 3 identifies vehicle 2 for which a prediction process for energy consumption required for a desired run is performed, and acquires vehicle information such as remaining charge information of battery 20 of the identified vehicle 2 and information affecting running resistance (step S1). In other words, ECU (control unit) 16 transmits to server (vehicle 2 energy consumption prediction device) 3 the status of motor (drive source) 22 provided in vehicle 2 for rotating wheels 14a and battery 20 for supplying energy for driving motor 22. Note that information affecting the running resistance of vehicle 2 includes, for example, the current total weight of vehicle 2 (including the weight of occupants), the frontal projection area of ​​vehicle 2, and the inertial equivalent weight of the rotating part of the drive mechanism of vehicle 2.

[0062] The control unit 31 of the server 3 obtains route information (information indicating the planned route of the vehicle 2) along which the vehicle 2 is scheduled to travel from the navigation API (step S2). The route information includes map information of the planned route, gradient information (altitude change information), traffic congestion information, speed limit information, etc. The route information also includes information (arrival time prediction information) regarding the time t2 at which the vehicle will arrive at point B when departing from point A (distance 0) at time t1.

[0063] The control unit 31 of the server 3 can calculate vehicle speed information from point A (distance 0) to point B based on the route information, and sets the vehicle speed for each point on the route (step S3).

[0064] In addition, the control unit 31 of the server 3 receives the running resistance R totalFor example, weather information that may affect road conditions along the route acquired by the navigation API is acquired from a weather API. Furthermore, the server 3 predicts the degree of increase in garbage weight using, for example, the relationship shown in the graph in FIG. 3(A) and information on the predicted operating time of the equipment (garbage collection unit 26) at each garbage collection location. The control unit 31 of the server 3 acquires information on the operation of the vehicle 2, for example, via the network N, and calculates predicted information on the weight of the vehicle 2 or predicted information on weight changes.

[0065] Then, the rolling resistance Rr based on the formula (2), the air resistance Ra based on the formula (3), the gradient resistance Rg based on the formula (4), and the acceleration resistance Ri based on the formula (5) are calculated, and the running resistance R based on the formula (1) is calculated. total Calculate the running resistance R total The total weight of the vehicle 2, which affects the running resistance R, changes as the garbage is collected at each collection point. total The gradient and road surface conditions on the route that affect the running resistance R total is given as a function of time that changes over time (step S4). That is, the control unit 31 of the server 3 identifies the running resistance that the vehicle 2 experiences when it travels along the planned travel route, based on the information indicating the planned travel route.

[0066] The control unit 31 of the server 3 calculates the power output required for the vehicle 2 to travel from point A to point B (step S5). That is, based on the information indicating the planned travel route, the control unit 31 of the server 3 specifies the travel power output required to drive the motor 22, which is the drive source of the vehicle 2, when the vehicle 2 travels along the planned travel route. To this end, the control unit 31 of the server 3 calculates the travel power output required to drive the motor (drive source) 22 that rotates the wheels 14a of the vehicle 2 to obtain the planned vehicle speed when the vehicle 2 travels along the planned travel route. The horizontal axis of the graph showing "Calculation of power output required for travel" shown in FIG. 5 is the planned time for the vehicle 2 to travel from point A to point B, and the vertical axis is the torque required at each time of the motor 22, which is used as the drive source to move the wheels 14a.

[0067] When acquiring vehicle information about the vehicle 2, the control unit 31 of the server 3 acquires, for example, the type of motor 22 of the vehicle 2, the number of years of use, and the distance traveled using the motor 22 (the cumulative number of rotations of the motor). For example, in the graph shown in FIG. 5, "Calculation of Various Efficiencies," the horizontal axis represents the number of rotations per unit time [rad / s] of the motor 22, and the vertical axis represents the torque [Nm] of the motor 22. Such characteristics (motor efficiency) vary depending on the type of motor 22, the number of years of use, the distance traveled, and the like. The control unit 31 of the server 3 calculates the motor efficiency of the motor 22, for example, using an appropriate coefficient (step S6). Note that, for example, if the coefficient uses the motor efficiency of the motor 22, the control unit 31 of the server 3 can determine this coefficient for each vehicle 2.

[0068] In step S6, the server 3 calculates various efficiencies. These efficiencies include, for example, calculating the influence of the relationship between the amount of energy consumed by the vehicle 2's body during garbage collection and the operation of the body of the vehicle 2, as shown in FIG. 3(B), and / or the relationship between the amount of energy consumed by the vehicle 2's body during garbage discharge from the vehicle 2's body to the outside of the vehicle 2, as shown in FIG. 3(C). For this reason, the server 3 calculates the planned operation time of the vehicle 2's body when the vehicle 2 is a garbage truck, and the planned energy consumption of the body during the planned operation time. Therefore, in step S6, the control unit 31 of the server 3 calculates various efficiencies, for example, as appropriate coefficients, based on the amount of energy consumed by the vehicle 2's body in addition to the motor efficiency of the motor 22.

[0069] The control unit 31 of the server 3 calculates the energy consumption required for the vehicle 2 to travel, for example, from point A to point B (step S7) using the power required for travel obtained in step S5 and the coefficient calculated in step S6. The predicted energy consumption here is preferably output as a single value, but the coefficient calculated in step S6 may be a coefficient that includes unknown conditions of the vehicle 2 and output as a value within an appropriate range. If the vehicle 2 is a garbage truck, for example, the energy consumption calculated by the server 3 when traveling from point A to point B while collecting garbage at multiple locations includes the energy consumption required to operate the vehicle 2's equipment, in addition to the energy required for travel, which reflects the effect of running resistance.

[0070] The control unit 31 of the server 3 accurately estimates the total weight of the vehicle 2 including weight changes, the gradient of the planned travel route, and the planned vehicle speed on the planned travel route, and uses these to predict (calculate) the energy consumption, thereby improving the prediction accuracy of the energy consumption of the vehicle 2. This allows the operator of the vehicle 2 to use the server (vehicle 2 energy consumption prediction device) 3 to realize a highly accurate operation plan (route optimization) for the vehicle 2, which can lead to reduced operation costs of the vehicle 2 and reduced energy consumption.

[0071] Furthermore, the control unit 31 of the server 3 can output whether or not the vehicle 2 can travel from point A to point B, where the vehicle 2 is scheduled to travel, without charging the battery 20, based on the calculated energy consumption and the current remaining charge of the battery 20. This allows the user of the server 3 to perform energy management for the vehicle 2. Furthermore, if the control unit 31 of the server 3 determines that the vehicle 2 cannot travel from point A to point B, where the vehicle 2 is scheduled to travel, without charging the battery 20, the control unit 31 can perform charging management by incorporating a new charging facility that can charge the battery 20 of the vehicle 2 as a stopover point between point A and point B. If there are multiple charging facilities, the control unit 31 of the server 3 can output (suggest) an optimal charging facility as a stopover point, taking into consideration the total weight of the vehicle 2, including weight changes, the gradient of the planned travel route, the planned vehicle speed on the planned travel route, and the like.

[0072] Therefore, according to this embodiment, it is possible to provide a vehicle 2 energy consumption prediction device (server) 3, a vehicle 2 energy consumption prediction system 1, a vehicle 2 energy consumption prediction method, and a vehicle 2 energy consumption prediction program, which are capable of more accurately predicting the energy consumption of the vehicle 2.

[0073] In the present embodiment, an example has been described in which running resistance, including the rolling resistance of the vehicle's tires, the air resistance of the vehicle, the gradient resistance generated when the vehicle climbs a slope, and the acceleration resistance generated when the vehicle accelerates, is calculated using prediction information on the weight of the vehicle 2, information on altitude changes along the planned travel route of the vehicle 2, and the average vehicle speed calculated from the distance of the planned travel route and the average required time, or the planned vehicle speed calculated from the distance of the planned travel route and the planned required time. According to the present embodiment, by specifying the running resistance based on at least one of the prediction information on the weight of the vehicle 2, information on altitude changes along the planned travel route of the vehicle 2, and the vehicle speed calculated from the distance of the planned travel route and the average required time or the planned required time, it is possible to provide an energy consumption prediction device (server) 3 for the vehicle 2, an energy consumption prediction system 1 for the vehicle 2, a method for predicting energy consumption of the vehicle 2, and a program for predicting energy consumption of the vehicle 2, which are capable of predicting the energy consumption of the vehicle 2 with appropriate accuracy. For this reason, when predicting the energy consumption of the vehicle 2, it is not necessarily necessary to have all of the predicted information on the weight of the vehicle 2, information on the elevation change of the planned travel route of the vehicle 2, and the planned vehicle speed calculated from the distance of the planned travel route and the average required time or the planned required time, but any one of these will contribute to higher accuracy in predicting the energy consumption of the vehicle 2. The energy consumption prediction device (server) 3 (processor) of the vehicle 2 calculates the running resistance R based on at least one piece of information on the distance of the planned travel route, the average required time or the planned required time, and the average vehicle speed or the planned vehicle speed. totalFurthermore, the energy consumption prediction device (server) 3 (processor) of the vehicle 2 determines the running resistance R based on two or more pieces of information on the weight of the vehicle 2 when the vehicle 2 travels along the planned travel route, at least one piece of information on the distance of the planned travel route, the average required time or planned required time, and the average vehicle speed or planned vehicle speed, and at least one piece of information on the altitude and road surface conditions along the planned travel route. total It is preferable to specify

[0074] Here, a garbage truck has been used as an example of vehicle 2. For example, vehicle 2 may also be a delivery vehicle. For example, a brief description will be given of a case in which some first delivery items loaded into vehicle 2 are delivered from a parking location (point A) where vehicle (delivery vehicle) 2 is parked, via a logistics base (point B) where a large number of delivery items are loaded, to the address or location of a first delivery destination (point C), and second delivery items are delivered to the address or location of a second delivery destination (point D).

[0075] The weight of the delivery items at the logistics base (point B) is measured or estimated, for example, by a system (equipment) of the logistics warehouse. Therefore, the control unit 31 of the server 3 acquires the total weight of the many delivery items to be delivered by the vehicle 2 from the logistics warehouse system, etc., and calculates the running resistance R total can be reflected in.

[0076] 4, the control unit 31 of the server 3 acquires vehicle information for the vehicle 2, as well as destination information for the multiple deliveries to be loaded at the logistics base and the weight of each delivery. Therefore, in step S1, the control unit 31 of the server 3 can acquire the total weight of the multiple deliveries to be loaded at the logistics base.

[0077] In step S2, the control unit 31 of the server 3 acquires route information for the vehicle 2 based on points A, B, C, and D. The order in which the vehicle 2 travels from point A to point B is determined without any conditions. Whether the vehicle 2 takes the first route from point B to point D via point C or the second route from point B to point C via point D can be determined based on, for example, the time required for delivery and the amount of energy consumed to complete the delivery. Here, it is assumed that the server 3 is set to place more importance on the amount of energy consumed than on the time required to complete the delivery.

[0078] As the vehicle 2 travels, the weight of the first delivery item will decrease at point C, and the weight of the second delivery item will decrease at point D. The control unit 31 of the server 3 calculates the running resistance for each of the first route and the second route based on the elevation difference (gradient) of the route and the degree of decrease in the weight of the delivery item, and further outputs (predicts) the energy consumption (steps S3-S7).

[0079] The control unit 31 of the server 3 can output a route that is calculated as optimal based on this energy consumption. Therefore, the control unit 31 of the server 3 can present a highly accurate operation plan to the user of the vehicle 2.

[0080] For example, the change in the total weight of vehicle 2 on the route after leaving the logistics base may be determined using information obtained from a weight sensor attached to some of vehicles 2a-2n managed by server 3. Furthermore, for example, the weight of the vehicle 2 decreases each time a delivery is delivered from the logistics base (point B) to a destination. Server 3 can estimate the change in the weight of the delivery by, for example, obtaining the number of times a door equipped with an opening / closing sensor (not shown) on the body (luggage compartment) of vehicle 2 is opened and closed from ECU 16 that controls the opening / closing sensor. The change in the total weight of vehicle 2 can be estimated using, for example, information obtained from ECU 16 of vehicle 2 during travel and operation. Information related to the weight of vehicle 2 includes information indicating the change in weight due to the weight of items loaded on vehicle 2 while traveling along the planned travel route. In this way, server 3 may obtain, for example, the relationship between the number of delivery destinations and the weight information of all deliveries, or the relationship between the number of times the doors of vehicle 2 are opened and closed and the weight of the deliveries. By using this information, it is possible to provide a vehicle 2 energy consumption prediction device (server) 3, a vehicle 2 energy consumption prediction system 1, a vehicle 2 energy consumption prediction method, and a vehicle 2 energy consumption prediction program, which can calculate running resistance using the weight lost at each delivery destination and more accurately predict the energy consumption of the vehicle 2.

[0081] In addition, if the vehicle 2 is a delivery vehicle, the number of times the vehicle 2 is loaded is not limited to one time, and the vehicle 2 may load new deliveries while delivering deliveries to appropriate delivery destinations. In this case, the server 3 can also more accurately predict the energy consumption of the vehicle 2 by estimating the weight of the deliveries to be loaded as appropriate.

[0082] If the vehicle 2 is equipped with a weighing scale, for example, after loading items onto the body of the vehicle 2, the server 3 may be used to predict the energy consumption of the vehicle 2 up to the destination.

[0083] If the vehicle 2 is a delivery vehicle, the weight of the pallet carrying the delivery items may be obtained in addition to the weight of the delivery items and used to calculate the running resistance of the vehicle 2 at a given time.

[0084] When an engine vehicle such as a diesel vehicle, HEV vehicle, PHEV vehicle, or FCEV vehicle is used as the vehicle 2 described above instead of an EV vehicle, the engine can be used as a drive source instead of the motor 22. Furthermore, diesel or gasoline can be used as an energy source instead of the battery 20. For this reason, the server (the energy consumption prediction device for the vehicle 2) 3 can predict the electricity consumption as a prediction of the energy consumption of the EV vehicle as the vehicle 2, or can predict the fuel efficiency as a prediction of the energy consumption of the engine vehicle as the vehicle 2.

[0085] The server (vehicle energy consumption prediction device) 3 according to this embodiment has been described using one information processing server 3 as an example, but may be realized by a plurality of information processing servers 3 with functions distributed therebetween.

[0086] The present invention is not limited to the above-described embodiments, and various modifications can be made in the implementation stage without departing from the spirit of the invention. Furthermore, the embodiments may be implemented in appropriate combinations, in which case the combined effects can be obtained. Furthermore, the above-described embodiments include various inventions, and various inventions can be extracted by combining selected elements from the disclosed elements. For example, if the problem can be solved and the desired effect can be obtained even if some elements are deleted from all elements shown in the embodiments, the configuration from which these elements are deleted can be extracted as an invention. [Explanation of symbols]

[0087] 1...vehicle energy consumption prediction system, 2 (2a to 2n)...vehicle, 3...server (vehicle energy consumption prediction device), 12...cab, 14...chassis, 14a...wheel, 18...communication unit, 20...battery, 22...motor, 24...garbage storage unit, 26...garbage collection unit, 28...input unit, 31...control unit, 32...memory unit, 33...communication unit.

Claims

1. Obtain information indicating the planned route of the vehicle; Identifying a running resistance applied to the vehicle when the vehicle travels along the planned traveling route based on the information indicating the planned traveling route; determining a driving output required to drive a drive source of the vehicle when the vehicle travels along the planned driving route based on information indicating the planned driving route; outputting energy consumption when the vehicle travels along the planned travel route based on the travel resistance and the travel output; An energy consumption prediction device having a processor.

2. the processor determines the running resistance based on information about the weight of the vehicle when the vehicle travels along the planned travel route. The energy consumption prediction device according to claim 1 .

3. the information relating to the weight of the vehicle includes information indicating a change in weight due to the weight of an object carried on the vehicle while the vehicle is traveling along the planned travel route; The energy consumption prediction device according to claim 2 .

4. The weight of the vehicle includes the weight of the cab of the vehicle, the chassis including the drive source, and the weight of a body attached to the chassis. The energy consumption prediction device according to claim 2 .

5. the processor determines the running resistance based on at least one of information on altitude and road surface conditions on the planned traveling route. The energy consumption prediction device according to claim 1 .

6. The processor determines the running resistance based on at least one of information on the distance, average travel time, and average vehicle speed of the planned travel route. The energy consumption prediction device according to claim 1 .

7. the processor determines the running resistance based on two or more pieces of information among information on the weight of the vehicle when the vehicle runs along the planned running route, information on at least one of the distance, average required time, and average vehicle speed of the planned running route, and information on at least one of the altitude and road surface conditions on the planned running route; The energy consumption prediction device according to claim 1 .

8. The energy consumption prediction device according to any one of claims 1 to 7; a control unit provided in the vehicle and configured to transmit to the energy consumption prediction device the state of the drive source of the vehicle and the state of a battery that supplies energy for driving the drive source; An energy consumption prediction system comprising:

9. Obtaining information indicating the planned route of the vehicle; Identifying a running resistance applied to the vehicle when the vehicle travels along the planned traveling route based on the information indicating the planned traveling route; determining, based on the information indicating the planned driving route, a driving output required for driving a drive source of the vehicle when the vehicle travels along the planned driving route; outputting energy consumption when the vehicle travels along the planned travel route based on the travel resistance and the travel output; The energy consumption prediction method includes:

10. Obtaining information indicating the planned route of the vehicle; Identifying a running resistance applied to the vehicle when the vehicle travels along the planned traveling route based on the information indicating the planned traveling route; determining, based on the information indicating the planned driving route, a driving output required for driving a drive source of the vehicle when the vehicle travels along the planned driving route; outputting energy consumption when the vehicle travels along the planned travel route based on the travel resistance and the travel output; An energy consumption prediction program that causes a computer to execute the above.

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