Charging plan generation device

Abstract

In a charging plan generation apparatus, a charging plan generator obtains an energy change level of a first travel path as a first energy change level, and obtains an energy change level of a second travel path as a second energy change level. The charging plan generator is assigned according to a comparison between a first energy change level of the first driving path and a second energy change level of the second driving path based on a common stop time of the first electric vehicle and the second electric vehicle. To generate a first charging plan for the first electric vehicle and a second charging plan for the second electric vehicle accordingly.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application is based upon and claims the benefit of priority of Japanese Patent Application No. 2023-105922, filed on June 28, 2023, the disclosure of which is incorporated herein in its entirety by reference. Technical Field

[0003] The present disclosure relates to an apparatus for generating a charging plan for a plurality of electric vehicles. Background Art

[0004] Japanese Patent Application Publication No. 2022-118575 discloses a charging system for generating a charging plan that schedules charging of a plurality of electric vehicles.

[0005] The energy consumed by the travel of each electric vehicle may vary according to the situation related to the travel of the corresponding one of the electric vehicles. This is completely normal for different electric vehicles. Even for one electric vehicle, if the situation of the first travel path is different from the situation of the second travel path, the energy consumed by the electric vehicle traveling on the first travel path may be different from the energy consumed by the electric vehicle traveling on the second travel path. In addition to the change of the travel path, the energy consumed by the travel of the electric vehicle may also vary according to the driving operation of the electric vehicle.

[0006] The charging system disclosed in the patent publication may unfortunately generate a charging plan for multiple electric vehicles without taking into account such variations in the driving energy consumed by the multiple electric vehicles. As a result, this may cause the disclosed charging system to generate a driving plan with poor energy efficiency for the multiple electric vehicles. Summary of the invention

[0007] From this perspective, the present disclosure seeks to provide a method and a device, each of which is capable of generating a charging plan for each of a plurality of electric vehicles; the charging plan generated for each electric vehicle is capable of adapting to changes in the driving energy value consumed by the corresponding electric vehicle.

[0008] A first exemplary aspect of the present disclosure provides a charging plan generation device. The charging plan generation device includes a change calculator, which is configured to calculate the energy change level of (i) the value of the driving energy required for at least one electric vehicle to travel along a corresponding one of the multiple driving paths and (ii) one of the values ​​of at least one influencing factor of each of the multiple driving paths based on information related to the driving energy required for at least one electric vehicle to travel along each of the multiple driving paths. At least one influencing factor will affect the driving energy. The charging plan generation device includes a charging plan generator.

[0009] The charging plan generator is configured to obtain an energy change level of a first driving path included in the plurality of driving paths as a first energy change level, and obtain an energy change level of a second driving path included in the plurality of driving paths as a second energy change level.

[0010] The charging plan generator is configured to allocate available charging time to the first electric vehicle and the second electric vehicle based on a common stop time of the first electric vehicle and the second electric vehicle included in a first driving plan for the first electric vehicle and a second driving plan for the second electric vehicle, according to a comparison between a first energy change level of a first driving path and a second energy change level of a second driving path, so as to correspondingly generate a first charging plan for the first electric vehicle and a second charging plan for the second electric vehicle.

[0011] A second exemplary aspect of the present disclosure provides a charging device. The charging device includes a charging plan generating device according to the first exemplary aspect and a charging execution unit, wherein the charging execution unit is configured to execute charging of a first electric vehicle battery according to a first charging plan for a first electric vehicle, and to execute charging of a second electric vehicle battery according to a second charging plan for a second electric vehicle.

[0012] A third exemplary aspect of the present disclosure provides a charging program product for at least one processor. The charging program product includes a non-transitory computer-readable storage medium and a set of computer program instructions stored in the computer-readable storage medium. The above instructions enable at least one processor to calculate the energy change level of (i) the value of the driving energy required for at least one electric vehicle to travel along each of the multiple driving paths and (ii) one of the values ​​of at least one influencing factor for each of the multiple driving paths based on information related to the driving energy required for at least one electric vehicle to travel along each of the multiple driving paths. At least one influencing factor can affect the driving energy.

[0013] The above instructions enable at least one processor to obtain an energy change level of a first driving path included in a plurality of driving paths as a first energy change level, and to obtain an energy change level of a second driving path included in a plurality of driving paths as a second energy change level.

[0014] The above instructions cause at least one processor to allocate available charging time to the first electric vehicle and the second electric vehicle based on a common stop time of the first electric vehicle and the second electric vehicle included in a first driving plan for the first electric vehicle and a second driving plan for the second electric vehicle, according to a comparison between a first level of energy change of the first driving path and a second level of energy change of the second driving path, so as to generate a first charging plan for the first electric vehicle and a second charging plan for the second electric vehicle accordingly.

[0015] The first exemplary aspect to the third exemplary aspect respectively provide a charging plan generating device, a charging device and a charging program product, each of which is configured to allocate available charging time to a first electric vehicle and a second electric vehicle based on whether a first energy change level of a first driving path is greater than a second energy change level of a second driving path, thereby correspondingly generating a first charging plan for the first electric vehicle and a second charging plan for the second electric vehicle.

[0016] Since the first energy change level and the second energy change level of the corresponding first driving path and the second driving path depend on the driving energy consumed by the corresponding first electric vehicle and the second electric vehicle traveling along the first driving path and the second driving path, this construction of each of the above-mentioned charging plan generating device, charging device and charging program product enables the available charging time of the first electric vehicle and the second electric vehicle to be appropriately allocated based on the difference between the driving energy consumption of the first electric vehicle and the driving energy loss of the second electric vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Other aspects of the present disclosure will become apparent from the following description of embodiments with reference to the accompanying drawings, in which:

[0018] Figure 1 is a hardware and block diagram schematically showing an exemplary hardware configuration and functional components of a charging device according to a first embodiment;

[0019] Figure 2 is a flowchart schematically illustrating a charging plan generation routine executed by a charging device;

[0020] Figure 3A is a timing chart schematically showing an example of travel energy information related to at least one electric vehicle stored in a travel information memory;

[0021] Figure 3B is a timing chart schematically showing an example of a travel plan for a first electric vehicle;

[0022] Figure 3Cis a timing chart schematically showing an example of a travel plan for a second electric vehicle;

[0023] Figure 4 is a timing diagram schematically showing an example of a charging plan;

[0024] Figure 5A is a timing diagram schematically illustrating an example of a charging plan for a first electric vehicle;

[0025] Figure 5B is a timing diagram schematically showing an example of a charging plan for a second electric vehicle;

[0026] Figure 6 is a flowchart schematically showing a charging plan creation routine executed by the charging device according to the third embodiment. DETAILED DESCRIPTION

[0027] Hereinafter, exemplary embodiments of the present disclosure are described with reference to the accompanying drawings. In the embodiments and their variations, descriptions of similar parts between the exemplary embodiments and their variations are omitted or simplified with similar reference numerals marked as much as possible to avoid redundant descriptions.

[0028] First embodiment

[0029] Figure 1 2 is a hardware and block diagram schematically showing an exemplary hardware configuration and functional components of the charging device 2 according to the first embodiment. Figure 2 2 is a flowchart schematically showing a charging plan generation routine executed by the charging device 2 .

[0030] The charging device 2 is configured to generate charging plans for a plurality of available electric vehicles, and to charge the battery 52 in each available electric vehicle according to the generated charging plan for a corresponding one of the available electric vehicles.

[0031] That is, the charging device 2 can also function as a charging plan generating device for generating a charging plan for each available electric vehicle.

[0032] Specifically, the charging device 2 is configured as a computer system including, for example, a processor 2A such as a central processing unit (CPU), a memory device 2B, a storage device 2C, and a communication interface (I / F) 2D. These components 2A, 2B, 2C, and 2D are communicably connected to each other. The storage device can serve both the storage device 2B and the storage device 2C.

[0033] In addition, for example, Figure 1As shown, the charging device 2 functionally includes a variation calculator 101, a charging plan generator 102, and a charging execution unit 103. The storage device 2C includes a travel information memory 201 and a travel plan memory 202. The storage device 2C may be installed in the charging device 2 or separated from the charging device 2.

[0034] The CPU 2A is configured to execute one or more computer programs, ie, computer program instructions, installed in the memory device 2B to accordingly implement various functions corresponding to the one or more computer programs, including the above-mentioned functions 101 to 103 .

[0035] At least a portion of all functions provided by the charging device 2, including functions 101 to 103, may be implemented by at least one processor, such as CPU 2A, and the at least one processor may include:

[0036] (1) a combination of at least one memory and at least one programmable processing unit, i.e. at least one programmable logic circuit;

[0037] (2) at least one hardwired logic circuit;

[0038] (3) At least one hybrid circuit of hardwired logic and programmable logic.

[0039] The driving information storage 201 stores, for example, driving energy information related to at least one of the available electric vehicles for each available driving route i, the available driving routes including driving routes ia and ib.

[0040] The driving energy information associated with at least one electric vehicle for each driving route i includes values ​​of driving energy required for a plurality of driving actions of the at least one electric vehicle along the corresponding driving route i.

[0041] The value of the driving energy of at least one electric vehicle for each driving path i may be a measured value actually used for multiple driving actions of at least one electric vehicle along the corresponding driving path i, or may be a predicted value predicted for multiple driving actions of at least one electric vehicle along the corresponding driving path i.

[0042] The driving energy information related to the at least one electric vehicle may include a plurality of energy influencing factors, and the plurality of energy influencing factors have an influence on each value of the driving energy of the at least one electric vehicle.

[0043] The plurality of energy influencing factors influencing each value of the driving energy of at least one electric vehicle measured during the driving of at least one electric vehicle along each driving path i may include:

[0044] (I) a first energy influencing factor, the first energy influencing factor indicating a distance traveled by at least one electric vehicle along a corresponding driving path i, which distance will be referred to as a driving distance;

[0045] (II) a second energy influencing factor, the second energy influencing factor indicating a time required for at least one electric vehicle to travel along a corresponding driving path i, which time will be referred to as a driving time;

[0046] (III) a third energy influencing factor, i.e., a traffic influencing factor, wherein the third energy influencing factor indicates a traffic condition of the corresponding driving path i during the period when the at least one electric vehicle is traveling along the corresponding driving path i;

[0047] (IV) a fourth energy influencing factor, the fourth energy influencing factor indicating the number of stops of at least one electric vehicle along the corresponding driving path i;

[0048] (V) a fifth energy influencing factor, the fifth energy influencing factor indicating an average speed of at least one electric vehicle during the period when the at least one electric vehicle travels along the corresponding driving path i;

[0049] (VI) a sixth energy influencing factor indicating a number of changes in the driver of at least one electric vehicle during driving of the at least one electric vehicle along the corresponding driving path i;

[0050] (VI I) a seventh energy influencing factor, i.e., a driving operation change factor, the seventh energy influencing factor indicating a change in the driving operation of at least one electric vehicle during driving of the at least one electric vehicle along the corresponding driving path i;

[0051] (VIII) An eighth energy influencing factor, namely a weather condition factor, which indicates weather conditions during the driving of at least one electric vehicle along the corresponding driving path i.

[0052] The third energy influencing factor for at least one electric vehicle may include, for example:

[0053] (i) traffic volume, i.e., the count of vehicles passing through a predetermined driving path during the driving of at least one electric vehicle along the corresponding driving path i;

[0054] (ii) The average speed of the vehicles counted.

[0055] The seventh energy influencing factor for at least one electric vehicle may include, for example, the number of accelerations and the number of decelerations of the at least one electric vehicle during driving along the corresponding driving path i.

[0056] The eighth energy influencing factor for at least one electric vehicle may include: (i) changes in ambient temperature; (ii) changes in wind direction; and (iii) changes in wind force during travel of at least one electric vehicle along the corresponding travel path i.

[0057] Figure 3A An example of the traveling energy information related to at least one electric vehicle stored in the traveling information memory 201 is shown.

[0058] Specifically, the past ten driving actions of at least one electric vehicle along each driving path i, i.e., the first driving action to the tenth driving action, are performed, so that ten values ​​of driving energy, i.e., the first value TEV1(i) of driving energy to the tenth value TEV10(i) of driving energy, are measured for the corresponding first driving action to the tenth driving action.

[0059] At this time, the first traveling information item IT1(i) related to the first value TEV1(i) of traveling energy included in the traveling energy information to the tenth traveling information item IT10(i) related to the tenth value TEV10(i) of traveling energy are stored in the traveling information memory 201.

[0060] For example, the first driving information item I T1(i) includes: (i) a first driving energy value TEV1(i); (ii) a value FI 1(i) of a driving distance as a first influencing factor; (iii) a value FII 1(i) of a driving time as a second influencing factor; (iv) a value FIII 1(i) of a traffic volume as a third influencing factor; (v) a value FIV1(i) of the number of stops of at least one electric vehicle as a fourth influencing factor; (vi) a value FV1(i) of an average speed of at least one electric vehicle as a fifth influencing factor; (vii) a value FV I 1(i) of the number of driver changes of at least one electric vehicle as a sixth influencing factor; (viii) a value FV II A1(i) of the number of accelerations of at least one electric vehicle as a seventh influencing factor; (ix) a value FVI I B1(i) of the number of decelerations of at least one electric vehicle as a seventh influencing factor; and (x) a value FVIII 1(i) indicating a change in wind direction as an eighth influencing factor. Each of the remaining second to tenth travel information items I T2(i) to I T10(i) has substantially the same data configuration as that of the first travel information item I T1(i).

[0061] The driving plan memory 202 stores, for example, a driving plan for each electric vehicle; the driving plan for each electric vehicle indicates how the corresponding electric vehicle is scheduled to travel along each driving path i.

[0062] Specifically, the travel plan of each electric vehicle includes, for example, at least one actual travel time zone and at least one stop time zone.

[0063] Figure 3B The driving plan of an electric vehicle, that is, a first electric vehicle A included in a plurality of electric vehicles is illustrated. Specifically, the electric vehicle A is arranged to travel along a predetermined driving path ia from time t1 to time t2 and from time t3 to time t4. That is, Figure 3B The driving plan of the electric vehicle A shown includes a first actual driving time zone TTZ1 defined from time t1 to time t2 and a second actual driving time zone TTZ2 defined from time t3 to time t4. In addition, Figure 3B The driving plan shown includes a first stop time zone STZ1 defined before time t1, a second stop time zone STZ2 defined between time t2 and time t3, and a third stop time zone STZ3 defined after time t4. Each of the first to third stop time zones STZ1 to STZ3 represents a charging time during which the target electric vehicle A can be charged.

[0064] Figure 3C The driving plan of an electric vehicle, that is, a second electric vehicle B included in the plurality of electric vehicles is also exemplified. Figure 3C As shown, Figure 3C The driving plan of the electric vehicle B shown in FIG. Figure 3B The driving plan of the electric vehicle A shown in FIG. 1 is the same as that of the electric vehicle A, and therefore, the driving plan of the electric vehicle B includes the first actual driving time zone TTZ1 and the second actual driving time zone TTZ2 and the first to third stop time zones STZ1 to STZ3.

[0065] For ease of explanation, Figure 3B and Figure 3C It is shown that the travel plans of the electric vehicles A and B are determined so that the electric vehicles A, B are scheduled to travel during the same actual travel time zones TTZ1 and TTZ2, and stop during the same stop time zones STZ1 to STZ3.

[0066] In particular, the second stop time zone STZ2 defined between the first actual driving time zone TTZ1 and the second actual driving time zone TTZ2 is a common stop time zone for both electric vehicles A and B, so that the second stop time zone STZ2 is a chargeable time zone that is the only chargeable period between the actual driving schedules. In other words, the second stop time zone STZ2 needs to be shared by the charging of the electric vehicle A and the charging of the electric vehicle B. Therefore, the second stop time zone STZ2 will also be referred to as the limited total chargeable time Tsum between the actual driving schedules.

[0067] For example, each electric vehicle includes a vehicle drive system 50, which includes at least one motor, a battery 52, and a sensor SS. Specifically, the vehicle drive system 50 of each electric vehicle generates driving power based on direct current (DC) power supplied from the battery 52 to transmit the driving power, that is, torque, to the motor accordingly, so that at least one motor can be rotated. The rotation of at least one motor rotates the drive wheels of each electric vehicle, thereby causing the corresponding electric vehicle to travel.

[0068] The sensor SS and the battery 52 of each electric vehicle can communicate with the charging device 2 through the communication I / F 2D.

[0069] The sensor SS of each electric vehicle is configured to measure travel-related information related to the travel of the corresponding electric vehicle, and the vehicle drive system 50 of the corresponding electric vehicle is configured to transmit the measured travel-related information to the vehicle drive system 50 and the charging device 2 .

[0070] That is, the sensor SS of the selected electric vehicle is configured to measure at least the first influencing factor, the second influencing factor, the fourth influencing factor, the fifth influencing factor, the sixth influencing factor and the seventh influencing factor for each driving action of the selected electric vehicle in addition to the corresponding driving energy value, and the vehicle drive system 50 is configured to send the measured at least the first influencing factor, the second influencing factor, the fourth influencing factor, the fifth influencing factor, the sixth influencing factor and the seventh influencing factor to the charging device 2 in addition to the corresponding driving energy value for each driving action of the selected electric vehicle.

[0071] Furthermore, the sensor SS of each electric vehicle is configured to cyclically measure the state of charge (SOC) of the battery 52 , and the vehicle drive system 50 is configured to transmit the cyclically measured SOC of the battery 52 of the corresponding electric vehicle to the charging device 2 .

[0072] Various external sensors and / or servers ES capable of communicating with the communication device 2 via the communication I / F 2D are configured to obtain the third influencing factor and the eighth influencing factor for each driving action of at least one electric vehicle, and to send the obtained third influencing factor and the eighth influencing factor to the charging device 2 for each driving action of at least one electric vehicle.

[0073] Thus, as described above, the first driving information item IT1(i) associated with the first value TEV1(i) of driving energy included in the driving energy information to the tenth driving information item IT10(i) associated with the tenth value TEV10(i) of driving energy have been stored in the driving information memory 201.

[0074] The variation calculator 101 is configured to calculate a variation level of a value of an energy-related parameter, which is one of the driving energy and at least one of the first to eighth influencing factors, based on the first to tenth driving information items IT1(i) to IT10(i).

[0075] Specifically, the variation calculator 101 is configured to calculate one of (I) and (II):

[0076] (I) a change level from a first value TEV1(i) of driving energy to a tenth value TEV10(i) of driving energy for at least one electric vehicle traveling along a selected driving route I;

[0077] (II) A change level of a first value to a tenth value of at least one of the first to eighth influencing factors for the travel of at least one electric vehicle along the selected travel route i.

[0078] The charging plan generator 102 is configured to generate a first charging plan for electric vehicle A and a second charging plan for electric vehicle B during a limited total charging time Tsum based on (i) a driving plan for electric vehicle A stored in the driving plan memory 202, (ii) a driving plan for electric vehicle B stored in the driving plan memory 202, (iii) values ​​of energy-related parameters of a selected driving path ia among the available driving paths i for electric vehicle A, i.e., a first change level of driving energy or at least one of the first to eighth influencing factors, and (iv) values ​​of energy-related parameters of a selected driving path ib among the available driving paths i for electric vehicle B, i.e., a second change level of driving energy or at least one of the first to eighth influencing factors.

[0079] Specifically, the charging plan generator 102 is configured to determine whether a first change level of the value of the energy-related parameter of the selected travel route ia of electric vehicle A is greater than a second change level of the value of the energy-related parameter of the selected travel route ib of electric vehicle B.

[0080] Then, the charging plan generator 102 is configured to generate a first charging plan for the electric vehicle A and a second charging plan for the electric vehicle B, such that

[0081] (I) in a case where it is determined that a first change level of the value of the energy-related parameter of the selected driving route ia of electric vehicle A is greater than a second change level of the value of the energy-related parameter of the selected driving route ib of electric vehicle B, the charging time allocated to electric vehicle A is greater than the charging time allocated to electric vehicle B;

[0082] (II) When it is judged that the second change level of the value of the energy-related parameter of the selected driving path ib of electric vehicle B is greater than the first change level of the value of the energy-related parameter of the selected driving path ia of electric vehicle A, the charging time allocated to electric vehicle B is greater than the charging time allocated to electric vehicle A.

[0083] The charging execution unit 103 is configured to execute charging of the battery 52 of the electric vehicle A according to the first charging plan of the electric vehicle A, and to execute charging of the battery 52 of the electric vehicle B according to the second charging plan of the electric vehicle B.

[0084] The communication I / F 2D of the charging device 2 includes an input unit that enables an operator to input a request to generate a charging plan for each of the electric vehicles A, B.

[0085] Next, the following will use Figure 2 The flowchart of the present invention is used to describe a charging plan generation routine based on corresponding program instructions of one or more programs stored in the memory device 2B according to the first embodiment. For example, the CPU 2A is programmed to execute the charging plan generation routine in response to a charging plan generation request input by the operator through the communication I / F 2D.

[0086] When the charging plan generation routine is started, the CPU 2A functions as the variation calculator 101 to read, in step S001, the first driving information item IT1(i) to the tenth driving information item IT10(i) (see FIG. 10 ) related to the selected electric vehicle from the driving information memory 201. Figure 3A ).

[0087] Next, the CPU 2A is used as a change calculator 101 to obtain, in step S002, a first change level of the value of the energy-related parameter of the selected driving path ia for the electric vehicle A, i.e., the driving energy or the value of at least one of the first to eighth influencing factors, based on the first driving information item IT1(i) to the tenth driving information item IT10(i), and a second change level of the value of the energy-related parameter of the selected driving path ib for the electric vehicle B, i.e., the driving energy or the value of at least one of the first to eighth influencing factors, based on the first driving information item IT1(i) to the tenth driving information item IT10(i).

[0088] Specifically, in step S002, the CPU 2A functions as the variation calculator 101, thereby obtaining any one of the following as a first variation level of the value of the energy-related parameter for the selected travel route ia of the electric vehicle A:

[0089] (I) a change level of a first value TEV1 (i=ia) to a tenth value TEV10 (i=ia) of the driving energy for a selected driving route ia of the electric vehicle A;

[0090] (II) A change level of the first value to the tenth value of at least one of the first to eighth influencing factors for the selected driving route ia of the electric vehicle A.

[0091] For example, CPU 2A is used as a change calculator 101, thereby calculating the change of the first value TEV1 (i=ia) to the tenth value TEV10 (i=ia) of the driving energy as the change level of the first value TEV1 (i=ia) to the tenth value TEV10 (i=ia) of the driving energy, so as to correspondingly calculate the change σ(ia) of the energy required for the electric vehicle A to travel along the selected driving path ia.

[0092] Alternatively, the CPU 2A functions as the change calculator 101 to calculate the change σ(ia) of the energy required for the electric vehicle A to travel along the selected travel route ia as a change level of the first value to the tenth value of at least one of the first to eighth influencing factors according to the following formula f01A and based on a combination of selected two of the first to eighth influencing factors:

[0093] σ(ia)=σa1(ia)×σa2(ia)…(f01A)

[0094] in:

[0095] σa1(ia) represents a change in a selected one of the first to eighth influencing factors when the electric vehicle A travels along the selected travel path ia;

[0096] σa2(ia) represents a change in a selected alternative one of the first to eighth influencing factors when the electric vehicle A travels along the selected travel route ia.

[0097] Similarly, in step S002, the CPU 2A functions as the variation calculator 101, thereby calculating either one of (I) and (II) as a second variation level of the value of the energy-related parameter for the selected travel route ib of the electric vehicle B:

[0098] (I) a change level of a first value TEV1 (I=ib) to a tenth value TEV10 (I=ib) of the travel energy of the selected travel route ib of the electric vehicle B;

[0099] (II) A change level of the first value to the tenth value of at least one of the first to eighth influencing factors of the selected driving route ib of the electric vehicle B.

[0100] For example, the CPU 2A functions as the variation calculator 101 to calculate the variation of the first value TEV1 (i=ib) to the tenth value TEV10 (i=ib) of the traveling energy to correspondingly calculate the variation σ(ib) of the energy required for the electric vehicle B to travel along the selected traveling route ib.

[0101] Alternatively, the CPU 2A functions as the variation calculator 101 to calculate a variation σ(ib) of energy required for the electric vehicle B to travel along the selected travel route ib as a variation level of the first value to the tenth value of at least one of the first to eighth influencing factors according to the following formula f01 B and based on a combination of selected two of the first to eighth influencing factors:

[0102] σ(ib)=σb1(ib)×σb2(ib)…(f01B)

[0103] in:

[0104] σb1(ib) represents a change in a selected one of the first to eighth influencing factors when the electric vehicle B travels along the selected travel path ib;

[0105] σb2(ib) represents a change in a selected alternative one of the first to eighth influencing factors when the electric vehicle B travels along the selected travel route ib.

[0106] After the operation in step S002, the CPU 2A functions as the charging plan generator 102, thereby reading the travel plan of the electric vehicle A and the travel plan of the electric vehicle B from the travel plan memory 202 in step S003 (see FIG. 1 ). Figure 3B and Figure 3C ).

[0107] After the operation in step S003, CPU 2A is used as a charging plan generator 102, so as to generate a first charging plan for electric vehicle A and a second charging plan for electric vehicle B in step S004 based on (i) the driving plan for electric vehicle A stored in the driving plan memory 202, (ii) the driving plan for electric vehicle B stored in the driving plan memory 202, (iii) the first change level of the value of the energy-related parameter for the selected driving path ia of electric vehicle A, and (iv) the second change level of the value of the energy-related parameter for the selected driving path ib of electric vehicle B.

[0108] Specifically, CPU 2A is used as a charging plan generator 102, so that in step S004A1, based on the current SOC of the battery 52 of electric vehicle A, a predetermined basic charging time T(ia) required to charge the battery 52 in electric vehicle A to a predetermined SOC required for electric vehicle A to travel along a predetermined driving path ia is calculated, and based on the current SOC of the battery 52 in electric vehicle B, a predetermined basic charging time T(ib) required to charge the battery 52 in electric vehicle B to a predetermined SOC required for electric vehicle B to travel along a predetermined driving path ib is calculated.

[0109] Then, the CPU 2A functions as the charging plan generator 102, thereby calculating the charging margin time Tm_sum (see FIG. 1 ) in step S004A2 according to the following formula f02: Figure 4 ):

[0110] Tm_sum=Tsum-T(ia)-T(ib)...(f02)

[0111] Next, the CPU 2A functions as the charging plan generator 102, thereby allocating the charging margin time Tm_sum to both the electric vehicle A and the electric vehicle B as their additional charging times Tm(ia) and Tm(ib) according to the following formulas f03 and f04 in step S004A3:

[0112] Tm(ia)=Tm_sum×σ(ia) / {σ(ia)+σ(ib)}…(f03)

[0113] Tm(ib)=Tm_sum×σ(ib) / {σ(ia)+σ(ib)}…(f04)

[0114] in:

[0115] Tm_sum represents the charge margin time;

[0116] σ(ia) represents the change in the energy required for electric vehicle A to travel along the selected driving path ia;

[0117] σ(ib) represents the change in energy required for the electric vehicle B to travel along the selected travel route ib.

[0118] Next, CPU 2A is used as a charging plan generator 102, so that in step S004A4, the first charging plan of electric vehicle A is calculated as the sum of the basic charging time T(ia) and the additional charging time Tm(ia), and the second charging plan of electric vehicle B is calculated as the sum of the basic charging time T(ib) and the sum of the additional charging time Tm(ib).

[0119] After the operation in step S004 ( S004A4 ), the CPU 2A terminates the charging plan creation routine.

[0120] Thereafter, at a desired timing, for example, in response to a charging request input by the operator through the communication I / F 2D, the CPU 2A functions as the charging execution unit 103, thereby executing charging of the battery 52 of the electric vehicle A according to the first charging schedule of the electric vehicle A, and executing charging of the battery 52 of the electric vehicle B according to the second charging schedule of the electric vehicle B in step S005. After completing charging of the battery 52 of each of the electric vehicles A and B, the CPU 2A terminates the operation in step S005.

[0121] Specifically, Figure 5A The first charging plan of the electric vehicle A is shown as the sum of the basic charging time T(ia) and the additional charging time Tm(ia), which is represented by (T(ia)+Tm(ia)).

[0122] Similarly, Figure 5B The second charging plan of the electric vehicle B is shown as the sum of the basic charging time T(ib) and the additional charging time Tm(ib), which is represented by (T(ib)+Tm(ib)).

[0123] That is to say, Figure 5A and Figure 5B As shown, according to the charging device 2 of the first embodiment, the limited total chargeable time Tsum can be allocated to the electric vehicles A and B so that

[0124] (I) when it is determined that the change σ(ia) of the energy required for electric vehicle A to travel along the selected travel path ia is greater than the change σ(ib) of the energy required for electric vehicle B to travel along the selected travel path ib, the charging time allocated to electric vehicle A is greater than the charging time allocated to electric vehicle B;

[0125] (II) When it is determined that the change σ(ib) of the energy required for electric vehicle B to travel along the selected driving path ib is greater than the change σ(ia) of the energy required for electric vehicle A to travel along the selected driving path ia, the charging time allocated to electric vehicle B is greater than the charging time allocated to electric vehicle A.

[0126] The charging plan generator 102 according to the modification of the first embodiment may be configured to allocate the charging margin time Tm_sum to the additional charging time Tm(ia) for the electric vehicle A and the additional charging time Tm(ib) for the electric vehicle B according to the following (I) to (VI) in step S004A3:

[0127] (I) the travel plan of the electric vehicle A stored in the travel plan memory 202;

[0128] (II) the travel plan of the electric vehicle B stored in the travel plan memory 202;

[0129] (III) the change σ(ia) in the energy required for electric vehicle A to travel along the selected driving path ia;

[0130] (IV) the change σ(ib) in the energy required for electric vehicle B to travel along the selected driving path ib;

[0131] (V) charging the battery 52 of the electric vehicle A to a predetermined basic energy amount Ea required for the electric vehicle A to travel along the predetermined travel route ia;

[0132] (VI) The battery 52 of the electric vehicle B is charged to a predetermined basic energy amount Eb required for a predetermined SOC required for the electric vehicle B to travel along the predetermined travel route ib.

[0133] Specifically, the charging plan generator 102 may allocate the charging margin time Tm_sum to the additional charging time Tm(ia) for the electric vehicle A according to the following formula f05 in step S004A3:

[0134] Tm(ia)=Tm_sum×σ(ia) / {σ(ia)+σ(ib)}×Ea / (Ea+Eb)…(f05)

[0135] in:

[0136] Tm_sum represents the charge margin time;

[0137] σ(ia) represents the change in the energy required for electric vehicle A to travel along the selected driving path ia;

[0138] σ(ib) represents the change in the energy required for electric vehicle B to travel along the selected driving path ib;

[0139] Ea represents the basic amount of energy required to charge the battery 52 of the electric vehicle A to a predetermined SOC required for the electric vehicle A to travel along the predetermined travel route ia;

[0140] Eb represents a basic amount of energy required to charge the battery 52 of the electric vehicle B to a predetermined SOC required for the electric vehicle B to travel along the predetermined travel route ib.

[0141] In step S004A3, the CPU 2A functions as the charging plan generator 102, thereby additionally allocating the charging margin time Tm_sum to the additional charging time Tm(ib) for the electric vehicle B according to the following formula f06:

[0142] Tm(ib)=Tm_sum×σ(ib) / {σ(ia)+σ(ib)}×Eb / (Ea+Eb)…(f06)

[0143] Therefore, if the change in the energy and basic energy amount for one of electric vehicles A and B is greater than the change in the energy and basic energy amount for the other of electric vehicles A and B, the charging device 2 according to the variation of the first embodiment makes it possible to allocate a greater amount of the limited total chargeable time Tsum to one of electric vehicles A and B than to the other of electric vehicles A and B.

[0144] Second embodiment

[0145] A second embodiment of the present disclosure will be described below.

[0146] The configuration of the charging device 2 of the second embodiment is substantially the same as that of the first embodiment, except that the traveling energy information stored in the traveling information memory 201 of the second embodiment is different from that of the first embodiment.

[0147] That is, assuming a plurality of electric vehicles, they will be referred to as electric vehicle j (j is an integer greater than or equal to 2).

[0148] Specifically, the travel information memory 201 of the second embodiment stores, for example, travel energy information related to each electric vehicle j for each travel route i.

[0149] The traveling energy information related to each electric vehicle j for each traveling route i includes values ​​of traveling energy required for a plurality of traveling actions of each electric vehicle j along the corresponding traveling route i.

[0150] The value of the driving energy of each electric vehicle j for each driving path i may be a measured value actually used for multiple driving actions of the corresponding electric vehicle j along the corresponding driving path i, or may be a predicted value predicted for multiple driving actions of the corresponding electric vehicle j along the corresponding driving path i.

[0151] Specifically, similar to the first embodiment, the driving energy information related to each electric vehicle j for each driving path i is stored in the driving information memory 201, and the driving energy information includes, for example, the first to tenth driving information items. The first to tenth driving information items related to each electric vehicle j for each driving path i will be referred to as I T1(j, i) to I T10(j, i).

[0152] Specifically, in step S002, the CPU 2A functions as the variation calculator 101, thereby calculating any one of the following as a first variation level of the value of the energy-related parameter of the selected travel route ia of the electric vehicle A:

[0153] (I) a change level of a first value TEV1(j, i=ia) to a tenth value TEV10(j, i=ia) of the driving energy for each electric vehicle j along the selected driving route ia;

[0154] (II) A change level of the first value to the tenth value of at least one of the first to eighth influencing factors for the travel of each electric vehicle j along the selected travel route ia.

[0155] For example, CPU 2A is used as a change calculator 101, thereby calculating the change from the first value to the tenth value of the driving energy TEV1 (j, i=ia) to TEV10 (j, i=ia) as the change level of the first value to the tenth value of the driving energy TEV2 (i=ia) to TEV10 (i=ia), so as to correspondingly calculate the change σ(j, ia) of the energy required for each electric vehicle j to travel along the selected driving path ia.

[0156] Alternatively, the CPU 2A functions as the variation calculator 101 to calculate the variation σ(j, ia) of the energy required for each electric vehicle j to travel along the selected travel route ia as the variation level of the first value to the tenth value of at least one of the first to eighth influencing factors according to the following formula f07A:

[0157] σ(j,ia)=σa1(j,ia)×σa2(j,ia)(f07A)

[0158] in:

[0159] σa1(j, ia) represents a change in a selected one of the first to eighth influencing factors for each electric vehicle j traveling along the selected driving path ia;

[0160] σa2(j,ia) represents a change in a selected alternative one of the first to eighth influencing factors for each electric vehicle j traveling along the selected driving route ia.

[0161] Similarly, in step S002, the CPU 2A functions as the variation calculator 101, thereby calculating either one of (I) and (II) as a second variation level of the value of the energy-related parameter for the selected travel route ib of the electric vehicle B:

[0162] (I) a change level of a first value TEV1 (j, i=ib) to a tenth value TEV10 (j, i=ib) of the travel energy for each electric vehicle j along the selected travel route ib;

[0163] (II) A change level of the first value to the tenth value of at least one of the first to eighth influencing factors for the travel of each electric vehicle j along the selected travel route ib.

[0164] For example, CPU 2A is used as a change calculator 101 to calculate the change of the first value TEV1 (j, i=ib) to the tenth value TEV10 (j, i=ib) of the driving energy to correspondingly calculate the change σ(j, ib) of the energy required for each electric vehicle j to travel along the selected driving path ib.

[0165] Alternatively, the CPU 2A functions as the change calculator 101 to calculate the change amount σ(j, ib) of energy required for each electric vehicle j to travel along the selected travel route ib as a change level of the first value to the tenth value of at least one of the first to eighth influencing factors according to the following formula f07B and based on a combination of selected two of the first to eighth influencing factors:

[0166] σ(j,ib)=σa1(j,ib)×σa2(j,ib)(f07B)

[0167] in:

[0168] σa1(j, ib) represents a change in a selected one of the first to eighth influencing factors for each electric vehicle j traveling along the selected driving path ib;

[0169] σa2(j, ib) represents a change in a selected one of the first to eighth influencing factors for each electric vehicle j traveling along the selected driving route ib.

[0170] In step S004A3, the CPU 2A functions as the charging plan generator 102 to allocate the charging margin time Tm_sum to the additional charging time Tm(ia) for the electric vehicle A according to the following formula f08:

[0171] Tm(ia)=Tm_sum×σ(a, ia) / {σ(a, ia)+σ(b, ib)}…(f08)

[0172] in:

[0173] Tm_sum represents the charge margin time;

[0174] σ(a, ia) represents the change in the energy required for electric vehicle A to travel along the selected driving path ia;

[0175] σ(b, ib) represents the change in energy required for the electric vehicle B to travel along the selected travel route ib.

[0176] In step S004A3, the CPU 2A functions as the charging plan generator 102, thereby allocating the charging margin time Tm_sum to the additional charging time Tm(ib) for the electric vehicle B according to the following formula f09:

[0177] Tm(ib)=Tm_sum×σ(b, ib) / {σ(a, ia)+σ(b, ib)}…(f09)

[0178] in:

[0179] σ(a, ia) represents the change in the energy required for electric vehicle A to travel along the selected driving path ia;

[0180] σ(b, ib) represents the change in energy required for the electric vehicle B to travel along the selected travel route ib.

[0181] Therefore, according to the charging device 2 of the second embodiment, the limited total chargeable time Tsum can be allocated to the electric vehicles A and B so that

[0182] (I) when it is determined that the change σ(a, ia) of the energy required for electric vehicle A to travel along the selected travel path ia is greater than the change σ(b, ib) of the energy required for electric vehicle B to travel along the selected travel path ib, the charging time allocated to electric vehicle A is greater than the charging time allocated to electric vehicle B;

[0183] (II) When it is determined that the change σ(b, ib) in the energy required for electric vehicle B to travel along the selected driving path ib is greater than the change σ(a, ia) in the energy required for electric vehicle A to travel along the selected driving path ia, the charging time allocated to electric vehicle B is greater than the charging time allocated to electric vehicle A.

[0184] The charging plan generator 102 according to the modification of the second embodiment may be configured to allocate the charging margin time Tm_sum to the additional charging time Tm(ia) for the electric vehicle A and the additional charging time Tm(ib) for the electric vehicle B according to the following (I) to (VI) in step S004A3:

[0185] (I) the travel plan of the electric vehicle A stored in the travel plan memory 202;

[0186] (II) the travel plan of the electric vehicle B stored in the travel plan memory 202;

[0187] (III) the change σ(a, ia) in the energy required for electric vehicle A to travel along the selected driving path ia;

[0188] (IV) the change σ(b,ib) in the energy required for electric vehicle B to travel along the selected driving path ib;

[0189] (V) charging the battery 52 of the electric vehicle A to a basic energy amount Ea required to a predetermined SOC required for the electric vehicle A to travel along a predetermined travel route ia;

[0190] (VI) The battery 52 of the electric vehicle B is charged to a basic energy amount Eb required to a predetermined SOC required for the electric vehicle B to travel along the predetermined travel route ib.

[0191] Specifically, the charging plan generator 102 may allocate the charging margin time Tm_sum to the additional charging time Tm(ia) for the electric vehicle A according to the following formula f10 in step S004A3:

[0192] Tm(ia)=Tm_sum×σ(a, ia) / {σ(a, ia)+σ(b, ib)}×Ea / (Ea+Eb)…(f10)

[0193] in:

[0194] Tm_sum represents the charge margin time;

[0195] σ(a, ia) represents the change in the energy required for electric vehicle A to travel along the selected driving path ia;

[0196] σ(b, ib) represents the change in energy required for the electric vehicle B to travel along the selected travel route ib.

[0197] Ea represents the basic amount of energy required to charge the battery 52 of the electric vehicle A to a predetermined SOC required for the electric vehicle A to travel along the predetermined travel route ia;

[0198] Eb represents a basic amount of energy required to charge the battery 52 of the electric vehicle B to a predetermined SOC required for the electric vehicle B to travel along the predetermined travel route ib.

[0199] In step S004A3, the CPU 2A functions as the charging plan generator 102, thereby additionally allocating the charging margin time Tm_sum to the additional charging time Tm(ib) for the electric vehicle B according to the following formula f11:

[0200] Tm(ib)=Tm_sum×σ(b, ib) / {σ(a, ia)+σ(b, ib)}×Eb / (Ea+Eb)…(f11)

[0201] Therefore, if the change in the energy and basic energy amount of one of electric vehicles A and B is greater than the change in the energy and basic energy amount of the other of electric vehicles A and B, the charging device 2 according to the variant of the second embodiment can make the amount of the limited total charging time Tsum allocated to one of electric vehicles A and B greater than the amount allocated to the other of electric vehicles A and B.

[0202] Third embodiment

[0203] A third embodiment of the present disclosure will be described below.

[0204] The configuration of the charging device 2 of the third embodiment is substantially the same as that of the charging device 2 of the first embodiment, except that the charging device 2 is configured to calculate the energy prediction reliability degree for each travel route i as the change level of the energy-related parameter.

[0205] Specifically, the charging device 2 of the third embodiment performs the following operations before the charging plan generation routine. Figure 6 The prediction reliability calculation routine is performed for each driving path i shown.

[0206] When the prediction reliability calculation routine is started, the CPU 2A functions as the variation calculator 101, thereby Figure 6 In step S101, the predicted driving energy value is calculated based on the first value TEV1(i) to the tenth value TEV10(i) of the driving energy of each driving path i previously detected, or the predicted value of at least one selected from the first to eighth influencing factors is calculated based on the first value to the tenth value of at least one selected from the first to eighth influencing factors previously detected.

[0207] For example, the variation calculator 101 may calculate the average value of the first value TEV1(i) to the tenth value TEV10(i) of the previously detected driving energy for each driving path i as the predicted driving energy value of the corresponding driving path i. Alternatively, the variation calculator 102 may calculate the average value of the first value to the tenth value of the selected at least one of the first to eighth influencing factors previously detected for each driving path i as the predicted value of the selected at least one of the first to eighth influencing factors for the corresponding driving path i.

[0208] The predicted driving energy value for each driving path i or the predicted value of at least one selected from the first to eighth influencing factors for each driving path i is referred to as a prediction result Xprd(i).

[0209] After the operation in step S101, the CPU 2A functions as the variation calculator 101, thereby acquiring in step S102 an actual value of the driving energy required for the actual driving of at least one electric vehicle along each driving path i, or an actual value of a selected at least one of the first to eighth influencing factors required for the actual driving of at least one electric vehicle along each driving path i. For example, in step S102, the sensor SS of at least one electric vehicle may measure an actual driving energy value required for the driving of at least one electric vehicle along each driving path i, or measure an actual value of a selected at least one of the first to eighth influencing factors during the driving of at least one electric vehicle along each driving path i, and the CPU 2A may acquire the actual driving energy value for each driving path i, or an actual value of a selected at least one of the first to eighth influencing factors for each driving path i, from the sensor SS of the selected electric vehicle.

[0210] The actual driving energy value required for the actual driving of at least one electric vehicle along each driving path i or the actual value of at least one selected from the first to eighth influencing factors required for the actual driving of at least one electric vehicle along each driving path i is called the actual measurement result Xmes(i).

[0211] Note that if the predicted driving energy value of each driving path i is selected as the predicted result Xprd(i), the actual driving energy value of each driving path i is selected as the actual measurement result Xmes(i). Otherwise, if the predicted value of at least one of the first to eighth influencing factors for each driving path i is selected as the predicted result Xprd(i), the actual value of the selected at least one of the first to eighth influencing factors for each driving path i is selected as the actual measurement result Xmes(i).

[0212] After the operation in step S102, the CPU 2A functions as the variation calculator 101 to calculate the prediction reliability R(i) of each travel path i in step S103 according to the following formula (f12):

[0213] R(i)=Xprd(i) / Xmes(i)…(f12)

[0214] That is, the prediction reliability R(i) of each driving path i represents the degree of deviation between the prediction result Xprd(i) and the actual measurement result Xmes(i) for the corresponding driving path i.

[0215] Then, the CPU 2A functions as the variation calculator 101 , thereby storing the prediction reliability R(i) for each travel route i in the travel information memory 201 in step S103 .

[0216] After the operation in step S103, similarly to the operation in step S004, the CPU 2A functions as the charging plan generator 102, thereby generating in step S104 a first charging plan for the electric vehicle A and a second charging plan for the electric vehicle B based on (i) the driving plan for the electric vehicle A stored in the driving plan memory 202, (ii) the driving plan for the electric vehicle B stored in the driving plan memory 202, and (iii) the prediction reliability R(i) for each driving path i (see Figure 4 ).

[0217] Specifically, CPU 2A is used as a charging plan generator 102, thereby calculating the basic charging time T(ia) of electric vehicle A and the basic charging time T(ib) of electric vehicle B in step S104A1 similarly to the operation in step S004A1, and calculating the charging margin time Tm_sum according to the above formula f02 in step S104A2 similarly to the operation in step S0104A2.

[0218] Next, in step S104A3, the CPU 2A functions as the charging plan generator 102, thereby allocating the charging margin time Tm_sum to both the electric vehicle A and the electric vehicle B as their additional charging times Tm(ia) and Tm(ib) according to the following formulas f13 and f14:

[0219] Tm(ia)=Tm_sum×R(ib) / {R(ia)+R(ib)}…(f13)

[0220] Tm(ib)=Tm_sum×R(ia) / {R(ia)+R(ib)}…(f14)

[0221] in:

[0222] Tm_sum represents the charge margin time;

[0223] R(ia) represents the prediction reliability of the selected driving path ia;

[0224] R(ib) represents the prediction reliability of the selected driving path ib.

[0225] Next, similar to the operation in step S004A4, in step S104A4, CPU 2A is used as a charging plan generator 102, thereby calculating a first charging plan for electric vehicle A as the sum of a basic charging time T(ia) and an additional charging time Tm(ia), and calculating a second charging plan for electric vehicle B as a basic charging time T.

[0226] After the operation in step S104 ( S104A4 ), the CPU 2A terminates the charging plan creation routine.

[0227] Thereafter, at a desired timing, for example, in response to a charging request input by the operator through the communication I / F 2D, the CPU 2A functions as the charging execution unit 103, thereby executing charging of the battery 52 of the electric vehicle A according to the first charging plan of the electric vehicle A, and executing charging of the battery 52 of the electric vehicle B according to the second charging plan of the electric vehicle B in step S105. Thereafter, the CPU 2A terminates the charging plan generation routine.

[0228] Specifically, Figure 5A A first charging plan for the electric vehicle A is shown as the sum of a basic charging time T(ia) and an additional charging time Tm(ia), which is represented by (T(ia)+Tm(ia)).

[0229] Similarly, Figure 5B The second charging plan of the electric vehicle B is shown as the sum of the basic charging time T(ib) and the additional charging time Tm(ib), which is represented by (T(ib)+Tm(ib)).

[0230] That is to say, Figure 5A and Figure 5B As shown, according to the charging device 2 of the first embodiment, the limited total chargeable time Tsum can be allocated to the electric vehicles A and B so that

[0231] (I) when it is determined that the prediction reliability R(ib) of the selected driving path ib is greater than the prediction reliability R(ia) of the selected driving path ia, the charging time allocated to the electric vehicle A is greater than the charging time allocated to the electric vehicle B;

[0232] (II) When it is determined that the prediction reliability R(ia) of the selected driving route ia is greater than the prediction reliability R(ib) of the selected driving route ib, the charging time allocated to electric vehicle B is greater than the charging time allocated to electric vehicle A.

[0233] That is, as long as the prediction reliability of the travel path of one of the electric vehicles A and B is lower than the prediction reliability of the travel path of the other of the electric vehicles A or B, the allocation of the total chargeable time Tsum to one of the electric vehicles A and B is greater than the allocation of the total chargeable time Tsum to the other of the electric vehicles A and B. This is because the higher the prediction reliability for each travel path i, the smaller the level of change in the value of the energy-related parameter for the corresponding travel path i, and the lower the prediction reliability for each travel path i, the greater the level of change in the value of the energy-related parameter for the corresponding travel path i.

[0234] The charging plan generator 102 according to the modification of the third embodiment may be configured to allocate the charging margin time Tm_sum to the additional charging time Tm(ia) for the electric vehicle A and the additional charging time Tm(ib) for the electric vehicle B according to the following (I) to (VI) in step S104A3:

[0235] (I) a travel plan for electric vehicle A stored in the travel plan memory 202;

[0236] (II) the travel plan for electric vehicle B stored in the travel plan memory 202;

[0237] (III) The prediction reliability R(ia) of the selected driving path ia;

[0238] (IV) the prediction reliability R(ib) of the selected driving path ib;

[0239] (V) charging the battery 52 of the electric vehicle A to an amount of energy Ea required to reach a predetermined SOC required for the electric vehicle A to travel along a predetermined travel route ia;

[0240] (VI) The battery 52 of the electric vehicle B is charged to a basic energy amount Eb required to a predetermined SOC required for the electric vehicle B to travel along the predetermined travel route ib.

[0241] Specifically, the charging plan generator 102 may allocate the charging margin time Tm_sum to the additional charging time Tm(ia) for the electric vehicle A according to the following formula f15 in step S104A3:

[0242] Tm(ia)=Tm_sum×{Ea / (Ea+Eb)}×R(ib) / {R(ia)+R(ib)}…(f15)

[0243] in:

[0244] Tm_sum represents the charge margin time;

[0245] R(ia) represents the prediction reliability of the selected driving path ia;

[0246] R(ib) represents the prediction reliability of the selected driving path ib.

[0247] Ea represents the basic amount of energy required to charge the battery 52 of the electric vehicle A to a predetermined SOC required for the electric vehicle A to travel along the predetermined travel route ia;

[0248] Eb represents a basic amount of energy required to charge the battery 52 of the electric vehicle B to a predetermined SOC required for the electric vehicle B to travel along the predetermined travel route ib.

[0249] In step S104A3, the CPU 2A functions as the charging plan generator 102, thereby additionally allocating the charging margin time Tm_sum to the additional charging time Tm(ib) for the electric vehicle B according to the following formula f16:

[0250] Tm(ib)=Tm_sum×{Eb / (Ea+Eb)}×R(ia) / {R(ia)+R(ib)}…(f16)

[0251] Therefore, if the change in the energy and basic energy amount of one of electric vehicles A and B is greater than the change in the energy and basic energy amount of the other of electric vehicles A and B, the charging device 2 according to the variant of the third embodiment can make the amount of the limited total charging time Tsum allocated to one of electric vehicles A and B greater than the amount allocated to the other of electric vehicles A and B.

[0252] Fourth embodiment

[0253] A fourth embodiment of the present disclosure will be described below.

[0254] The configuration of the charging device 2 of the fourth embodiment is substantially the same as that of the charging device 2 of the third embodiment, except that the traveling energy information stored in the traveling information memory 201 of the fourth embodiment is different from the traveling energy information stored in the traveling information memory 201 of the third embodiment.

[0255] That is, a plurality of electric vehicles are assumed, which are referred to as electric vehicle j (j is an integer greater than or equal to 2).

[0256] The travel information memory 201 of the fourth embodiment stores, for example, travel energy information on each electric vehicle j for each travel route i.

[0257] The traveling energy information related to each electric vehicle j for each traveling route i includes values ​​of traveling energy required for a plurality of traveling actions of each electric vehicle j along the corresponding traveling route i.

[0258] The value of the driving energy of each electric vehicle j for each driving path i may be a measured value of multiple driving actions of the actual corresponding electric vehicle j along the corresponding driving path i, or may be a predicted value predicted for multiple driving actions of the corresponding electric vehicle j along the corresponding driving path i.

[0259] The driving energy information related to each electric vehicle j for each driving path i is stored in the driving information memory 201, and the driving energy information includes, for example, first to tenth driving information items. The first to tenth driving information items related to each electric vehicle j for each driving path i will be referred to as IT1(j, i) to IT10(j, i).

[0260] Specifically, in step S101, CPU 2A is used as a change calculator 101 to calculate a predicted driving energy value based on the first value TEV1(j, i) to the tenth value TEV10(j, i) of the driving energy previously detected for each electric vehicle j traveling along each driving path i, or to calculate a predicted value of at least one selected one of the first to eighth influencing factors based on the first value to the tenth value of at least one selected one of the first to eighth influencing factors previously detected for each electric vehicle j traveling along each driving path i.

[0261] The predicted driving energy value for each electric vehicle j traveling along each driving path i or the predicted value of at least one selected from the first to eighth influencing factors for each electric vehicle j traveling along each driving path i is called the prediction result Xprd(j, i).

[0262] After the operation in step S101, CPU 2A is used as a change calculator 101, thereby obtaining in step S102 the actual value of the driving energy required for the actual driving of each electric vehicle j along each driving path i, or the actual value of at least one selected from the first to eighth influencing factors required for the actual driving of each electric vehicle i along each driving path i.

[0263] The actual driving energy value required for the actual driving of each electric vehicle j along each driving path i or the actual value of at least one selected from the first to eighth influencing factors required for the actual driving of each electric vehicle j along each driving path i is called the actual measurement result Xmes(j, i).

[0264] Note that if the predicted driving energy value of each electric vehicle j and each driving path i is selected as the predicted result Xprd(j, i), the actual driving energy value of each electric vehicle j and each driving path i is selected as the actual measurement result Xmes(j, i). Otherwise, if the predicted value of at least one selected from the first to eighth influencing factors for each electric vehicle j and each driving path i is selected as the predicted result Xprd(j, i), the actual value of at least one selected from the first to eighth influencing factors for each electric vehicle j and each driving path i is selected as the actual measurement result Xmes(j, i).

[0265] After the operation in step S102, the CPU 2A functions as the variation calculator 101 to calculate the prediction reliability R(j, i) of each electric vehicle j and each travel path i according to the following formula (f17) in step S103:

[0266] R(j,i)=Xprd(j,i) / Xmes(j,i)...(f17)

[0267] Then, the CPU 2A functions as the variation calculator 101 , thereby storing the prediction reliability R(j, i) for each electric vehicle j and for each travel path i in the travel information memory 201 in step S103 .

[0268] After the operation in step S103, similar to the operation in step S004, CPU 2A functions as a charging plan generator 102, thereby generating a first charging plan for electric vehicle A and a second charging plan for electric vehicle B in step S104 based on (i) the driving plan for electric vehicle A stored in the driving plan memory 202, (ii) the driving plan for electric vehicle B stored in the driving plan memory 202, and (iii) the predicted reliability R(i) for each electric vehicle j and for each driving path i.

[0269] Specifically, in step S104A3, the CPU 2A functions as the charging plan generator 102, thereby allocating the charging margin time Tm_sum to the additional charging time Tm(ia) for the electric vehicle A according to the following formula f18:

[0270] Tm(ia)=Tm_sum×R(b, ib) / {R(a, ia)+R(b, ib)}…(f18)

[0271] in:

[0272] Tm_sum represents the charge margin time;

[0273] R(a, ia) represents the prediction reliability of the electric vehicle A and the selected driving path ia;

[0274] R(b, ib) represents the prediction reliability of the electric vehicle B and the selected driving path ib.

[0275] In step S104A3, the CPU 2A functions as the charging plan generator 102, thereby allocating the charging margin time Tm_sum to the additional charging time Tm(ib) for the electric vehicle B according to the following formula f19:

[0276] Tm(ib)=Tm_sum×R(a, ia) / {R(a, ia)+R(b, ib)}…(f19)

[0277] in:

[0278] R(a, ia) represents the prediction reliability of the electric vehicle A and the selected driving path ia;

[0279] R(b, ib) represents the prediction reliability of the electric vehicle B and the selected driving path ib.

[0280] Therefore, according to the charging device 2 of the fourth embodiment, the limited total chargeable time Tsum can be allocated to the electric vehicles A and B so that

[0281] (I) when it is determined that the predicted reliability R(b, ib) of electric vehicle B and the selected driving path ib is greater than the predicted reliability R(a, ia) of electric vehicle A and the selected driving path ia, the charging time allocated to electric vehicle A is greater than the charging time allocated to electric vehicle B;

[0282] (II) When it is determined that the predicted reliability R(a, ia) of electric vehicle A and the selected driving path ia is greater than the predicted reliability R(b, ib) of electric vehicle B and the selected driving path ib, the charging time allocated to electric vehicle B is greater than the charging time allocated to electric vehicle A.

[0283] The charging plan generator 102 according to the modification of the fourth embodiment enables, in step S104A3, the charging margin time Tm_sum to be allocated to the additional charging time Tm(ia) for the electric vehicle A and the additional charging time Tm(ib) for the electric vehicle B according to the following (I) to (VI):

[0284] (I) a travel plan for electric vehicle A stored in the travel plan memory 202;

[0285] (II) the travel plan for electric vehicle B stored in the travel plan memory 202;

[0286] (III) the prediction reliability R(a, ia) of the electric vehicle A and the selected driving path ia;

[0287] (IV) the predicted reliability R(b, ib) of the electric vehicle B and the selected driving path ib;

[0288] (V) charging the battery 52 of the electric vehicle A to a basic energy amount Ea required to a predetermined SOC required for the electric vehicle A to travel along a predetermined travel route ia;

[0289] (VI) The battery 52 of the electric vehicle B is charged to a basic energy amount Eb required to a predetermined SOC required for the electric vehicle B to travel along the predetermined travel route ib.

[0290] Specifically, the charging plan generator 102 may allocate the charging margin time Tm_sum to the additional charging time Tm(ia) for the electric vehicle A according to the following formula f20 in step S104A3:

[0291] Tm(ia)=Tm_sum×{Ea / (Ea+Eb)}×R(b, ib) / {R(a, ia)+R(b, ib)}…(f20)

[0292] in:

[0293] Tm_sum represents the charge margin time;

[0294] R(a, ia) represents the prediction reliability of the electric vehicle A and the selected driving path ia;

[0295] R(b, ib) represents the prediction reliability of electric vehicle b and selected driving path ib;

[0296] Ea represents the basic amount of energy required to charge the battery 52 of the electric vehicle A to a predetermined SOC required for the electric vehicle A to travel along the predetermined travel route ia;

[0297] Eb represents a basic amount of energy required to charge the battery 52 of the electric vehicle B to a predetermined SOC required for the electric vehicle B to travel along the predetermined travel route ib.

[0298] In step S004A3, the CPU 2A functions as the charging plan generator 102, thereby additionally allocating the charging margin time Tm_sum to the additional charging time Tm(ib) for the electric vehicle B according to the following formula f21:

[0299] Tm(ib)=Tm_sum×{Eb / (Ea+Eb)}×R(a, ia) / {R(a, ia)+R(b, ib)}…(f21)

[0300] Therefore, if the change in the energy and basic energy amount of one of electric vehicles A and B is greater than the change in the energy and basic energy amount of the other of electric vehicles A and B, the charging device 2 according to the variant of the fourth embodiment can make the amount of the limited total charging time Tsum allocated to one of electric vehicles A and B greater than the amount allocated to the other of electric vehicles A and B.

[0301] The present disclosure includes the following first to eleventh technical concepts.

[0302] The first technical concept is a charging plan generating device (2). The charging plan generating device (2) includes a variation calculator (101), which is configured to calculate, based on information related to the driving energy required for at least one electric vehicle to travel along each of a plurality of driving paths, (i) a value of the driving energy required for at least one electric vehicle to travel along each of a plurality of driving paths and (ii) an energy variation level of one of the values ​​of at least one influencing factor for each of the plurality of driving paths. The at least one influencing factor affects the driving energy.

[0303] The charging plan generating device (2) includes a charging plan generator (102), which is configured to obtain an energy change level of a first driving path included in a plurality of driving paths as a first energy change level, and to obtain an energy change level of a second driving path included in a plurality of driving paths as a second energy change level.

[0304] The charging plan generator (102) is configured to allocate available charging time to the first electric vehicle and the second electric vehicle based on a common stop time of the first electric vehicle and the second electric vehicle included in a first driving plan for the first electric vehicle and a second driving plan for the second electric vehicle, according to a comparison between a first energy change level of a first driving path and a second energy change level of a second driving path, so as to generate a first charging plan for the first electric vehicle and a second charging plan for the second electric vehicle accordingly.

[0305] In a second technical concept dependent on the first technical concept, the charging plan generator is configured to determine the allocation of available charging time to the first electric vehicle and the second electric vehicle such that

[0306] (I) when it is determined that the first energy change level of the first driving route is greater than the second energy change level of the second driving route, a first charging time included in the available charging time and allocated to the first electric vehicle is greater than a second charging time included in the available charging time and allocated to the second electric vehicle;

[0307] (II) When it is determined that the second energy change level of the second driving path is greater than the first energy change level of the first driving path, the second charging time included in the available charging time and allocated to the second electric vehicle is greater than the first charging time included in the available charging time and allocated to the first electric vehicle.

[0308] In a third technical concept dependent on the first technical concept, a change calculator is configured to calculate an energy change level of a value of driving energy required for at least one electric vehicle to travel along a corresponding one of a plurality of driving paths as an energy change level for each of the plurality of driving paths.

[0309] The charging plan generator is configured to obtain an energy change level of the first driving route as a first energy change level, and to obtain an energy change level of the second driving route as a second energy change level.

[0310] The charging plan generator is configured to determine an allocation of available charging time to the first electric vehicle and the second electric vehicle such that

[0311] (I) when it is determined that the first energy change level is greater than the second energy change level, a first charging time included in the available charging time and allocated to the first electric vehicle is greater than a second charging time included in the available charging time and allocated to the second electric vehicle;

[0312] (II) When it is determined that the second energy change level is greater than the first energy change level, the second charging time included in the available charging time and allocated to the second electric vehicle is greater than the first charging time included in the available charging time and allocated to the first electric vehicle.

[0313] In a fourth technical concept that depends on any one of the first to third technical concepts, the value of the driving energy required for at least one electric vehicle to travel along each of a plurality of driving paths includes (i) a measured value of the driving energy actually used when the at least one electric vehicle travels along a corresponding one of the plurality of driving paths and (ii) one of a predicted value of the driving energy required for the at least one electric vehicle to travel along a corresponding one of the plurality of driving paths.

[0314] The at least one influencing factor of each of the plurality of driving paths includes:

[0315] (I) a first energy influencing factor, the first energy influencing factor indicating a distance traveled by at least one electric vehicle along a corresponding one of a plurality of travel paths;

[0316] (II) a second energy influencing factor, the second energy influencing factor indicating a time required for at least one electric vehicle to travel along a corresponding one of the plurality of travel paths;

[0317] (III) a third energy influencing factor indicating a traffic condition of a corresponding one of the plurality of driving paths during driving of the at least one electric vehicle along the corresponding one of the plurality of driving paths;

[0318] (IV) a fourth energy influencing factor indicating a number of stops of at least one electric vehicle along a corresponding one of the plurality of driving paths;

[0319] (V) a fifth energy influencing factor indicating an average speed of at least one electric vehicle during driving of at least one electric vehicle along a corresponding one of the plurality of driving paths;

[0320] (VI) a sixth energy influencing factor indicating a number of changes in a driver of at least one electric vehicle during driving of at least one electric vehicle along a corresponding one of the plurality of driving routes;

[0321] (VI I) a seventh energy influencing factor indicating a change in driving operation of at least one electric vehicle during driving of at least one electric vehicle along a corresponding one of the plurality of driving routes;

[0322] (VIII) An eighth energy influencing factor indicating weather conditions during driving of at least one electric vehicle along a corresponding one of the plurality of driving routes.

[0323] In a fifth technical concept dependent on the first technical concept, a change calculator is configured to calculate, as an energy change level, (i) a value of driving energy required for at least one electric vehicle to travel along each of a plurality of driving paths and (ii) an energy change in one of the values ​​of at least one influencing factor for each of the plurality of driving paths.

[0324] The charging plan generator is configured to obtain an energy change of the first driving route as a first energy change, and to obtain an energy change of the second driving route as a second energy change.

[0325] The charging plan generator is configured to determine an allocation of available charging time to the first electric vehicle and the second electric vehicle such that

[0326] (I) when it is determined that the first energy change of the first driving path is greater than the second energy change of the second driving path, the first charging time included in the available charging time and allocated to the first electric vehicle is greater than the second charging time included in the available charging time and allocated to the second electric vehicle;

[0327] (II) When it is determined that the second energy change of the second driving path is greater than the first energy change of the first driving path, the second charging time included in the available charging time and allocated to the second electric vehicle is greater than the first charging time included in the available charging time and allocated to the first electric vehicle.

[0328] In a sixth technical concept dependent on the first technical concept, at least one electric vehicle includes a plurality of electric vehicles, and a change calculator is configured to calculate (i) a value of driving energy required for each of the plurality of electric vehicles to travel along each of a plurality of driving paths and (ii) an energy change level of one of the values ​​of at least one influencing factor for each of the plurality of driving paths.

[0329] In a seventh technical concept dependent on the sixth technical concept, a change calculator is configured to calculate, as an energy change level, (i) a value of driving energy required for each of a plurality of electric vehicles to travel along each of a plurality of driving paths and (ii) one of a value of at least one influencing factor for each of the plurality of driving paths.

[0330] In an eighth technical concept dependent on the first technical concept, a change calculator is configured to calculate a predicted energy parameter for each of a plurality of driving paths based on (i) a value of driving energy required for at least one electric vehicle to travel along a corresponding one of a plurality of driving paths and (ii) one of the values ​​of at least one influencing factor for a corresponding one of the plurality of driving paths.

[0331] The change calculator is configured to calculate an actual measured energy parameter for each of the multiple driving paths based on (i) an actual measured value of driving energy required for at least one electric vehicle to travel along a corresponding one of the multiple driving paths and (ii) one of the actual measured values ​​of at least one influencing factor for the corresponding one of the multiple driving paths.

[0332] The change calculator is configured to calculate a deviation between a predicted energy parameter and an actually measured energy parameter for each of the plurality of driving paths, and to calculate a deviation between the predicted energy parameter and the actually measured energy parameter for a corresponding one of the plurality of driving paths as an energy change level for each of the plurality of driving paths.

[0333] In a ninth technical concept dependent on the eighth technical concept, the at least one electric vehicle includes a plurality of electric vehicles. The variation calculator is configured to calculate a predicted energy parameter for each of the plurality of driving paths based on (i) a value of driving energy required for each of the plurality of electric vehicles to travel along a corresponding one of the plurality of driving paths and (ii) one of a value of at least one influencing factor for the corresponding one of the plurality of driving paths.

[0334] The change calculator is configured to calculate an actual energy parameter for each of the multiple driving paths based on (i) an actual measured value of the driving energy required for each of the multiple electric vehicles to travel along a corresponding one of the multiple driving paths and (ii) one of the actual measured values ​​of at least one influencing factor for the corresponding one of the multiple driving paths.

[0335] The tenth technical concept is a charging device, which includes a charging plan generating device according to any one of the first to ninth technical concepts and a charging execution unit (103), wherein the charging execution unit is configured to charge a first electric vehicle battery according to a first charging plan for a first electric vehicle, and to charge a second electric vehicle battery according to a second charging plan for a second electric vehicle.

[0336] The eleventh technical concept is a charging program product for at least one processor. The program product includes a non-transitory computer-readable storage medium and a set of computer program instructions stored in the computer-readable storage medium. The above instructions enable the above at least one processor

[0337] (I) calculating an energy change level of one of the following (i) and (ii) based on information related to driving energy required for at least one electric vehicle to travel along each of a plurality of driving paths: (i) a value of the driving energy required for at least one electric vehicle to travel along each of the plurality of driving paths and (ii) a value of at least one influencing factor for each of the plurality of driving paths, the at least one influencing factor affecting the driving energy;

[0338] (II) obtaining an energy change level of a first driving path included in the plurality of driving paths as a first energy change level;

[0339] (III) obtaining an energy change level of a second driving path included in the plurality of driving paths as a second energy change level;

[0340] (IV) Based on the common stop time of the first electric vehicle and the second electric vehicle included in the first driving plan for the first electric vehicle and the second driving plan for the second electric vehicle, available charging time is allocated to the first electric vehicle and the second electric vehicle according to a comparison between a first energy change level of the first driving path and a second energy change level of the second driving path to accordingly generate a first charging plan for the first electric vehicle and a second charging plan for the second electric vehicle.

[0341] The charging device and the charging method thereof disclosed in the present disclosure may be implemented by a special-purpose computer including a memory and a processor, the processor being programmed to execute one or more functions embodied by one or more computer programs.

[0342] The charging device and the charging method thereof disclosed in the present disclosure may also be implemented by a dedicated computer, which includes a processor composed of one or more dedicated hardware logic circuits.

[0343] The charging device and the charging method thereof disclosed in the present disclosure may also be implemented by a processor system including a memory, a processor programmed to execute one or more functions embodied by one or more computer programs, and one or more hardware logic circuits.

[0344] One or more computer programs may be stored in a non-transitory storage medium as instructions executed by a computer or a processor.

[0345] The present disclosure having been explained above is not limited to the above-described exemplary embodiments.

[0346] As long as each exemplary embodiment modified in design includes the above-mentioned features disclosed in the present disclosure, each exemplary embodiment appropriately modified in design by those skilled in the art is included in the scope of the present disclosure.

[0347] Each component included in the charging device according to each exemplary embodiment is not limited to the corresponding disclosure described in the corresponding exemplary embodiment, and is therefore appropriately modified. For example, the arrangement, characteristics, and shape of each component included in the charging device according to each exemplary embodiment are not limited to the arrangement, characteristics, and shape of the corresponding disclosure in the corresponding exemplary embodiment, and are therefore appropriately modified.

[0348] The combination of components included in the charging device according to each exemplary embodiment may be changed to a different combination as long as there is no technical contradiction in the changed combination.

Claims

1. A charging plan generating device, comprising: A change calculator configured to calculate an energy change level of one of the following (i) and (ii) based on information related to travel energy required for at least one electric vehicle to travel along each of a plurality of travel routes: (i) a value of driving energy required for the at least one electric vehicle to travel along each of the plurality of driving routes, (ii) a value of at least one influencing factor for each of the plurality of driving paths, the at least one influencing factor affecting the driving energy; as well as A charging plan generator, wherein the charging plan generator is configured to: obtaining an energy change level of a first driving path included in the plurality of driving paths as a first energy change level; obtaining an energy change level of a second driving path included in the plurality of driving paths as a second energy change level; Based on the common stop time of the first electric vehicle and the second electric vehicle included in the first driving plan for the first electric vehicle and the second driving plan for the second electric vehicle, available charging time is allocated to the first electric vehicle and the second electric vehicle according to a comparison between a first energy change level of the first driving path and a second energy change level of the second driving path to accordingly generate a first charging plan for the first electric vehicle and a second charging plan for the second electric vehicle.

2. The charging plan generating device according to claim 1, characterized in that: The charging plan generator is configured to determine the allocation of the available charging time to the first electric vehicle and the second electric vehicle such that When it is determined that the first energy change level of the first driving path is greater than the second energy change level of the second driving path, a first charging time included in the available charging time and allocated to the first electric vehicle is greater than a second charging time included in the available charging time and allocated to the second electric vehicle, And when it is determined that the second energy change level of the second driving path is greater than the first energy change level of the first driving path, the second charging time included in the available charging time and allocated to the second electric vehicle is greater than the first charging time included in the available charging time and allocated to the first electric vehicle.

3. The charging plan generating device according to claim 1, characterized in that: The variation calculator is configured to calculate an energy variation level of a value of driving energy required for the at least one electric vehicle to travel along each of the plurality of driving routes as an energy variation level for each of the plurality of driving routes, The charging plan generator is constructed as follows: obtaining an energy change level of the first driving path as a first energy change level; obtaining an energy change level of the second driving path as a second energy change level; as well as Determine the allocation of the available charging time to the first electric vehicle and the second electric vehicle so that When it is determined that the first energy change level is greater than the second energy change level, a first charging time included in the available charging time and allocated to the first electric vehicle is greater than a second charging time included in the available charging time and allocated to the second electric vehicle, And when it is determined that the second energy change level is greater than the first energy change level, the second charging time included in the available charging time and allocated to the second electric vehicle is greater than the first charging time included in the available charging time and allocated to the first electric vehicle.

4. The charging plan generating device according to any one of claims 1 to 3, characterized in that: The value of the driving energy required for the at least one electric vehicle to travel along each of the plurality of driving paths includes one of (i) a measured value of the driving energy actually used when the at least one electric vehicle travels along a corresponding one of the plurality of driving paths and (ii) a predicted value of the driving energy required for the at least one electric vehicle to travel along a corresponding one of the plurality of driving paths, and the at least one influencing factor for each of the plurality of driving paths includes: a first energy influencing factor indicating a distance traveled by the at least one electric vehicle along a corresponding one of the plurality of travel paths; a second energy influencing factor indicating a time required for the at least one electric vehicle to travel along a corresponding one of the plurality of travel paths; a third energy influencing factor indicating a traffic condition of a corresponding one of the plurality of driving paths during driving of the at least one electric vehicle along the corresponding one of the plurality of driving paths; a fourth energy influencing factor indicating a number of stops of the at least one electric vehicle along a corresponding one of the plurality of driving paths; a fifth energy influencing factor indicating an average speed of the at least one electric vehicle during driving of the at least one electric vehicle along a corresponding one of the plurality of driving paths; a sixth energy influencing factor indicating a number of changes in a driver of at least one electric vehicle during driving of the at least one electric vehicle along a corresponding one of the plurality of driving routes; a seventh energy influencing factor indicating a change in a driving operation of the at least one electric vehicle during travel of the at least one electric vehicle along a corresponding one of the plurality of travel paths; and An eighth energy influencing factor indicates weather conditions during driving of at least one electric vehicle along a corresponding one of the plurality of driving routes.

5. The charging plan generating device according to claim 1, characterized in that: The change calculator is configured to calculate an energy change of one of the following (i) and (ii) as the energy change level: (i) a value of driving energy required for the at least one electric vehicle to travel along each of the plurality of driving routes; (ii) a value of the at least one influencing factor for each of the plurality of driving paths, The charging plan generator is constructed as follows: obtaining the energy change of the first driving path as a first energy change; obtaining an energy change of the second driving path as a second energy change; as well as Determine the allocation of the available charging time to the first electric vehicle and the second electric vehicle so that When it is determined that the first energy change of the first driving path is greater than the second energy change of the second driving path, a first charging time included in the available charging time and allocated to the first electric vehicle is greater than a second charging time included in the available charging time and allocated to the second electric vehicle, And when it is determined that the second energy change of the second driving path is greater than the first energy change of the first driving path, the second charging time included in the available charging time and allocated to the second electric vehicle is greater than the first charging time included in the available charging time and allocated to the first electric vehicle.

6. The charging plan generating device according to claim 1, characterized in that: The at least one electric vehicle comprises a plurality of electric vehicles, The change calculator is configured to calculate the energy change level of one of the following (i) and (ii): (i) a value of driving energy required for each of the plurality of electric vehicles to travel along each of the plurality of driving routes; as well as (ii) a value of at least one influencing factor for each of the plurality of driving paths.

7. The charging plan generating device according to claim 6, characterized in that: The change calculator is configured to calculate an energy change of one of the following (i) and (ii) as the energy change level: (i) a value of driving energy required for each of the plurality of electric vehicles to travel along each of the plurality of driving routes; as well as (ii) a value of at least one influencing factor for each of the plurality of driving paths.

8. The charging plan generating device according to claim 1, characterized in that: The variation calculator is configured to The predicted energy parameter of each of the plurality of driving paths is calculated based on one of the following (i) and (ii): (i) a value of driving energy required for the at least one electric vehicle to travel along a corresponding one of the plurality of driving paths; (ii) a value of the at least one influencing factor for a corresponding one of the plurality of driving paths, The actual measured energy parameter of each of the plurality of driving paths is calculated based on one of the following (I) and (II): (I) an actual measured value of the driving energy required for the at least one electric vehicle to travel along a corresponding one of the plurality of driving paths; as well as (II) an actual measured value of the at least one influencing factor for a corresponding one of the plurality of driving paths, calculating, for each of the plurality of driving paths, a deviation between the predicted energy parameter and the actually measured energy parameter, And a deviation between the predicted energy parameter and the actually measured energy parameter is calculated for a corresponding one of the plurality of driving paths as an energy change level of each of the plurality of driving paths.

9. The charging plan generating device according to claim 8, characterized in that: The at least one electric vehicle comprises a plurality of electric vehicles, The variation calculator is configured to The predicted energy parameter of each of the plurality of driving paths is calculated based on one of the following (i) and (ii): (i) a value of driving energy required for each of the plurality of electric vehicles to travel along a corresponding one of the plurality of driving routes; as well as (ii) a value of the at least one influencing factor for a corresponding one of the plurality of driving paths, and calculating the actual measured energy parameter of each of the plurality of driving paths based on one of the following (I) and (II): (I) an actual measured value of the driving energy required for each of the plurality of electric vehicles to travel along a corresponding one of the plurality of driving routes; as well as (II) an actual measured value of the at least one influencing factor for a corresponding one of the plurality of driving paths.

10. A charging device, comprising: The charging plan generating device according to any one of claims 1 to 9; as well as A charging execution unit, wherein the charging execution unit is configured to: performing charging of a battery of the first electric vehicle according to the first charging plan for the first electric vehicle; as well as Charging of the battery of the second electric vehicle is performed according to the second charging plan for the second electric vehicle.

11. A charging program product for at least one processor, the charging program product comprising: a non-transitory computer-readable storage medium; as well as A set of computer program instructions stored in the computer readable storage medium causes the at least one processor to Based on information related to travel energy required for at least one electric vehicle to travel along each of the plurality of travel routes, an energy change level of one of the following (i) and (ii) is calculated: (i) a value of driving energy required for the at least one electric vehicle to travel along each of the plurality of driving routes; as well as (ii) a value of at least one influencing factor for each of the plurality of driving paths, the at least one influencing factor affecting the driving energy, obtaining an energy change level of a first driving path included in the plurality of driving paths as a first energy change level, obtaining an energy change level of a second driving path included in the plurality of driving paths as a second energy change level, And based on the common stop time of the first electric vehicle and the second electric vehicle included in the first driving plan for the first electric vehicle and the second driving plan for the second electric vehicle, the available charging time is allocated to the first electric vehicle and the second electric vehicle according to the comparison between the first energy change level of the first driving path and the second energy change level of the second driving path to accordingly generate a first charging plan for the first electric vehicle and a second charging plan for the second electric vehicle.

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