JP6898714B2 - Electric truck travel route selection system, electric truck travel route selection method - Google Patents

Description

The present invention relates to an electric truck traveling route selection system and an electric truck traveling route selection method, and more particularly to a traveling route selection technique relating to collection and delivery of cargo and delivery by an electric truck.

Conventionally, many automobiles are equipped with a car navigation system, a destination is set by the map information in the car navigation system, and driving guidance is provided by an optimum traveling route from the current location of the automobile to the destination. In particular, in the technical field of electric vehicles, it is important to select a traveling route that minimizes the consumption of the battery mounted on the vehicle from the viewpoint of increasing the mileage and reducing the electricity cost. For example, in Patent Document 1, an electric vehicle capable of extending the cruising range by automatically limiting acceleration in response to an excessive acceleration command so that the vehicle can travel in the optimum driving mode for the selected optimum driving route. The driving route selection system of 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 transportation costs has become an important management issue. Therefore, even in the logistics industry, there is an increasing demand for a system for selecting an optimum delivery route (that is, a traveling route). For example, Patent Document 2 discloses a vehicle dispatch delivery planning method that enables an efficient visit even when the time required to reach a destination varies due to various factors such as a traffic accident, traffic regulation, and traffic congestion.

Japanese Unexamined Patent Publication No. 08-178683 Japanese Unexamined Patent Publication No. 2001-14296

In the future logistics industry, from the viewpoint of further reducing logistics costs and environmental load, it is expected that electric trucks suitable for transporting a large number of luggage among electric vehicles will become widespread. 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 electricity cost. However, it is not possible to sufficiently improve electricity costs only with road condition information such as traffic accidents, traffic regulations, and traffic jams.

The present invention has been made to solve such a problem, and an object of the present invention is to provide a travel route selection system for an electric truck capable of further improving electricity costs, and a travel route selection method for an electric truck. To do.

The traveling route selection system for an electric truck according to this application example is a traveling route selection system for an electric truck whose drive source is a motor driven by electric power supplied from a battery, and includes information on a transportation start point of the electric truck and information on the transportation start point of the electric truck. A map information acquisition means for acquiring map information including transportation route information connecting a plurality of luggage loading / unloading points, initial weight information of the initial load loaded at the transportation starting point, and boarding / alighting at the luggage loading / unloading point. The transportation weight information acquisition means for acquiring the transportation weight information including the loading / unloading weight information of the loaded luggage and the fluctuation information of the total loading weight that fluctuates during transportation based on the transportation weight information are obtained from the transportation start point. The optimum route from the plurality of transportation routes based on the fluctuation information estimation means that estimates for each of the plurality of transportation routes that pass through all of the baggage loading / unloading points, the map information, and the basic information including the fluctuation information. possess the optimum route selecting means for selecting, for the, the best route selection means, said plurality of based on the variation information estimated in the transport every route, the regenerated electric energy of the motor and the travel power consumption of the electrical track The amount is calculated for each of the plurality of transportation routes, and the calculation results are compared to select the optimum route .

In the traveling route selection system for an electric truck according to this application example, the optimum route selection means is described in a state where the total load weight is relatively heavy when the transportation route information includes a downhill road having a predetermined gradient or more. The optimum route may be selected so as to travel on a downhill road. As a result, the optimum route can be selected in consideration of the regenerated electric energy amount and the running power consumption amount, and the optimum route can be selected with higher accuracy.

In the traveling route selection system for an electric truck according to this application example, when the transportation route information includes an uphill road having a predetermined gradient or more, the optimum route selection means climbs the slope with a relatively light total load weight. The optimum route may be selected so as to travel on the road. As a result, the optimum route can be selected in consideration of the regenerated electric energy amount and the running power consumption amount, and the optimum route can be selected with higher accuracy.

In the traveling route selection system for an electric truck according to this application example, the optimum route selecting means classifies the traveling area in the map information according to the road condition, and based on the total load weight, any of the classified areas. The optimum route may be selected so as to travel in the traveling area of. As a result, it is possible to select the optimum route with higher accuracy while preventing the transportation route from becoming complicated.

In the traveling route selection system for an electric truck according to this application example, when the optimum route selecting means classifies the traveling area in the map information into a lowland area and a highland area according to the altitude, the total load weight is relatively large. The optimum route may be selected so as to travel in the lowland area in a heavy state and travel in the highland area in a state where the total load weight is relatively light. As a result, numerical data such as the regenerative electric energy of the motor and the running power consumption of the electric truck are taken into consideration, and the optimum route can be selected with higher accuracy.

In the traveling route selection system for an electric truck according to this application example, the optimum route selecting means classifies the traveling area in the map information into an uphill road area and a non-uphill road area according to the number of uphill roads having a predetermined gradient or more. The optimum route may be selected so as to travel in the non-uphill road area with the total load weight relatively heavy and to travel in the uphill road area with the total load weight relatively light. As a result, numerical data such as the regenerative electric energy of the motor and the running power consumption of the electric truck are taken into consideration, and the optimum route can be selected with higher accuracy.

In the traveling route selection system for an electric truck according to this application example, the optimum route selecting means classifies the traveling area in the map information into a downhill road area and a non-downhill road area according to the number of downhill roads having a predetermined gradient or more. The optimum route may be selected so as to travel in the downhill road area with the total load weight relatively heavy and to travel in the non-downhill road area with the total load weight relatively light. As a result, numerical data such as the regenerative electric energy of the motor and the running power consumption of the electric truck are taken into consideration, and the optimum route can be selected with higher accuracy.

The traveling route selection method for an electric truck according to this application example is a traveling route selection method for an electric truck using a motor driven by electric power supplied from a battery as a drive source, and includes information on a transportation start point of the electric truck and information on the transportation start point of the electric truck. A map information acquisition step for acquiring map information including transportation route information connecting a plurality of luggage loading / unloading points, initial weight information of the initial load loaded at the transportation starting point, and boarding / alighting at the luggage loading / unloading point. The transportation weight information acquisition step for acquiring transportation weight information including the loading and unloading weight information of the loaded luggage, and the fluctuation information of the total loading weight that fluctuates during transportation based on the transportation weight information, are described from the transportation start point. Based on the variation information estimation step that estimates for each of the plurality of transportation routes that pass through all of the luggage loading / unloading points, and the map information and the basic information including the variation information, the optimum route is selected from the plurality of transportation routes. possess the optimum route selection step of selecting, a, in the best route selection step, based on the variation information estimated in the each of the plurality of transport routes, the regenerated electric energy of the motor and the travel power consumption of the electrical track Is calculated for each of the plurality of transportation routes, and the calculation results are compared to select the optimum route .

In the method for selecting a traveling route of an electric truck according to the present application example, in the optimum route selection step, when the transportation route information includes a downhill road having a predetermined gradient or more, the descending is performed in a state where the total load weight is relatively heavy. The optimum route may be selected so as to travel on a slope. As a result, the optimum route can be selected in consideration of the regenerated electric energy amount and the running power consumption amount, and the optimum route can be selected with higher accuracy.

In the method of selecting a travel route for an electric truck according to this application example, in the optimum route selection step, when the transportation route information includes an uphill road having a predetermined gradient or more, the uphill is in a state where the total load weight is relatively light. The optimum route may be selected so as to travel on the road. As a result, the optimum route can be selected in consideration of the regenerated electric energy amount and the running power consumption amount, and the optimum route can be selected with higher accuracy.

In the method of selecting a travel route for an electric truck according to this application example, in the optimum route selection step, the travel area in the map information is classified according to the road condition, and any of the classified areas is classified based on the total load weight. The optimum route may be selected so as to travel in the traveling area of. As a result, it is possible to select the optimum route with higher accuracy while preventing the transportation route from becoming complicated.

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

In the method of selecting a traveling route of an electric truck according to this application example, 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 according to the number of uphill roads having a predetermined gradient or more. The optimum route may be selected so as to travel in the non-uphill road area with the total load weight relatively heavy and to travel in the uphill road area with the total load weight relatively light. As a result, numerical data such as the regenerative electric energy of the motor and the running power consumption of the electric truck are taken into consideration, and the optimum route can be selected with higher accuracy.

In the method of selecting a travel route for an electric truck according to this application example, in the optimum route selection step, the travel area in the map information is classified into a downhill area and a non-downhill area according to the number of downhill roads having a predetermined slope or more. The optimum route may be selected so as to travel in the downhill road area with the total load weight relatively heavy and to travel in the non-downhill road area with the total load weight relatively light. As a result, numerical data such as the regenerative electric energy of the motor and the running power consumption 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 a traveling route selection system for an electric truck and a traveling route selection method for an electric truck, which can further improve the electricity cost.

It is a block diagram which shows the relationship between the electric truck provided with the traveling 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 optimum route selection executed by the vehicle ECU of 1st Embodiment of this invention. It is a route conceptual diagram which concerns on the optimum route selection executed by the vehicle ECU of the 1st Embodiment of this invention. It is a flowchart which shows the control routine which concerns on the optimum route selection executed by the vehicle ECU of the 2nd Embodiment of this invention. It is a route conceptual diagram which concerns on the optimum route selection executed by the vehicle ECU of the 2nd Embodiment of this invention. It is a route conceptual diagram which concerns on the optimum route selection executed by the vehicle ECU of the 2nd Embodiment of this invention. It is a route conceptual diagram which concerns on the optimum route selection executed by the vehicle ECU of the 2nd Embodiment of this invention. It is a route conceptual diagram which concerns on the optimum route selection executed by the vehicle ECU of the 2nd Embodiment of this invention. It is a route conceptual diagram which concerns on the optimum route selection executed by the vehicle ECU of the 2nd Embodiment of this invention. It is a route conceptual diagram which concerns on the optimum route selection executed by the vehicle ECU of the 2nd Embodiment of this invention.

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

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

The electric truck 1 shown in FIG. 1 is a type of electric vehicle whose drive source is a motor driven by electric power supplied from a battery, and is a vehicle provided with a container or a loading platform capable of transporting 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, as the motor. Further, in the electric truck 1, a differential device is connected to the output shaft of the motor via a propeller shaft, and left and right 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. Since the structure of the electric truck 1 described above is general, various components are omitted in FIG. 1 for convenience of the configuration and description of the present invention, and detailed description thereof is also omitted. ..

Further, as shown in FIG. 1, the electric truck 1 has 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 above-mentioned components of the electric truck 1, various sensors, and various electronic devices are connected to the vehicle ECU 2. 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 has a map information acquisition unit 11, a transportation 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 from the map information acquisition unit 11, the transportation weight information acquisition unit 12, the fluctuation information estimation unit 13, and the optimum route selection unit 14, and the vehicle ECU 2 is the travel route selection system. Or the vehicle ECU 2 itself corresponds to the travel route selection system.

Here, the mode of the traveling route selection system of the present invention is not limited as long as it includes the map information acquisition unit 11, the transportation weight information acquisition unit 12, the fluctuation information estimation unit 13, and the optimum route selection unit 14. Although not shown, for example, on the data server 30, the arithmetic control unit 32 includes a map information acquisition unit 11, a transportation weight information acquisition unit 12, a fluctuation information estimation unit 13, and an optimum route selection unit 14, and communicates with 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, the information acquired by the communication unit 3 in the following description is stored in advance in the data server 30, or is acquired from the outside by the communication unit 31 in the data server 30.

Further, for example, the traveling route selection system of the present invention has 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 be mounted on a vehicle and can communicate with a wireless communication network. The form may include a unit 12, a fluctuation information estimation unit 13, and an optimum route selection unit 14.

In the following, as shown in FIG. 1, the vehicle ECU 2 has a map information acquisition unit 11, a transportation weight information acquisition unit 12, 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 transportation weight information acquisition unit 12, the fluctuation information estimation unit 13, and the optimum route selection unit 14 is individually provided with programs for realizing various functions described later. It is supposed to be a control circuit. The map information acquisition unit 11, the transportation 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 built into one control circuit constituting the vehicle ECU 2. It does not have to be a part of one program and has a shape like a part.

The map information acquisition unit 11 acquires the map information recorded outside the electric truck 1 via the communication unit 3. Here, the map information includes transportation start point information of the electric truck 1 (for example, each business office of the transportation company that owns the electric truck 1), and a luggage loading / unloading point (for example, of luggage) from the transportation start point. It includes transportation route information to the delivery destination, the cargo collection destination, or the place where the cargo is delivered and collected at the same time), and the transportation route information of the route connecting the cargo loading / unloading points. Further, the map information includes not only the above information but also route information other than the transportation route (that is, general information of the road displayed on the navigation device 4), gradient information, signal information, road surface information, and real-time or prediction. It may also include various types of information such as traffic jam information, accident information, and construction information. The map information acquisition unit 11 may acquire information such as route information and gradient information that is not updated frequently from the memory of the navigation device 4. As a result, the amount of data transmitted / received to 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 the 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 to be loaded at each of the luggage loading / unloading points. I'm out. Further, the initial weight information includes not only the weight of the cargo actually loaded at the transportation start point but also the weight of the cargo remaining in the container or the like of the electric truck 1. 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 the 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. The method for estimating the 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 assume and extract all the transportation routes via the transportation start point and each baggage loading / unloading point. Further, here, the fluctuation information estimation unit 13 may extract a travel route that can be executed in consideration of time conditions such as delivery and collection / delivery as a transportation route. After that, the fluctuation information estimation unit 13 estimates the fluctuation information of the total load weight by adding the information of the total load weight for each of the estimated transportation routes.

The optimum route selection unit 14 can further improve the electricity cost based on the map information acquired by the map information acquisition unit 11 and the basic information including the fluctuation information estimated by the fluctuation information estimation unit 13. Select the optimal route to travel. Here, the basic information includes various information such as running record data including electricity cost information with respect to the past total load weight (hereinafter, also referred to as load capacity) as other information other than map information and fluctuation information. You may. The other information may be information stored in a memory (not shown) in the electric truck 1, information stored outside the vehicle, and information acquired via the communication unit 3. It may be.

In the present embodiment, the optimum route selection unit 14 calculates the regenerative electric energy of the motor and the traveling power consumption of the electric truck 1 based on the total load weight estimated for each traveling section of each transportation route, and the calculation result. To select the optimum route by comparing. As a more specific selection of the optimum route, when the transportation route information includes a downhill road having a predetermined gradient or more, the optimum route selection unit 14 travels on the downhill road with a relatively heavy total load weight. The optimum route may be selected. On the other hand, when the transportation route information includes an uphill road having a predetermined gradient or more, the optimum route selection unit 14 may select the optimum route so as to travel on the uphill road with a relatively light total load weight. ..

Here, a state in which the total load weight is relatively heavy is, for example, 50% or more of the maximum load capacity, and a state in which the total load weight is relatively light is, for example, less than 50% of the maximum load capacity. Further, a downhill road having a predetermined slope or more is, for example, a downhill road of 2% or more, and an uphill road having a predetermined slope or more is, for example, an uphill road of 2% or more. It should be noted that these numerical values are appropriately determined according to the size of the electric truck 1, the weight including the load capacity, and the shape.

The communication unit 3 is connected to the data server 30 via the wireless communication network 20 so as to be capable of telecommunications. Then, in such a communication state, the communication unit 3 transmits various information of the electric truck 1 (for example, real-time congestion information and other information on the actual electricity cost) to the data server 30, and the data server 30 provides map information. Receives transportation weight information and various other information (for example, electricity cost information for past load capacity). Further, the communication unit 3 may perform vehicle-to-vehicle communication with another vehicle (not shown), road-vehicle communication with VICS (registered trademark), or share various information with the other vehicle. Good.

The navigation device 4 stores map information including road curves and slopes in advance in its own storage area, and while the electric truck 1 is traveling, it sequentially receives GPS information via an antenna and displays it on the map. Identify the position of your vehicle. 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 is provided by various communication companies, and connects communication devices that exist at remote locations. The wireless communication network 20 may be either a public communication network or a dedicated communication network.

The data server 30 is installed at a location different from that of the electric truck 1, and is connected to the electric truck 1 and other vehicles via a wireless communication network 20 so as to be capable of telecommunications. Further, as shown in FIG. 1, the data server 30 has a communication unit 31, an arithmetic 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 via the wireless communication network 20 so as to be capable of telecommunications. Then, in such a communication state, the communication unit 31 receives various information of the electric truck 1 (for example, real-time traffic congestion information and other information on the actual electricity cost) from the electric truck 1, and receives map information, transportation weight information, and the like. And various other information is transmitted to the electric truck 1.

The arithmetic control unit 32 is a control circuit for integrated control of the data server 30. Specifically, the arithmetic control unit 32 controls the communication unit 31, stores various information received via the communication unit 31 in the data recording unit 33, or takes out various stored information and takes out each vehicle. Control to send to. Further, in FIG. 1, only the electric truck 1 is provided with the traveling route selection system of the present invention including the map information acquisition unit 11, the transportation weight information acquisition unit 12, the fluctuation information estimation unit 13, and the optimum route selection unit 14. However, the travel route selection system may be provided in the calculation control unit 32. That is, as described above, the arithmetic control unit 32 has 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 the optimum route to be selected is the electric truck 1. May be notified to.

The data recording unit 33 is composed of a general hard disk or a semiconductor memory. In addition, 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, the method of selecting the optimum route by the traveling route selection system (vehicle ECU 2) of the present invention will be specifically described with reference to FIGS. 2 and 3. Here, FIG. 2 is a flowchart showing a control routine related to optimum route selection executed by the vehicle ECU 2 of the present embodiment. Further, 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 transport weight information acquisition unit 12 relates to the load capacity (100 kg) at the transport start point O, the load capacity (20 kg) at the highland A, and the load capacity (80 kg) at the lowland B, as shown in FIG. Obtain transportation weight information.

Next, the fluctuation information estimation unit 13 of the vehicle ECU 2 estimates the fluctuation information of the load 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 has a first route from the transportation start point O to reach the lowland B via the highland A, and a first route from the transportation start point O to reach the highland A via the lowland B. Extract 2 routes. After that, the fluctuation information estimation unit 13 adds information on the load capacity 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 load capacity is 100 kg at the transportation start point O, the load capacity is 80 kg in the highland A, and then the load capacity is 0 kg in the lowland B. On the other hand, in the second route, it is estimated that the load capacity is 100 kg at the transportation start point O, the load capacity is 20 kg in the lowland B, and then the load capacity is 0 kg in the highland A.

Next, the optimum route selection unit 14 of the vehicle ECU 2 calculates the regenerative electric energy of the motor and the traveling power consumption of the electric truck 1 based on the total load weight estimated for each traveling section of each transportation route. After that, the optimum route selection unit 14 considers the calculation result as an element of basic information and selects the optimum route (step S4: optimum route selection step).

As a specific optimum route selection step, the optimum route selection unit 14 calculates the traveling power consumption (Elos 100) of the uphill road 40 and the regenerative electric energy (Egin 80) of the downhill road 50 in the first route shown in FIG. Further, the optimum route selection unit 14 calculates the regenerated electric energy (Egin100) of the downhill road 60 and the traveling power consumption (Elos20) of the uphill road 70 in the second route shown in FIG. Then, the optimum route selection unit 14 compares the calculation result (Elos100 + Elos20) in the first route with the calculation result (Egin100 + Elos20) in the second route, and optimizes the transportation route that can travel with better electricity cost with higher accuracy. It can be selected as a route.

As described above, selecting a transportation route in consideration of the amount of regenerative electric energy and the amount of running power consumption means that the total load weight is relatively heavy when the transportation route information includes a downhill road having a predetermined gradient or more. If the route is selected to run on the downhill road and the transportation route information includes uphill roads with a predetermined gradient or more, the route is selected to run on the uphill road with a relatively light gross load. Will be.

After that, the vehicle ECU 2 supplies the information regarding the optimum route to the navigation device 4, and the navigation device 4 starts the traveling guidance.

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, various information related to the transportation route and basic information including fluctuation information of the total load weight of the cargo can be obtained. Since the optimum route is selected based on this, it is possible to visualize the transportation cost with higher accuracy and select the transportation route that can substantially improve the electricity cost as compared with the conventional one. 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, it is possible to further improve the electric cost and reduce the transportation cost.

In particular, in the present embodiment, the regenerative electric energy of the motor and the traveling power consumption of the electric truck 1 are calculated based on the total load weight estimated for each traveling section of each transportation route, and the calculation results are compared. In order to select the optimum route, it is possible to select the optimum route with higher accuracy by using the numerical data that can be easily calculated.

In addition, when the transportation route information includes a downhill road with a predetermined slope or more, the optimum route is selected so that the vehicle travels on the downhill road with a relatively heavy total load weight, or the transportation route information includes a downhill road with a predetermined slope or more. When the uphill road is included, the optimum route can be selected so that the vehicle travels on the uphill road with a relatively light gross load, so that the optimum route can be selected in consideration of the amount of regenerative power and the amount of running power consumption. The selection will be realized, and the optimum route that can substantially reduce the electricity cost can be selected with higher accuracy.

In the description of the above embodiment, it was assumed that the cargo was only unloaded (that is, delivered) at the highlands A and the lowlands B, which are the cargo loading / unloading points, but the cargo was loaded (that is, delivered). Collection) may be assumed, and a case where the delivery and collection of cargo are performed at each point at the same time (that is, collection and delivery) can also be assumed. In addition, although there were only two places for loading and unloading luggage, highland A and lowland B, the same optimum route selection is performed even if there are three or more points.

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

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

The optimum route selection unit 14 according to the second embodiment further improves the electricity cost based on the map information acquired by the map information acquisition unit 11 and the basic information including the fluctuation information estimated by the fluctuation information estimation unit 13. Select the optimum route that the electric truck 1 can travel. More specifically, the optimum route selection unit 14 classifies the travel area in the map information according to the road condition, and selects the optimum route so as to travel in one of the classified travel areas based on the total load weight. To do.

For example, when the traveling area in the map information is classified into a lowland area and a highland area according to the altitude, the optimum route selection unit 14 travels in the lowland area with a relatively heavy total load weight, and the total load weight is high. Select the optimum route so that the vehicle travels in the highland area in a relatively light condition. Further, when the traveling area in the map information is classified into an uphill road area and a non-uphill road area according to the number of uphill roads having a predetermined slope or more, the optimum route selection unit 14 is in a state where the total loaded weight is relatively heavy and the non-uphill road is concerned. Select the optimum route so that the vehicle travels in the road area and travels in the uphill road area with a relatively light gross load. Further, when the traveling area in the map information is classified into a downhill road area and a non-downhill road area according to the number of downhill roads having a predetermined slope or more, the optimum route selection unit 14 is in a state where the total loaded weight is relatively heavy. Select the optimum route so that the vehicle travels in the area and travels in the non-downhill area with a relatively light gross load.

Here, the state where the total load weight is relatively heavy, the state where the total load weight is relatively light, the downhill road having a predetermined slope or more, and the uphill road having a predetermined slope or more are the same as those defined in the first embodiment. is there.

Next, a method of selecting the optimum route by the traveling route selection system (vehicle ECU 2) of the present invention will be specifically described with reference to FIGS. 4 to 10. Here, FIG. 4 is a flowchart showing a control routine related to optimum route selection executed by the vehicle ECU 2 of the present embodiment. 5 to 10 are conceptual diagrams of routes related to optimum route selection executed by the vehicle ECU 2 of the present embodiment. In particular, FIGS. 5 to 7 are route conceptual diagrams premised on delivery, and FIGS. 8 to 10 are route conceptual diagrams premised 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 provides transportation route information from the transportation start point O shown in FIGS. 5 to 10 to each luggage loading / unloading point (12 circle areas painted in black in the figure). , And various information such as transportation route information connecting each baggage loading / unloading point.

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 transport weight information acquisition unit 12 has a load capacity (110 kg) at the transport start point O and a load capacity (10 kg) at each baggage loading / unloading point shown in FIGS. 5 to 7. ), Acquire transportation weight information. On the other hand, when it is assumed that the cargo is collected, the transport weight information acquisition unit 12 relates to the load capacity (0 kg) at the transport start point O and the load capacity (10 kg) at each luggage loading / unloading point shown in FIGS. 8 to 10. Obtain transportation weight information.

Next, the fluctuation information estimation unit 13 of the vehicle ECU 2 estimates the fluctuation information of the load 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 from the transportation start point O via all of the baggage loading / unloading points. Here, the fluctuation information estimation unit 13 may extract a travel route that can be executed in consideration of time conditions such as delivery and collection / delivery as a transportation route. After that, the fluctuation information estimation unit 13 adds information on the load capacity at the transportation start point O and each baggage loading / unloading point for each transportation route.

In addition, in FIGS. 5 to 7, since delivery is premised, the load capacity is 110 kg at the transportation start point O, and the load capacity is reduced by 10 kg each time the cargo gets on and off. ing. On the other hand, in FIGS. 8 to 10, since collection is premised, the load capacity is 0 kg at the transportation start point O, and the load capacity increases by 10 kg each time the baggage is loaded and unloaded. ing. Further, in FIGS. 5 to 10, one of the finally determined optimum routes is shown.

Next, the optimum route selection unit 14 of the vehicle ECU 2 classifies the traveling area in the map information according to the road condition. After that, the optimum route selection unit 14 selects the optimum route so as to travel in any of the classified traveling areas based on the total load 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 capacity is relatively heavy (the load capacity is indicated by 110 kg to 60 kg, and the delivery is less than half completed. Travel in lowland area C (state), move from lowland area C to highland area D with a load capacity of 60 kg, and have a relatively light load capacity (load capacity is indicated by 50 kg to 0 kg, delivery is more than half). Select the optimum route so that the vehicle travels in the highland area D (in the finished state).

Further, as shown in FIG. 6, when the traveling area is classified into the non-uphill road area E and the uphill road area F, the load capacity is relatively heavy (the load capacity is indicated by 110 kg to 60 kg, and the delivery is completed by less than half). Traveling on the non-uphill road area E (without), moving from the non-uphill road area E to the uphill road area F with the load capacity of 60 kg, and the load capacity is relatively light (load capacity is 50 kg to 0 kg). Select the optimum route so that the vehicle travels on the uphill road area F (in the state where the delivery is completed by more than half as shown by).

Further, as shown in FIG. 7, when the traveling area is classified into the downhill road area G and the non-downhill road area H, the load capacity is relatively heavy (the load capacity is indicated by 110 kg to 60 kg, and the delivery is completed by less than half). Traveling on the downhill road area G (without), moving from the downhill road area G to the non-downhill road area H with a load capacity of 60 kg, and with a relatively light load capacity (load capacity of 50 kg to 0 kg). The optimum route is selected so as to travel in the non-downhill road area H (in the state where the delivery is completed by more than half as shown).

On the other hand, in the case of collection, when the traveling area is classified into lowland area C and highland area D as shown in FIG. 8, the load capacity is relatively light (the load capacity is indicated by 0 kg to 60 kg, and the collection is half. Travel in the highland area D with only the following completed), move from the highland area D to the lowland area C with a load capacity of 60 kg, and the load capacity is relatively heavy (load capacity is shown as 70 kg to 110 kg). Select the optimum route so that the vehicle travels in the lowland area C when the collection is completed by more than half.

Further, as shown in FIG. 9, when the traveling area is classified into the non-uphill road area E and the uphill road area F, the load capacity is relatively light (the load capacity is indicated by 0 kg to 60 kg, and the collection is completed by less than half). Traveling on the uphill road area F (without), moving from the uphill road area F to the non-uphill road area E with a load capacity of 60 kg, and with a relatively heavy load capacity (load capacity of 70 kg to 110 kg). Select the optimum route so that the vehicle travels on the non-uphill road area E (in the state where the collection is completed by more than half as shown).

Further, as shown in FIG. 10, when the traveling area is classified into the downhill road area G and the non-downhill road area H, the load capacity is relatively light (the load capacity is indicated by 0 kg to 60 kg, and the collection is completed by less than half). Traveling on the non-downhill road area H in the non-downhill road area H, moving from the non-downhill road area H to the downhill road area G with the load capacity of 60 kg, and the load capacity is relatively heavy (load capacity is 70 kg to 110 kg). Select the optimum route so that the vehicle travels on the downhill road area G (in the state where the collection is completed by more than half as shown by).

After that, the vehicle ECU 2 supplies the information regarding the optimum route to the navigation device 4, and the navigation device 4 starts the traveling guidance.

From 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 fluctuation information of the total load weight of the cargo. Since the optimum route is selected, it is possible to visualize the transportation cost and select the transportation route that can substantially improve the electricity cost as compared with the conventional one. That is, it is possible to further improve the electricity cost and reduce the transportation cost.

In particular, in the present embodiment, the traveling area in the map information is classified according to the road condition, and the optimum route is selected so as to travel in any of the classified traveling areas based on the total load weight. It is possible to select the optimum route with higher accuracy while preventing the route from becoming complicated.

Further, in the present embodiment, by classifying the traveling area into a highland area and a lowland area, an uphill road area and a non-uphill road area, or a downhill road area and a non-downhill road area, the regenerative electric energy of the motor and the electric truck 1 Numerical data such as the running power consumption of the vehicle will be taken into consideration, and the optimum route can be selected with higher accuracy.

In the description of the above embodiment, only the classification into two areas has been explained, but by classifying the traveling area into three or more areas, the optimum route can be selected with higher accuracy. You may.

1 Electric truck 2 Vehicle ECU (travel route selection system)
3 Communication unit 4 Navigation device 11 Map information acquisition unit (map information acquisition means)
12 Transport weight information acquisition unit (transport weight information acquisition means)
13 Fluctuation information estimation unit (variation information estimation means)
14 Optimal route selection unit (optimal route selection means)
20 Wireless communication network 30 Data server 31 Communication unit 32 Arithmetic control unit 33 Data recording unit 40 Uphill road 50 Downhill road 60 Downhill road 70 Uphill road

Claims (14)

It is a travel route selection system for electric trucks that uses a motor driven by electric power supplied from a battery as a drive source.
A map information acquisition means for acquiring map information including transportation start point information of the electric truck and transportation route information connecting a plurality of luggage loading / unloading points.
A transportation weight information acquisition means for acquiring transportation weight information including initial weight information of the initial load loaded at the transportation start point and loading / unloading weight information of the luggage loaded at the luggage loading / unloading point.
Based on the transportation weight information, the fluctuation information estimation means that estimates the fluctuation information of the total load weight that fluctuates during transportation for each of a plurality of transportation routes that pass from the transportation start point to all of the cargo loading / unloading points.
Based on the map information and the basic information including the change information, have a, and optimum route selecting means for selecting an optimum route from among the plurality of transport routes,
The optimum route selection means calculates and calculates the regenerated electric energy of the motor and the traveling power consumption of the electric truck for each of the plurality of transportation routes based on the fluctuation information estimated for each of the plurality of transportation routes. An electric truck traveling route selection system characterized in that the optimum route is selected by comparing the results. The optimum route selecting means, the transport if a route information includes a predetermined gradient over the downhill to claim 1 for selecting the best route to the loading total weight traveling downhill road the relatively heavy state The driving route selection system for electric trucks described in. The optimum route selection means claims that when the transportation 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 load weight. Or the traveling route selection system for the electric truck according to 2. The optimum route selection means claims to classify the traveling area in the map information according to the road condition and select the optimum route so as to travel in any of the classified traveling areas based on the total load weight. Item 1. The traveling route selection system for an electric truck according to item 1. When the optimum route selection means classifies the traveling area in the map information into a lowland area and a highland area according to the altitude, the optimum route selection means travels in the lowland area with the total load weight relatively heavy, and the total load weight is the same. The traveling route selection system for an electric truck according to claim 4 , wherein the optimum route is selected so as to travel in the highland area in a relatively light state. 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 according to the number of uphill roads having a predetermined gradient or more, the non-uphill road is in a state where the total loaded weight is relatively heavy. The traveling route selection system for an electric truck according to claim 4 or 5 , 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 load weight is relatively light. 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 according to the number of downhill roads having a predetermined gradient or more, the downhill road area is in a state where the total loaded weight is relatively heavy. The traveling route selection system for an electric truck according to any one of claims 4 to 6 , wherein the optimum route is selected so as to travel in the non-downhill road area in a state where the total load weight is relatively light. .. This is a method for selecting a travel route for an electric truck that uses a motor driven by electric power supplied from a battery as a drive source.
A map information acquisition step for acquiring map information including transportation start point information of the electric truck and transportation route information connecting a plurality of luggage loading / unloading points.
A transportation weight information acquisition step for acquiring transportation weight information including initial weight information of the initial load loaded at the transportation start point and loading / unloading weight information of the luggage loaded at the luggage loading / unloading point, and a transportation weight information acquisition step.
Based on the transportation weight information, the fluctuation information estimation step that estimates the fluctuation information of the total loading weight that fluctuates during transportation for each of a plurality of transportation routes that pass from the transportation start point to all of the cargo loading / unloading points, and
Based on the map information and the basic information including the change information, have a, and optimal route selection step of selecting an optimum route from among the plurality of transport routes,
In the optimum route selection step, the regenerated electric energy of the motor and the traveling power consumption of the electric truck are calculated and calculated for each of the plurality of transportation routes based on the fluctuation information estimated for each of the plurality of transportation routes. A method for selecting a traveling route of an electric truck, which comprises comparing the results and selecting the optimum route. In the optimum route selection step, the case contained transportation routes information in descending more than a predetermined gradient slope is, claim the loading total weight to select the best route to travel downhill road the relatively heavy state 8 How to select the driving route of the electric truck described in. In the optimum route selection step, when said predetermined slope or climbing road transport route information is included, it claims the loading total weight to select the best route to travel the uphill at relatively mild conditions 8 Alternatively, the method for selecting a traveling route for an electric truck according to 9. In the optimum route selection step, the travel area in the map information is classified according to the road condition, and the optimum route is selected so as to travel in any of the classified travel areas based on the total load weight. Item 10. The method for selecting a traveling route of an electric truck according to Item 10. 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 the altitude, the vehicle travels in the lowland area with the total load weight relatively heavy, and the total load weight is the same. The traveling route selection method for an electric truck according to claim 11 , wherein the optimum route is selected so as to travel in the highland area in a relatively light state. 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 according to the number of uphill roads having a predetermined gradient or more, the non-uphill road is in a state where the total loaded weight is relatively heavy. The traveling route selection method for an electric truck according to claim 11 or 12 , 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 load weight is relatively light. In the optimum route selection step, when the traveling area in the map information is classified into a downhill road area and a non-downhill road area according to the number of downhill roads having a predetermined slope or more, the downhill road area is in a state where the total loaded weight is relatively heavy. The method for selecting a traveling route of an electric truck according to any one of claims 11 to 13 , wherein the optimum route is selected so as to travel in the non-downhill road area in a state where the total load weight is relatively light. ..

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