WO2018021027A1 - Electric track travel route selection system, electric track travel route selection method - Google Patents

Abstract

[Problem] To provide an electric track travel route selection system that can improve power efficiency. [Solution] This system is provided with: a map information acquisition means (11) which acquires map information, which includes electric track transport starting point information and transport route information from the transport starting point to a cargo loading/unloading point; a transport weight information acquisition means (12) which acquires transport weight information, which includes initial weight information about the initial load loaded at the transport starting point, and loading/unloading weight information about the cargo loaded/unloaded at the cargo loading/unloading point; a change information estimating means (13) which, on the basis of the transport weight information, estimates change information about the gross weight of the load, which changes during transport; and an optimal route selection means (14) which selects an optimal route on the basis of basic information, which includes the map information and the change information.

Description

Electric truck travel route selection system, electric truck travel route selection method

The present invention relates to a traveling route selection system for an electric truck and a traveling route selection method for an electric truck, and more particularly to a technology for selecting a traveling route related to collection and delivery of collection and delivery by an electric truck.

Conventionally, many automobiles are equipped with a car navigation system, and a destination is set by map information in the car navigation system, and driving guidance is carried out by an optimum driving route from the current position of the car to the destination. In particular, in the technical field of electric vehicles, it is important to select a travel route that minimizes the consumption of the battery mounted on the vehicle from the viewpoint of increasing the travel distance and reducing power consumption. For example, in Patent Document 1, an electric vehicle capable of automatically limiting an acceleration to an excessive acceleration command and extending a cruising distance so that the selected driving route can be driven in an optimal driving mode. A travel route selection system is disclosed.

By the way, in the recent logistics industry, it is required to reduce logistics costs and save labor while having problems such as traffic congestion, exhaust gas, noise, and energy saving. In particular, visualization and reduction of the cost required for transportation is an important management issue. For this reason, there is a high demand for a system for selecting an optimal delivery route (that is, a travel route) in the physical distribution industry. For example, Patent Document 2 discloses a vehicle allocation and delivery planning method that enables an efficient visit even when the required time to the visit destination varies due to various factors such as traffic accidents, traffic restrictions, and traffic jams.

Japanese Patent Laid-Open No. 08-178683 JP 2001-14296 A

In the future logistics industry, from the viewpoint of further reducing logistics costs and environmental impact, it is expected that electric trucks suitable for transporting a large number of luggage among electric vehicles will be popularized. Therefore, when a logistics company adopts the electric truck, it is required to construct a collection / delivery route selection system for collection and delivery that can visualize the transportation cost and further improve the electric cost. However, it is not possible to sufficiently improve the electricity cost only by road condition information such as traffic accidents, traffic regulations, and traffic jams.

The present invention has been made to solve such problems, and an object of the present invention is to provide an electric truck traveling route selection system and an electric truck traveling route selection method capable of further improving power consumption. There is to do.

An electric truck traveling route selection system according to this application example is an electric truck traveling route selection system using a motor driven by electric power supplied from a battery as a driving source, and the electric truck transportation start point information and Map information acquisition means for acquiring map information including transport route information from the transportation start point to the baggage landing point, initial weight information of the initial load loaded at the transport start point, and the baggage landing point Transport weight information acquisition means for acquiring transport weight information including the boarding / mounting weight information of the packages loaded and unloaded at the vehicle, and fluctuations for estimating fluctuation information of the total loaded weight that fluctuates during transport based on the transport weight information An information estimation unit; and an optimum route selection unit that selects an optimum route based on basic information including the map information and the variation information.

In the electric truck traveling route selection system according to this application example, the optimum route selecting means includes the regenerative electric energy of the motor and the electric truck based on the total loaded weight estimated for each traveling section of each transportation route. It is also possible to calculate the travel power consumption amount and compare the calculation results to select the optimum route. Thereby, the optimal route can be selected with higher accuracy by using numerical data that can be easily calculated.

In the electric truck travel route selection system according to this application example, the optimum route selection unit may be configured such that when the transportation route information includes a downhill road with a predetermined slope or more, the total load weight is relatively heavy. The optimum route may be selected so as to travel on a downhill road. Thereby, the selection of the optimal route in consideration of the regenerative power amount and the travel power consumption amount is realized, and the optimal route can be selected with higher accuracy.

In the electric truck traveling route selection system according to this application example, when the transportation route information includes an upslope with a predetermined gradient or more, the optimum route selecting unit includes the upslope with a relatively light total weight. The optimum route may be selected so as to travel on the road. Thereby, the selection of the optimal route in consideration of the regenerative power amount and the travel power consumption amount is realized, and the optimal route can be selected with higher accuracy.

In the electric truck traveling route selection system according to this application example, the optimum route selecting means classifies the traveling area in the map information according to road conditions, and selects any of the classified areas based on the total loaded weight. The optimum route may be selected so as to travel in the travel area. Thereby, the optimal route can be selected with higher accuracy while preventing the transportation route from becoming complicated.

In the electric truck traveling route selection system according to this application example, the optimum route selecting unit may be configured such that when the traveling area in the map information is classified into a lowland area and a highland area according to altitude, the total load weight is relatively low. The optimum route may be selected so that the vehicle travels in the lowland area in a heavy state and travels in the highland area in a state where the total weight of the load is relatively light. As a result, numerical data such as the regenerative power amount of the motor and the traveling power consumption amount of the electric truck are taken into consideration, and the optimum route can be selected with higher accuracy.

In the electric truck traveling route selection system according to this application example, the optimum route selecting unit classifies the traveling area in the map information into an uphill area and a non-uphill area depending on the number of uphill roads having a predetermined slope or more. The optimal route may be selected so that the non-uphill road area travels in a state in which the total loaded weight is relatively heavy, and the uphill road area travels in a state in which the total loaded weight is relatively light. As a result, numerical data such as the regenerative power amount of the motor and the traveling power consumption amount of the electric truck are taken into consideration, and the optimum route can be selected with higher accuracy.

In the electric truck traveling route selection system according to this application example, the optimum route selecting means classifies the traveling area in the map information into a downhill area and a non-downhill area depending on the number of downhill roads having a predetermined slope or more. The optimum route may be selected such that the vehicle travels in the downhill area with a relatively heavy total weight and the vehicle travels in the non-downhill area with a relatively light total weight. As a result, numerical data such as the regenerative power amount of the motor and the traveling power consumption amount of the electric truck are taken into consideration, and the optimum route can be selected with higher accuracy.

An electric truck traveling route selection method according to this application example is an electric truck traveling route selection method using a motor driven by electric power supplied from a battery as a drive source, and the electric truck transportation start point information and Map information acquisition step for acquiring map information including transport route information from the transport start point to the load / unload point, initial weight information of the initial load loaded at the transport start point, and the load / unload point A transportation weight information acquisition step for acquiring transportation weight information including the loading / unloading weight information of the cargo loaded and unloaded at the vehicle, and a variation for estimating fluctuation information of the total loaded weight that varies during transportation based on the transportation weight information An information estimation step, and an optimum route selection step for selecting an optimum route based on basic information including the map information and the variation information.

In the traveling route selecting method for an electric truck according to this application example, in the optimum route selecting step, the regenerative electric energy of the motor and the electric truck are based on the total loaded weight estimated for each traveling section of each transportation route. It is also possible to calculate the travel power consumption amount and compare the calculation results to select the optimum route. Thereby, the optimal route can be selected with higher accuracy by using numerical data that can be easily calculated.

In the electric truck traveling route selection method according to this application example, in the optimum route selection step, when the transportation route information includes downhill roads with a predetermined gradient or more, the total load weight is relatively heavy. The optimum route may be selected so as to travel on a slope. Thereby, the selection of the optimal route in consideration of the regenerative power amount and the travel power consumption amount is realized, and the optimal route can be selected with higher accuracy.

In the electric truck travel route selection method according to this application example, in the optimum route selection step, when the transport route information includes an uphill road having a predetermined gradient or more, the uphill road with a relatively light total weight is loaded. The optimum route may be selected so as to travel on the road. Thereby, the selection of the optimal route in consideration of the regenerative power amount and the travel power consumption amount is realized, and the optimal route can be selected with higher accuracy.

In the electric truck traveling route selection method according to this application example, in the optimum route selecting step, the traveling area in the map information is classified into areas according to road conditions, and any of the classified areas is classified based on the total loaded weight. The optimum route may be selected so as to travel in the travel area. Thereby, the optimal route can be selected with higher accuracy while preventing the transportation route from becoming complicated.

In the electric truck traveling route selection method according to this application example, in the optimum route selecting step, when the traveling area in the map information is classified into a lowland area and a highland area according to altitude, the total load weight is relatively low. The optimum route may be selected so that the vehicle travels in the lowland area in a heavy state and travels in the highland area in a state where the total weight of the load is relatively light. As a result, numerical data such as the regenerative power amount of the motor and the traveling power consumption amount of the electric truck are taken into consideration, and the optimum route can be selected with higher accuracy.

In the electric truck traveling route selection method according to this application example, in the optimum route selecting step, the traveling area in the map information is classified into an uphill area and a non-uphill area depending on the number of uphill roads having a predetermined slope or more. The optimal route may be selected so that the non-uphill road area travels in a state in which the total loaded weight is relatively heavy, and the uphill road area travels in a state in which the total loaded weight is relatively light. As a result, numerical data such as the regenerative power amount of the motor and the traveling power consumption amount of the electric truck are taken into consideration, and the optimum route can be selected with higher accuracy.

In the electric truck traveling route selection method according to this application example, in the optimum route selecting step, the traveling area in the map information is classified into a downhill area and a non-downhill area depending on the number of downhill roads having a predetermined slope or more. The optimum route may be selected such that the vehicle travels in the downhill area with a relatively heavy total weight and the vehicle travels in the non-downhill area with a relatively light total weight. As a result, numerical data such as the regenerative power amount of the motor and the traveling power consumption amount of the electric truck are taken into consideration, and the optimum route can be selected with higher accuracy.

According to the present invention using the above means, it is possible to provide an electric truck traveling route selection system and an electric truck traveling route selection method capable of further improving the electric power consumption.

It is a block diagram which shows the relationship between an electric truck provided with the driving | running route selection system in embodiment of this invention, and a data server. It is a flowchart which shows the control routine which concerns on the optimal route selection performed by vehicle ECU of 1st embodiment of this invention. It is a route conceptual diagram concerning optimal route selection performed by vehicle ECU of a first embodiment of the present invention. It is a flowchart which shows the control routine which concerns on the optimal route selection performed by vehicle ECU of 2nd embodiment of this invention. It is a route conceptual diagram concerning optimal route selection performed by vehicle ECU of a second embodiment of the present invention. It is a route conceptual diagram concerning optimal route selection performed by vehicle ECU of a second embodiment of the present invention. It is a route conceptual diagram concerning optimal route selection performed by vehicle ECU of a second embodiment of the present invention. It is a route conceptual diagram concerning optimal route selection performed by vehicle ECU of a second embodiment of the present invention. It is a route conceptual diagram concerning optimal route selection performed by vehicle ECU of a second embodiment of the present invention. It is a route conceptual diagram concerning optimal route selection performed by vehicle ECU of a second embodiment of the present invention.

<First embodiment>
Hereinafter, a first embodiment of the present invention will be described with reference to the drawings.

FIG. 1 is a block diagram showing the relationship between an electric truck equipped with a travel route selection system and a data server according to an embodiment of the present invention, and various configurations will be described based on the drawing.

An electric truck 1 shown in FIG. 1 is one type of electric vehicle that uses a motor driven by electric power supplied from a battery as a drive source, and is a vehicle including a container and a carrier that can transport a large amount of luggage. . The electric truck 1 includes an electric motor that can also operate as a generator, such as a permanent magnet synchronous motor. In the electric truck 1, the output shaft of the motor is connected to a differential device via a propeller shaft, and the right and left drive wheels are connected to the differential device via a drive shaft. With such a connection configuration, the electric truck 1 can travel by rotating the drive wheels using the motor as a drive source. In addition, since the structure of the electric track 1 described above is general, for convenience of the configuration and description of the present invention, various components are omitted in FIG. .

Further, as shown in FIG. 1, the electric truck 1 includes a vehicle ECU 2, a communication unit 3, and a navigation device 4. The vehicle ECU 2 is a control circuit for integrated control of the entire vehicle. Therefore, the vehicle ECU 2 is connected to the above-described components of the electric truck 1, various sensors, and various electronic devices. In particular, FIG. 1 shows a connection configuration in which the communication unit 3 and the navigation device 4 are connected to the vehicle ECU 2 in order to explain the present invention.

Further, the vehicle ECU 2 includes a map information acquisition unit 11, a transport weight information acquisition unit 12, a fluctuation information estimation unit 13, and an optimum route selection unit 14. Here, the travel route selection system of the present invention is configured by the map information acquisition unit 11, the transport weight information acquisition unit 12, the fluctuation information estimation unit 13, and the optimum route selection unit 14, and the vehicle ECU 2 performs the travel route selection system. Or the vehicle ECU 2 itself corresponds to the travel route selection system.

Here, as long as the travel route selection system of the present invention includes the map information acquisition unit 11, the transport weight information acquisition unit 12, the fluctuation information estimation unit 13, and the optimum route selection unit 14, the mode is not limited. Although not shown, for example, on the data server 30, the calculation control unit 32 includes a map information acquisition unit 11, a transport weight information acquisition unit 12, a fluctuation information estimation unit 13, and an optimum route selection unit 14, and communication of the vehicle 1. The unit 3 may receive the optimum route selected by the optimum route selection unit 14 in the data server 30 and display it on the navigation device 4. Here, the communication unit 3 may be provided inside the navigation device 4. In such a case, information acquired by the communication unit 3 in the following description is stored in the data server 30 in advance, or is acquired from the outside by the communication unit 31 in the data server 30.

Further, for example, the travel route selection system of the present invention can be installed in a vehicle and can acquire a map information acquisition unit 11 and a transportation weight information acquisition in an arithmetic processing unit (not shown) in a navigation device that can communicate with a wireless communication network. The form provided with the part 12, the fluctuation | variation information estimation part 13, and the optimal route selection part 14 may be sufficient.

In the following, as shown in FIG. 1, the vehicle ECU 2 includes a map information acquisition unit 11, a transport weight information acquisition unit 12 取得, a fluctuation information estimation unit 13, and an optimum route selection unit 14. This will be described as an embodiment of the present invention.

In the present embodiment, each of the map information acquisition unit 11, the transport weight information acquisition unit 12, the fluctuation information estimation unit 13, and the optimum route selection unit 14 is provided with a program for realizing various functions to be described later. It is assumed as a control circuit. Note that the map information acquisition unit 11, the transport weight information acquisition unit 12, the fluctuation information estimation unit 13, and the optimum route selection unit 14 are not individual control circuits but are included in one control circuit constituting the vehicle ECU 2. It is a part of one program and does not have to have a shape like a part.

The map information acquisition unit 11 acquires map information recorded outside the electric truck 1 via the communication unit 3. Here, the map information includes the transportation start point information of the electric truck 1 (for example, each sales office of the transportation company that is the owner of the electric truck 1), and the baggage loading / unloading point (for example, the cargo loading / unloading point). The delivery route information to the delivery destination, the collection destination of the package, or the place where the package is delivered and collected at the same time, and the transportation route information of the route connecting the package loading / unloading points. The map information includes not only the above information but also route information other than the transportation route (that is, general information on the road displayed on the navigation device 4), gradient information, signal information, road surface information, and real time or prediction. Various kinds of information such as traffic jam information, accident information, and construction information may be included. In addition, the map information acquisition part 11 may acquire the said information from the memory of the navigation apparatus 4 about information with low update frequency, such as route information and gradient information. Thereby, the amount of data transmitted / received to / from the outside of the vehicle is reduced, and the load on the vehicle ECU 2 can be reduced.

The transport weight information acquisition unit 12 acquires transport weight information recorded outside the electric truck 1 via the communication unit 3. Here, the transportation weight information includes the initial weight information of the initial load loaded at the transportation start point of the electric truck 1 and the loading / unloading information of the luggage loaded / unloaded at each loading / unloading point. It is out. The initial weight information includes not only the weight of the load actually loaded at the transportation start point, but also the weight of the load remaining in the container of the electric truck 1 or the like. That is, the initial weight information is the total weight of the loaded cargo immediately before the electric truck 1 departs from the transportation start point.

The fluctuation information estimation unit 13 estimates fluctuation information of the total load weight that fluctuates during transportation based on the transportation weight information acquired by the transportation weight information acquisition unit 12. A method for estimating fluctuation information of the total load weight that fluctuates during transportation is not particularly limited, and a known technique can be applied. For example, the fluctuation information estimation unit 13 may extract all of the transportation routes that pass through the transportation start point and each loading / unloading point. Here, the fluctuation information estimation unit 13 may extract a travel route that can be executed in consideration of temporal conditions such as delivery and collection / delivery as a transport route. Thereafter, the fluctuation information estimation unit 13 estimates the fluctuation information of the total loaded weight by adding information on the total loaded weight for each estimated transportation route.

The optimal route selection unit 14 is an electric truck 1 that can further improve power consumption based on the basic information including the map information acquired by the map information acquisition unit 11 and the fluctuation information estimated by the fluctuation information estimation unit 13. Select the best route to travel on. Here, the basic information includes various information such as travel performance data including power consumption information for the past total load weight (hereinafter also referred to as load amount) as other information other than the map information and the fluctuation information. May be. The other information may be information stored in a memory (not shown) in the electric truck 1 or information stored outside the vehicle and acquired via the communication unit 3. It may be.

In the present embodiment, the optimum route selection unit 14 calculates the regenerative power amount of the motor and the travel power consumption amount of the electric truck 1 based on the total loaded weight estimated for each travel section of each transport route, and the calculation result To select the optimal route. As a more specific selection of the optimum route, when the downhill road having a predetermined gradient or more is included in the transport route information, the optimum route selection unit 14 is configured to travel on the downhill road with a relatively heavy total weight. An optimal route may be selected. On the other hand, when the transport route information includes an uphill road having a predetermined gradient or more, the optimum route selection unit 14 may select the optimum route so that the uphill road travels with a relatively light total weight. .

Here, the state where the total load weight is relatively heavy is, for example, 50% or more of the maximum load capacity, and the state where the total load weight is relatively light is, for example, less than 50% of the maximum load capacity. Further, the downhill road having a predetermined gradient or higher is, for example, a 2% or higher downhill road, and the uphill road having a predetermined gradient or higher is, for example, a 2% or higher uphill road. These numerical values are appropriately determined according to the size of the electric truck 1, the weight including the loading capacity, and the shape.

The communication unit 3 is connected to the data server 30 through the wireless communication network 20 so as to be in electrical communication. Then, in such a communication state, the communication unit 3 transmits various types of information of the electric truck 1 (for example, information on the actual power consumption such as real-time traffic jam information) to the data server 30, and the map information, Transport weight information and various other information (for example, electricity cost information for past loading capacity) are received. Further, the communication unit 3 may perform inter-vehicle communication with other vehicles (not shown), road-vehicle communication with VICS (registered trademark), or share various information with other vehicles. Good.

The navigation device 4 stores map information including road curves and slopes in advance in its own storage area, and sequentially receives GPS information via an antenna while the electric truck 1 is running, Identify your vehicle position. Further, the navigation device 4 provides route guidance to the driver of the electric truck 1 while displaying the optimum route selected by the optimum route selection unit 14.

The wireless communication network 20 is a network that is generally known and provided by various communication companies, and connects communication devices that exist in remote locations. Note that the wireless communication network 20 may be either a public communication network or a dedicated communication network.

The data server 30 is installed in a place different from the electric truck 1 and is connected to the electric truck 1 and other vehicles via the wireless communication network 20 so as to be able to perform electric communication. As illustrated in FIG. 1, the data server 30 includes a communication unit 31, an operation control unit 32, and a data recording unit 33.

The communication unit 31 is connected to the communication unit 3 of the electric truck 1 through the wireless communication network 20 so as to be in electrical communication. Then, in such a communication state, the communication unit 31 receives various types of information on the electric truck 1 (for example, information on the actual power consumption such as real-time traffic jam information) from the electric truck 1, and maps information, transport weight information, And other various information are transmitted to the electric truck 1.

The arithmetic control unit 32 is a control circuit for performing integrated control of the data server 30. Specifically, the arithmetic control unit 32 controls the communication unit 31 and stores various types of information received via the communication unit 31 in the data recording unit 33, or extracts various types of stored information for each vehicle. Control to send to. In FIG. 1, only the electric truck 1 is provided with the travel route selection system of the present invention including the map information acquisition unit 11, the transport weight information acquisition unit 12, the fluctuation information estimation unit 13, and the optimum route selection unit 14. However, you may provide the said travel route selection system in the calculation control part 32. FIG. That is, as described above, the calculation control unit 32 includes the map information acquisition unit 11, the transport weight information acquisition unit 12, the fluctuation information estimation unit 13, and the optimum route selection unit 1.
4 and the electric truck 1 may be notified of the optimum route to be selected.

The data recording unit 33 is composed of a general hard disk or semiconductor memory. Further, the data recording unit 33 can easily store, retrieve, and rewrite various types of information under the control of the arithmetic control unit 32.

Next, a method for selecting an optimum route by the travel route selection system (vehicle ECU 2) of the present invention will be specifically described with reference to FIGS. Here, FIG. 2 is a flowchart showing a control routine relating to the optimum route selection executed by the vehicle ECU 2 of the present embodiment. FIG. 3 is a route conceptual diagram relating to the optimum route selection executed by the vehicle ECU 2 of the present embodiment.

First, the map information acquisition unit 11 of the vehicle ECU 2 acquires the map information recorded in the data recording unit 33 of the data server 30 via the communication unit 3 (step S1: map information acquisition step). At this time, the map information acquisition unit 11 may acquire a part of the map information from the navigation device 4. Specifically, the map information acquisition unit 11 acquires various information on the uphill road 40, the downhill road 50, the downhill road 60, and the uphill road 70 shown in FIG.

Next, the transport weight information acquisition unit 12 of the vehicle ECU 2 acquires the transport weight information recorded in the data recording unit 33 of the data server 30 via the communication unit 3 (step S2: transport weight information acquisition step). Specifically, the transportation weight information acquisition unit 12 relates to the loading amount (100 kg) at the transportation start point O, the loading amount at the highland A (20 kg), and the loading amount at the lowland B (80 kg) shown in FIG. Get transport weight information.

Next, the fluctuation information estimation unit 13 of the vehicle ECU 2 estimates the fluctuation information of the loading amount that fluctuates during transportation based on the transportation weight information acquired by the transportation weight information acquisition unit 12 (step S3: fluctuation information estimation step). ). More specifically, the fluctuation information estimation unit 13 is a first route that reaches the lowland B from the transportation start point O via the highland A, and a first route that reaches the highland A from the transportation start point O via the lowland B. Two routes are extracted. Thereafter, the fluctuation information estimation unit 13 adds information on the loading amount at the transportation start point O, the highland A, and the lowland B for each of the first route and the second route. That is, in the first route, it is estimated that the loading amount is 100 kg at the transportation start point O, the loading amount is 80 kg in the highland A, and then the loading amount is 0 kg in the lowland B. On the other hand, in the second route, it is estimated that the loading amount is 100 kg at the transportation start point O, the loading amount is 20 kg in the lowland B, and then the loading amount is 0 kg in the highland A.

Next, the optimum route selection unit 14 of the vehicle ECU 2 calculates the regenerative power amount of the motor and the travel power consumption amount of the electric truck 1 based on the total loaded weight estimated for each travel route of each transport route. Thereafter, the optimum route selection unit 14 considers the calculation result as an element of basic information and selects an optimum route (step S4: optimum route selection step).

As a specific optimal route selection step, the optimal route selection unit 14 calculates the traveling power consumption (Elos100) of the uphill road 40 and the regenerative electric energy (Egin80) of the downhill road 50 in the first route shown in FIG. Moreover, the optimal route selection part 14 calculates the regenerative electric energy (Egin100) of the descent road 60 and the traveling power consumption (Elos20) of the uphill road 70 in the 2nd route shown in FIG. Then, the optimum route selection unit 14 compares the calculation result in the first route (Elos100 + Egin80) with the calculation result in the second route (Egin100 + Elos20), and optimizes the transportation route that can travel with better power consumption with higher accuracy. Can be selected as a route.

Selecting a transportation route that takes into account the amount of regenerative power and travel power consumption means that, as described above, if the transportation route information includes downhill roads with a predetermined slope or higher, the total weight of the load is relatively heavy. If the route is selected to travel on the downhill road and the transport route information includes an uphill road with a predetermined slope or more, the route is selected to travel on the uphill road with a relatively light total weight. Will be.

Thereafter, the vehicle ECU 2 supplies information related to the optimum route to the navigation device 4, and travel guidance by the navigation device 4 is started.

From the above, according to the electric truck traveling route selection system and the electric truck traveling route selection method according to the present embodiment, the basic information including various information related to the transportation route and the variation information of the total load weight of the load is included. Since the optimum route is selected on the basis of this, it becomes possible to visualize the transportation cost with higher accuracy and to select the transportation route that can substantially improve the electricity cost as compared with the conventional method. In other words, according to the electric truck traveling route selection system and the electric truck traveling route selection method according to the present embodiment, the electric cost can be further improved and the transportation cost can be reduced.

In particular, in the present embodiment, the regenerative power amount of the motor and the travel power consumption amount of the electric truck 1 are calculated based on the total loaded weight estimated for each travel section of each transportation route, and the calculation results are compared. Since the optimum route is selected, the optimum route can be selected with higher accuracy by using numerical data that can be easily calculated.

In addition, when the transport route information includes downhill roads with a predetermined slope or higher, the optimum route is selected so that the total weight is relatively heavy, or the transport route information has a predetermined slope or higher. If the optimal route is selected so that it travels on the uphill road in a state where the total weight of the load is relatively light, Selection will be realized, and it is possible to select an optimum route that can substantially reduce power consumption with higher accuracy.

In the description according to the above embodiment, in the highland A and the lowland B, which are the loading and unloading points, it was assumed that only the baggage was dropped (that is, delivery), but the baggage was loaded (that is, (Collection) may be envisaged, and it is also possible to envisage a case where delivery and collection of packages are simultaneously performed at each point (ie, collection and delivery). In addition, although there are only two places for loading and unloading, the highland A and the lowland B, the same optimum route selection is made even if there are three or more places.

<Second embodiment>
Hereinafter, a second embodiment of the present invention will be described with reference to the drawings.

The structure of the electric truck 1, the structure of the wireless communication network 20, and the data server 30 in the second embodiment are the same as the form shown in FIG. 1 in the first embodiment. However, the second embodiment differs from the first embodiment in the optimum route selection method in the optimum route selection unit 14. Therefore, description of the electric truck 1, the wireless communication network 20, and the data server 30 in the second embodiment is omitted, and the optimum route selection method in the optimum route selection unit 14 according to the second embodiment is described with reference to FIG. This will be described below.

The optimal route selection unit 14 according to the second embodiment further improves the power consumption based on the basic information including the map information acquired by the map information acquisition unit 11 and the variation information estimated by the variation information estimation unit 13. The optimum route on which the electric truck 1 can travel is selected. More specifically, the optimum route selection unit 14 classifies the traveling area in the map information according to the road condition, and selects the optimum route so as to travel in one of the classified traveling areas based on the total loaded weight. To do.

For example, when the travel area in the map information is classified into a lowland area and a highland area according to the height of the altitude, the optimum route selection unit 14 travels in the lowland area with a relatively heavy total weight, and the total load weight is The optimum route is selected so as to travel in the highland area in a relatively light state. In addition, when the travel area in the map information is classified into an uphill road area and a non-uphill road area depending on the number of uphill roads having a predetermined slope or more, the optimum route selection unit 14 performs the non-hill climbing in a state in which the total loaded weight is relatively heavy. An optimum route is selected so that the vehicle travels on the road area and travels on the uphill road area with a relatively light total weight. Further, when the traveling area in the map information is classified into a downhill road area and a non-downhill road area depending on the number of downhill roads having a predetermined slope or more, the optimum route selection unit 14 sets the downhill road in a state in which the total loaded weight is relatively heavy. The optimum route is selected so that the vehicle travels in the area and travels in the non-downhill area with a relatively light total weight.

Here, the state in which the total load weight is relatively heavy, the state in which the total load weight is relatively light, the downhill road with a predetermined gradient or higher, and the uphill road with a predetermined gradient or higher are the same as the contents defined in the first embodiment. is there.

Next, a method for selecting an optimum route by the travel route selection system (vehicle ECU 2) of the present invention will be specifically described with reference to FIGS. Here, FIG. 4 is a flowchart showing a control routine related to the optimum route selection executed by the vehicle ECU 2 of the present embodiment. 5 to 10 are route conceptual diagrams related to the optimum route selection executed by the vehicle ECU 2 of the present embodiment. In particular, FIGS. 5 to 7 are conceptual diagrams of routes based on delivery, and FIGS. 8 to 10 are conceptual diagrams of routes based on collection.

First, the map information acquisition unit 11 of the vehicle ECU 2 acquires the map information recorded in the data recording unit 33 of the data server 30 via the communication unit 3 (step S11: map information acquisition step). At this time, the map information acquisition unit 11 may acquire a part of the map information from the navigation device 4. Specifically, the map information acquisition unit 11 transports the route information from the transportation start point O shown in FIGS. 5 to 10 to each loading / unloading point (12 circle areas blacked out in the figure). , And various information such as transport route information connecting the respective loading / unloading points.

Next, the transport weight information acquisition unit 12 of the vehicle ECU 2 acquires the transport weight information recorded in the data recording unit 33 of the data server 30 via the communication unit 3 (step S12: transport weight information acquisition step). Specifically, when delivery is premised, the transportation weight information acquisition unit 12 performs the loading amount (110 kg) at the transportation start point O and the loading amount (10 kg) at each loading / unloading point shown in FIGS. ) To obtain transport weight information. On the other hand, when premised on the collection, the transportation weight information acquisition unit 12 relates to the loading amount (0 kg) at the transportation start point O and the loading amount (10 kg) at each loading / unloading point shown in FIGS. Get transport weight information.

Next, the fluctuation information estimation unit 13 of the vehicle ECU 2 estimates the fluctuation information of the loading amount that fluctuates during transportation based on the transportation weight information acquired by the transportation weight information acquisition unit 12 (step S13: fluctuation information estimation step). ). More specifically, the fluctuation information estimation unit 13 extracts a plurality of transportation routes that pass from the transportation start point O through all of the luggage loading / unloading points. Here, the fluctuation information estimation unit 13 may extract a travel route that can be executed in consideration of temporal conditions such as delivery and collection / delivery as a transport route. After that, the fluctuation information estimation unit 13 adds information on the loading amount at the transportation start point O and each loading / unloading point for each transportation route.

5 to 7, since the delivery is premised, the loading amount is 110 kg at the transportation start point O, and the loading amount decreases by 10 kg every time it passes through each loading / unloading point. ing. On the other hand, in FIGS. 8 to 10, since the collection is premised, the loading amount is 0 kg at the transportation start point O, and the loading amount increases by 10 kg every time it passes through each loading / unloading point. ing. 5 to 10 show one of the optimum routes finally determined.

Next, the optimum route selection unit 14 of the vehicle ECU 2 classifies the travel areas in the map information according to the road conditions. Thereafter, the optimum route selection unit 14 selects an optimum route so as to travel in any of the classified travel areas based on the total loaded weight (step S14: optimum route selection step).

For example, as shown in FIG. 5, when the traveling area is classified into the lowland area C and the highland area D, the load amount is relatively heavy (the load amount is indicated by 110 kg to 60 kg, and the delivery is completed by less than half. State), travels in the lowland area C, moves from the lowland area C to the highland area D with a load of 60 kg, and the load is relatively light (loading is indicated by 50 kg to 0 kg, delivery is more than half In the finished state), the optimum route is selected so as to travel in the highland area D.

In addition, as shown in FIG. 6, when the traveling area is classified into the non-uphill area E and the uphill area F, the load amount is relatively heavy (the load amount is indicated by 110 kg to 60 kg, and the delivery is completed by less than half. In the non-climbing road area E, and moving from the non-climbing road area E to the uphill road area F with a load of 60 kg, the load is relatively light (loading is 50 kg to 0 kg) The optimal route is selected so that the vehicle travels in the uphill road area F in a state where the delivery has been completed by more than half.

Furthermore, as shown in FIG. 7, when the traveling area is classified into the downhill area G and the non-downhill area H, the load amount is relatively heavy (the load amount is indicated by 110 kg to 60 kg, and the delivery is completed by less than half. Drive downhill area G in a state where the load is 60 kg and move from downhill area G to non-downhill area H with a load of 60 kg, the load is relatively light (load is 50 kg to 0 kg) The optimum route is selected so as to travel in the non-downhill area H in the state where the delivery has been completed by more than half.

On the other hand, in the case of pickup, when the traveling area is classified into the lowland area C and the highland area D as shown in FIG. 8, the load amount is relatively light (the load amount is indicated by 0 kg to 60 kg, and the pickup is half. It travels in the highland area D in the state where only the following is completed), moves from the highland area D to the lowland area C with the loading capacity of 60kg, and the loading capacity is relatively heavy (loading capacity is shown as 70kg to 110kg) The optimal route is selected so that the vehicle travels in the lowland area C in a state where the collection is over halfway.

In addition, as shown in FIG. 9, when the traveling area is classified into the non-uphill area E and the uphill area F, the load amount is relatively light (the load amount is indicated by 0 kg to 60 kg, and the collection is completed by less than half. Drive uphill road area F, move uphill road area F to non-hill road area E with a load capacity of 60 kg, load capacity is relatively heavy (load capacity is 70 kg to 110 kg) The optimum route is selected so that the vehicle travels in the non-climbing road area E in the state where the collection has been completed by more than half.

Furthermore, as shown in FIG. 10, when the traveling area is classified into the downhill area G and the non-downhill area H, the load amount is relatively light (the load amount is indicated by 0 kg to 60 kg, and the collection is completed by less than half. In the non-downhill area H, and the load is 60 kg, the vehicle moves from the non-downhill area H to the downhill area G, and the load is relatively heavy (the load is 70 kg to 110 kg). The optimal route is selected so that the vehicle travels on the downhill area G in the state where the collection is completed by half or more).

Thereafter, the vehicle ECU 2 supplies information related to the optimum route to the navigation device 4, and travel guidance by the navigation device 4 is started.

Based on the above, the electric truck traveling route selection system and the electric truck traveling route selection method according to the present embodiment are also based on basic information including various information related to the transportation route and variation information of the total load weight of the load. Since the optimum route is selected, it becomes possible to visualize the transportation cost and to select a transportation route that can substantially improve the electricity cost compared with the conventional route. That is, the power consumption can be further improved and the transportation cost can be reduced.

In particular, in the present embodiment, the travel area in the map information is classified into areas according to road conditions, and the optimal route is selected to travel in any travel area after classification based on the total loaded weight. The optimal route can be selected with higher accuracy while preventing the route from becoming complicated.

In the present embodiment, the regenerative electric energy of the motor and the electric truck 1 are classified by classifying the traveling area into a highland area and a lowland area, an uphill area and a non-uphill area, or a downhill area and a non-downhill area. Thus, the numerical data of the travel power consumption is taken into consideration, so that the optimum route can be selected with higher accuracy.

In the above description of the embodiment, only the classification into two areas has been described. However, the optimum route can be selected with higher accuracy by classifying the travel area into three or more. May be.

1 Electric truck 2 Vehicle ECU (travel route selection system)
3 Communication Unit 4 Navigation Device 11 Map Information Acquisition Unit (Map Information Acquisition Unit)
12 Transport weight information acquisition unit (Transport weight information acquisition means)
13 Fluctuation information estimation unit (fluctuation information estimation means)
14 Optimal route selection section (optimum route selection means)
DESCRIPTION OF SYMBOLS 20 Wireless communication network 30 Data server 31 Communication part 32 Operation control part 33 Data recording part 40 Uphill road 50 Downhill road 60 Downhill road 70 Uphill road

Claims (16)

1. An electric truck travel route selection system using a motor driven by electric power supplied from a battery as a drive source,
   Map information acquisition means for acquiring map information including transport start point information of the electric truck and transport route information from the transport start point to a load / unload point;
   Transport weight information acquisition means for acquiring transport weight information including initial weight information of an initial load loaded at the transport start point and load / unload weight information of a load / unloading load at the load / unload point;
   Based on the transport weight information, fluctuation information estimation means for estimating fluctuation information of the total weight of the load that fluctuates during transportation that fluctuates during transportation;
   An electric truck travel route selection system comprising: an optimum route selection means for selecting an optimum route based on basic information including the map information and the variation information.
2. The optimum route selection means calculates the regenerative power amount of the motor and the travel power consumption amount of the electric truck based on the total load weight estimated for each travel section of each transport route, and compares the calculation results. The electric truck travel route selection system according to claim 1, wherein the optimum route is selected.
3. The optimal route selection means selects the optimal route so as to travel on the downhill road in a state where the total weight of the load is relatively heavy when the transport route information includes a downhill road having a predetermined gradient or more. Or the driving | running route selection system of the electric truck of 2.
4. The optimal route selection means selects the optimal route so that when the transport route information includes an uphill road having a predetermined gradient or more, the road is traveled on the uphill road with a relatively light total weight. The traveling route selection system of the electric truck of any one of thru | or 3.
5. The optimum route selecting means classifies a traveling area in the map information according to road conditions, and selects the optimum route so as to travel in one of the classified traveling areas based on the total loaded weight. Item 2. A route selection system for an electric truck according to Item 1.
6. The optimum route selection means, when classifying the traveling area in the map information into a lowland area and a highland area according to the altitude, travels in the lowland area with a relatively heavy total weight, the total gross weight is 6. The electric truck travel route selection system according to claim 5, wherein the optimum route is selected so as to travel in the highland area in a relatively light state.
7. When the optimum route selection means classifies the traveling area in the map information into an uphill road area and a non-uphill road area depending on the number of uphill roads having a predetermined slope or more, the non-uphill road is in a relatively heavy total weight state. The traveling route selection system for an electric truck according to claim 5 or 6, wherein the optimum route is selected so as to travel in the area and travel in the uphill road area in a state where the total weight of the load is relatively light.
8. When the optimum route selection means classifies the traveling area in the map information into a downhill road area and a non-downhill road area depending on the number of downhill roads having a predetermined gradient or more, the downhill area in a state where the total loaded weight is relatively heavy. The route selection system for an electric truck according to any one of claims 5 to 7, wherein the optimum route is selected so as to travel in the non-downhill area with the total weight of the load being relatively light. .
9. A method for selecting a traveling route of an electric truck using a motor driven by electric power supplied from a battery as a drive source,
   Map information acquisition step for acquiring map information including transport start point information of the electric truck and transport route information from the transport start point to a baggage landing point;
   Transport weight information acquisition step for acquiring transport weight information including initial weight information of an initial load loaded at the transport start point and load / unload weight information of the load / unloading at the load / unloading point;
   Based on the transport weight information, a fluctuation information estimation step for estimating fluctuation information of the total load weight that fluctuates during transportation;
   An electric truck travel route selection method comprising: an optimum route selection step of selecting an optimum route based on basic information including the map information and the variation information.
10. In the optimum route selection step, the regenerative power amount of the motor and the travel power consumption amount of the electric truck are calculated based on the total load weight estimated for each travel section of each transport route, and the calculation results are compared. The method for selecting a traveling route for an electric truck according to claim 9, wherein the optimum route is selected.
11. The optimal route is selected so that when the transport route information includes a downhill road having a predetermined gradient or more in the optimal route selection step, the optimal route is selected so as to travel on the downhill road with a relatively heavy total weight. Or the traveling route selection method of the electric truck of 10.
12. 10. The optimum route selection step, wherein, when the transport route information includes an uphill road having a predetermined gradient or more, the optimum route is selected so as to travel on the uphill road with a relatively light total weight. 12. A method for selecting a traveling route for an electric truck according to any one of claims 11 to 11.
13. In the optimal route selection step, the travel area in the map information is classified into areas according to road conditions, and the optimal route is selected so as to travel in any travel area after classification based on the total loaded weight. Item 10. A method for selecting a traveling route for an electric truck according to Item 9.
14. In the optimum route selection step, when the traveling area in the map information is classified into a lowland area and a highland area according to altitude, the traveling total weight is relatively heavy and the traveling area is relatively heavy. The method for selecting a travel route for an electric truck according to claim 13, wherein the optimum route is selected so as to travel in the highland area in a relatively light state.
15. In the optimum route selection step, when the traveling area in the map information is classified into an uphill road area and a non-uphill road area depending on the number of uphill roads having a predetermined slope or more, the non-uphill road with a relatively heavy total load weight The method for selecting a travel route for an electric truck according to claim 13 or 14, wherein the optimum route is selected so as to travel in an area and travel in the uphill area in a state where the total weight of the load is relatively light.
16. In the optimum route selection step, when the traveling area in the map information is classified into a descending slope area and a non-descending slope area depending on the number of descending slope roads having a predetermined slope or more, the descending slope area in a state where the total loaded weight is relatively heavy. 16. The method for selecting a traveling route for an electric truck according to any one of claims 13 to 15, wherein the optimum route is selected so as to travel in the non-downhill area with the total weight of the load being relatively light. .

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