Calculation system, charging plan creation program, and discharging plan creation program

Abstract

In the present invention, a pathfinding unit sets a plurality of nodes within a state of charge (SOC) segment between a target SOC for when a secondary cell installed on an electric mobile object is being charged and a current SOC, and sets a plurality of nodes within an available charge duration from a charging start time to a charging end time. A cost allocation unit consults a storage degradation property, a charging cycle degradation property, and / or a list of electricity fees by time slot, and allocates the cost of either an amount of degradation or an electricity fee to paths between the nodes. The pathfinding unit searches for a charging path where the sum of the costs of the paths between the nodes reaches a minimum. A charging plan creation unit creates a charging plan on the basis of the retrieved charging path.

Description

[Technical Field]

[0001] The present disclosure relates to a computing system, a charging plan creation program, and a discharging plan creation program that create a charging plan or a discharging plan for a secondary battery. [Background technology]

[0002] In recent years, electric vehicles (EVs) and plug-in hybrid vehicles (PHVs) have become increasingly popular. These electric vehicles are equipped with secondary batteries as key devices. To prevent secondary battery degradation and extend their lifespan, proper charge and discharge management of secondary batteries is required.

[0003] Cost management is even more important for commercial vehicles such as delivery vehicles. It is desirable to create a charging plan that minimizes deterioration of the secondary battery during the nighttime hours when electricity rates are cheaper. In doing so, it is necessary to create an optimal charging plan that takes into account the daily changes in the pre-charging State Of Charge (SOC) and the available time for charging.

[0004] Regarding the creation of a charging plan, a control method has been proposed that changes the charging pattern in real time depending on the state of internal parameters. This control is based on the premise of rapid charging, and an upper limit current value that is less likely to deteriorate is set (see, for example, Patent Document 1). In addition, a control method has been proposed that determines the SOC during storage when no charging or discharging is performed, taking into account storage deterioration and cycle deterioration (see, for example, Patent Document 2). [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Publication No. 2020-092598 [Patent Document 2] Patent No. 6651063 Summary of the Invention

[0006] Conventional control has not been able to simultaneously optimize current control, time control, and SOC control during idle periods.

[0007] The present disclosure has been made in light of these circumstances, and its purpose is to provide a technique for creating a charging plan or discharging plan that minimizes costs such as deterioration of secondary batteries.

[0008] To solve the above problem, a computing system according to one aspect of the present disclosure includes: a route search unit that sets multiple nodes within an SOC interval between a target SOC and a current SOC when charging a secondary battery mounted on an electric vehicle, sets the multiple nodes within a chargeable time between a charging start time and a charging end time, and searches for a charging route that passes through the multiple nodes from the current SOC at the charging start time to the target SOC at the charging end time; a charging plan creation unit that creates a charging plan based on the searched charging route; and a cost allocation unit that allocates a degradation amount or an electricity cost to a path between each node by referring to at least one of a storage degradation characteristic that specifies a storage degradation rate defined by at least one element including at least one of the SOC and temperature of the secondary battery, a charge cycle degradation characteristic that specifies a cycle degradation rate during charging defined by at least one element including at least one of the SOC of the secondary battery and a charging current rate, and a time-of-day electricity tariff. The route search unit searches for a charging route that minimizes the total cost of the paths between the nodes.

[0009] Any combination of the above components, and conversion of the expression of the present disclosure into an apparatus, method, system, computer program, etc., are also valid aspects of the present disclosure.

[0010] According to the present disclosure, it is possible to create a charging plan or discharging plan that minimizes costs such as deterioration of a secondary battery. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a diagram for explaining an outline of a computing system according to an embodiment; [Figure 2] FIG. 2 is a diagram illustrating a detailed configuration of a power supply system mounted on an electric vehicle according to an embodiment. [Figure 3] FIG. 1 is a diagram illustrating a first example of a configuration of a computing system according to an embodiment. [Figure 4A] FIG. 4A is a diagram showing a schematic example of a storage deterioration rate characteristic map. [Figure 4B] FIG. 4B is a diagram showing a schematic example of a charge cycle deterioration rate characteristic map. [Figure 4C] FIG. 4C is a diagram showing a schematic example of a discharge cycle deterioration rate characteristic map. [Figure 5] FIG. 10 is a diagram illustrating an example of a charging route search. [Figure 6] FIG. 10 is a diagram illustrating an example of assigning degradation costs to paths. [Figure 7] FIG. 10 is a diagram for specifically explaining current limit and time limit of a path. [Figure 8A] FIG. 8A is a diagram for explaining an example of a charging route search using the Dijkstra algorithm (part 1). [Figure 8B] FIG. 8B is a diagram for explaining an example of a charging route search using the Dijkstra algorithm (part 1). [Figure 9A] FIG. 9A is a diagram for explaining an example of a charging route search using the Dijkstra algorithm (part 2). [Figure 9B] FIG. 9B is a diagram for explaining an example of a charging route search using the Dijkstra algorithm (part 2). [Figure 10A] FIG. 10A is a diagram showing a specific example of variations in SOC and SOH between two cells connected in series. [Figure 10B] FIG. 10B is a diagram showing a specific example of variations in SOC and SOH between two cells connected in series. [Figure 10C] FIG. 10C is a diagram showing a specific example of variations in SOC and SOH between two cells connected in series. [Figure 11] FIG. 10 is a diagram showing an example of a charging path search when the SOC and SOH of two cells are different. [Figure 12] 4 is a flowchart showing the flow of a charging plan creation process performed by the computing system according to the embodiment. [Figure 13] FIG. 10 is a diagram illustrating a second example of a configuration of a computing system according to an embodiment. [Figure 14] FIG. 10 is a diagram showing an example of a discharge path search. [Figure 15] 4 is a flowchart showing the flow of a process for deriving a target SOC by the calculation system according to the embodiment. [Figure 16] FIG. 10 is a diagram illustrating a third example of a configuration of a computing system according to an embodiment. [Figure 17] 10 is a flowchart showing the flow of a discharge plan creation process performed by the calculation system according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0012] FIG. 1 is a diagram for explaining an overview of a computing system 1 according to an embodiment. The computing system 1 is a system used by businesses that operate delivery businesses, bus businesses, taxi businesses, rental car businesses, car sharing businesses, etc. The computing system 1 is a system for managing the business operations of the businesses. The computing system 1 is composed of one or more information processing devices (e.g., servers, PCs). Some or all of the information processing devices that make up the computing system 1 may be located in a data center. For example, the computing system 1 may be composed of a combination of a server in a data center and a client PC in the business.

[0013] A business operator (assumed to be a delivery business operator in this specification) owns multiple electric vehicles 3 and multiple chargers 4, and utilizes the multiple electric vehicles 3 for delivery business. In this embodiment, the electric vehicles 3 are assumed to be pure EVs that are not equipped with engines.

[0014] The plurality of electric vehicles 3 have wireless communication capabilities and can be connected to a network 2 to which a calculation system 1 is connected. The electric vehicles 3 can transmit battery data of the secondary batteries mounted on them to the calculation system 1 via the network 2. The electric vehicles 3 may transmit the battery data while parked in a parking lot or garage at a business office, or while driving.

[0015] Network 2 is a general term for communication paths such as the Internet and dedicated lines, and the communication medium and protocol are not important. Examples of communication media that can be used include a mobile phone network (cellular network), wireless LAN, wired LAN, optical fiber network, ADSL network, and CATV network. Examples of communication protocols that can be used include TCP (Transmission Control Protocol) / IP (Internet Protocol), UDP (User Datagram Protocol) / IP, and Ethernet (registered trademark).

[0016] The electric vehicle 3 may be connected to a server or PC of a business operator via P2P (Peer-to-Peer) and transmit battery data of the secondary battery mounted on the vehicle directly to the server or PC of the business operator. Alternatively, the battery data may be transferred to the server or PC of the business operator via a recording medium on which the battery data is recorded. Alternatively, the electric vehicle 3 may transmit the battery data to the server or PC of the business operator via a charging adapter 6 (see FIG. 2) described later.

[0017] 2 is a diagram illustrating a detailed configuration of a power supply system 40 mounted on an electric vehicle 3 according to an embodiment. The power supply system 40 is connected to the motor 34 via a first relay RY1 and an inverter 35. During power running, the inverter 35 converts DC power supplied from the power supply system 40 into AC power and supplies it to the motor 34. During regeneration, the inverter 35 converts AC power supplied from the motor 34 into DC power and supplies it to the power supply system 40. The motor 34 is a three-phase AC motor, and during power running, it rotates in response to the AC power supplied from the inverter 35. During regeneration, rotational energy generated by deceleration is converted into AC power and supplied to the inverter 35.

[0018] The vehicle control unit 30 is a vehicle ECU (Electronic Control Unit) that controls the entire electric vehicle 3, and may be configured, for example, as an integrated VCM (Vehicle Control Module). The wireless communication unit 36 ​​performs signal processing for wirelessly connecting to the network 2 via an antenna 36a. Examples of wireless communication networks that can be used by the electric vehicle 3 include a mobile phone network (cellular network), wireless LAN, ETC (Electronic Toll Collection System), DSRC (Dedicated Short Range Communications), V2I (Vehicle-to-Infrastructure), and V2V (Vehicle-to-Vehicle).

[0019] The first relay RY1 is a contactor inserted between the wiring connecting the power supply system 40 and the inverter 35. When the vehicle is running, the vehicle control unit 30 controls the first relay RY1 to an on state (closed state) to electrically connect the power supply system 40 and the power system of the electric vehicle 3. When the vehicle is not running, the vehicle control unit 30 controls the first relay RY1 to an off state (open state) as a general rule to electrically disconnect the power supply system 40 and the power system of the electric vehicle 3. Note that instead of a relay, other types of switches such as a semiconductor switch may be used.

[0020] By connecting the electric vehicle 3 to the charger 4, the battery module 41 in the power supply system 40 can be charged externally. In this embodiment, the electric vehicle 3 is connected to the charger 4 via a charging adapter 6. The charging adapter 6 is attached to the tip of the terminal of the charger 4, for example. When the charging adapter 6 is attached to the charger 4, the control unit in the charging adapter 6 establishes a communication channel with the control unit in the charger 4.

[0021] When the charging adapter 6 attached to the charger 4 is connected to the electric vehicle 3 with a charging cable, the battery module 41 in the electric vehicle 3 can be charged from the charger 4. The charging adapter 6 passes through the power supplied from the charger 4 to the electric vehicle 3. The charging adapter 6 has a wireless communication function and can send and receive data with the computing system 1. The charging adapter 6 functions as a gateway that relays communications between the electric vehicle 3 and the charger 4, between the electric vehicle 3 and the computing system 1, and between the charger 4 and the computing system 1.

[0022] The charger 4 is connected to a commercial power grid 5 and charges a power supply system 40 in the electric vehicle 3. In the electric vehicle 3, a second relay RY2 is inserted between the wiring connecting the power supply system 40 and the charger 4. Note that instead of a relay, other types of switches, such as a semiconductor switch, may be used. Before charging starts, the battery management unit 42 controls the second relay RY2 to the ON state via the vehicle control unit 30 or directly, and controls the second relay RY2 to the OFF state after charging is completed.

[0023] Generally, normal charging is performed with AC, and rapid charging is performed with DC. When charging with AC (for example, single-phase 100 / 200V), AC power is converted to DC power by an AC / DC converter (not shown) inserted between second relay RY2 and power supply system 40. When charging with DC, charger 4 generates DC power by full-wave rectifying AC power supplied from commercial power system 5 and smoothing it with a filter.

[0024] Examples of fast charging standards that can be used include CHAdeMO (registered trademark), ChaoJi, GB / T, and Combo (Combined Charging System). CHAdeMO 2.0 specifies a maximum output (specification) of 1000V x 400A = 400kW. CHAdeMO 3.0 specifies a maximum output (specification) of 1500V x 600A = 900kW. ChaoJi specifies a maximum output (specification) of 1500V x 600A = 900kW. GB / T specifies a maximum output (specification) of 750V x 250A = 185kW. Combo specifies a maximum output (specification) of 900V x 400A = 350kW. CHAdeMO, ChaoJi, and GB / T use CAN (Controller Area Network) as their communication method. Combo uses PLC (Power Line Communication) as its communication method.

[0025] A charging cable that employs the CAN system includes a communication line in addition to a power line. When the electric vehicle 3 and the charging adapter 6 are connected via the charging cable, the vehicle control unit 30 establishes a communication channel with the control unit in the charging adapter 6. Note that with a charging cable that employs the PLC system, communication signals are transmitted superimposed on the power line.

[0026] The vehicle control unit 30 establishes a communication channel with the battery management unit 42 via an in-vehicle network (for example, CAN or LIN (Local Interconnect Network)). If the communication standard between the vehicle control unit 30 and the control unit in the charging adapter 6 is different from the communication standard between the vehicle control unit 30 and the battery management unit 42, the vehicle control unit 30 functions as a gateway.

[0027] As will be described in detail later, in this embodiment, the calculation system 1 has a function of creating an optimal charging plan (charging schedule). When the control unit in the charging adapter 6 receives the charging plan from the calculation system 1, it transfers the received charging plan to the control unit in the charger 4. In this case, even if the control unit in the charging adapter 6 receives a command value for the charging current from the vehicle control unit 30, it does not transfer the command value to the control unit in the charger 4. Note that when the control unit in the charging adapter 6 receives upper limit values ​​(limit values) of the power, current, and voltage from the vehicle control unit 30, it transfers the upper limit values ​​to the control unit in the charger 4.

[0028] The charging adapter 6 is preferably configured in a small housing. In this case, the driver of the electric vehicle 3 can easily carry the charging adapter 6 and can attach and use the charging adapter 6 to chargers 4 other than those installed at business establishments. For example, the charging adapter 6 can be attached and used to chargers 4 installed at public facilities, commercial facilities, gas stations, car dealerships, and highway service areas, other than those installed at business establishments. In this case, the battery module 41 in the electric vehicle 3 can be charged from the charger 4 outside the business establishment based on the charging plan created by the computing system 1.

[0029] The power supply system 40 mounted on the electric vehicle 3 includes a battery module 41 and a battery management unit 42. The battery module 41 includes a plurality of cells E1-En connected in series. The battery module 41 may include a plurality of cells connected in series and parallel. The battery module 41 may also be configured by combining a plurality of battery modules. The cells may be lithium-ion battery cells, nickel-metal hydride battery cells, lead battery cells, or the like. In the following description, an example will be assumed in which lithium-ion battery cells (nominal voltage: 3.6-3.7V) are used. The number of cells E1-En connected in series is determined according to the drive voltage of the motor 34.

[0030] A shunt resistor Rs is connected in series with the cells E1-En. The shunt resistor Rs functions as a current detection element. A Hall element may be used instead of the shunt resistor Rs. A plurality of temperature sensors T1, T2 are installed in the battery module 41 to detect the temperatures of the cells E1-En. One temperature sensor may be installed in the battery module, or one may be installed for each of the cells. The temperature sensors T1, T2 may be, for example, a thermistor.

[0031] The battery management unit 42 includes a voltage measurement unit 43, a temperature measurement unit 44, a current measurement unit 45, and a battery control unit 46. Multiple voltage lines connect each node of the multiple series-connected cells E1-En to the voltage measurement unit 43. The voltage measurement unit 43 measures the voltage of each cell E1-En by measuring the voltage between each two adjacent voltage lines. The voltage measurement unit 43 transmits the measured voltage of each cell E1-En to the battery control unit 46.

[0032] Because the voltage measurement unit 43 has a higher voltage than the battery control unit 46, the voltage measurement unit 43 and the battery control unit 46 are insulated and connected by a communication line. The voltage measurement unit 43 can be configured using an ASIC (Application Specific Integrated Circuit) or a general-purpose analog front-end IC. The voltage measurement unit 43 includes a multiplexer and an A / D converter. The multiplexer outputs the voltage between two adjacent voltage lines to the A / D converter in order from top to bottom. The A / D converter converts the analog voltage input from the multiplexer into a digital value.

[0033] The temperature measurement unit 44 includes a voltage dividing resistor and an A / D converter. The A / D converter sequentially converts multiple analog voltages, each divided by the multiple temperature sensors T1 and T2 and the multiple voltage dividing resistors, into digital values ​​and outputs them to the battery control unit 46. The battery control unit 46 estimates the temperatures of the multiple cells E1-En based on the digital values. For example, the battery control unit 46 estimates the temperature of each cell E1-En based on the value measured by the temperature sensor closest to each cell E1-En.

[0034] The current measurement unit 45 includes a differential amplifier and an A / D converter. The differential amplifier amplifies the voltage across the shunt resistor Rs and outputs it to the A / D converter. The A / D converter converts the analog voltage input from the differential amplifier into a digital value and outputs it to the battery control unit 46. The battery control unit 46 estimates the current flowing through the multiple cells E1-En based on the digital value.

[0035] In addition, if an A / D converter is installed in the battery control unit 46 and an analog input port is installed in the battery control unit 46, the temperature measurement unit 44 and the current measurement unit 45 may output analog voltages to the battery control unit 46, which may be converted into digital values ​​by the A / D converter in the battery control unit 46.

[0036] The battery control unit 46 manages the states of the cells E1-En based on the voltages, temperatures, and currents of the cells E1-En measured by the voltage measurement unit 43, temperature measurement unit 44, and current measurement unit 45. The battery control unit 46 can be configured with a microcomputer and non-volatile memory (e.g., an EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory). The battery control unit 46 estimates the SOC and SOH (State Of Health) of each of the cells E1-En.

[0037] The battery control unit 46 estimates the SOC by combining the OCV (Open Circuit Voltage) method and the current integration method. The OCV method estimates the SOC based on the OCV of each cell E1-En measured by the voltage measurement unit 43 and the SOC-OCV curve of the cells E1-En. The SOC-OCV curve of the cells E1-En is created in advance based on characteristic tests conducted by the battery manufacturer and is registered in the internal memory of the microcomputer at the time of shipment.

[0038] The current integration method is a method for estimating the SOC based on the OCV of each cell E1-En at the start of charging / discharging and the integrated value of the current measured by the current measurement unit 45. In the current integration method, measurement errors by the current measurement unit 45 accumulate as the charging / discharging time increases. Therefore, it is preferable to correct the SOC estimated by the current integration method using the SOC estimated by the OCV method.

[0039] SOH is defined as the ratio of the current full charge capacity (FCC) to the initial FCC, with a lower value (closer to 0%) indicating more advanced deterioration. SOH can be calculated by measuring the capacity after full charge and discharge, or by adding together storage deterioration and cycle deterioration.

[0040] SOH can also be estimated based on its correlation with the cell's internal resistance. Internal resistance can be estimated by dividing the voltage drop that occurs when a specified current flows through the cell for a specified time by the current value. Internal resistance decreases as temperature increases, and increases as SOH decreases.

[0041] The battery control unit 46 transmits the voltage, temperature, current, SOC, and SOH of the multiple cells E1-En to the vehicle control unit 30 via the in-vehicle network. The vehicle control unit 30 transmits battery data including the current SOC, SOH, and temperature of the multiple cells E1-En to the computing system 1.

[0042] FIG. 3 is a diagram showing a configuration example 1 of a computing system 1 according to an embodiment. The computing system 1 includes a processing unit 11, a storage unit 12, an operation unit 13, a display unit 14, and a communication unit 15. The processing unit 11 includes an input information acquisition unit 111, a battery data acquisition unit 112, a route search unit 113, a cost allocation unit 114, a charging plan creation unit 115, and a charging plan output unit 116. The functions of the processing unit 11 can be realized by a combination of hardware resources and software resources, or by hardware resources alone. Examples of hardware resources that can be used include a CPU, ROM, RAM, GPU (Graphics Processing Unit), ASIC, FPGA (Field Programmable Gate Array), and other LSIs. Examples of software resources that can be used include an operating system, an application, and other programs.

[0043] The storage unit 12 includes a storage deterioration rate characteristic map 121, a charge cycle deterioration rate characteristic map 122, a discharge cycle deterioration rate characteristic map 123, and a time-of-day electricity rate table 124. The storage unit 12 includes a non-volatile recording medium such as an SSD (Solid State Drive) or an HDD (Hard Disk Drive), and stores various programs and data.

[0044] The storage deterioration rate characteristic map 121, the charge cycle deterioration rate characteristic map 122, and the discharge cycle deterioration rate characteristic map 123 are maps of the storage deterioration rate characteristic, the charge cycle deterioration rate characteristic, and the discharge cycle deterioration rate characteristic of the secondary battery mounted on the electric vehicle 3. The storage deterioration rate characteristic, the charge cycle deterioration rate characteristic, and the discharge cycle deterioration rate characteristic of the secondary battery are derived in advance for each secondary battery product through experiments and simulations by the battery manufacturer. Note that data derived by other evaluation organizations may also be used.

[0045] Storage degradation is degradation that progresses over time depending on the temperature and SOC of the secondary battery at each point in time. It progresses over time regardless of whether the battery is being charged or discharged. Storage degradation is mainly caused by the formation of a film (SEI (Solid Electrolyte Interphase) film) on the negative electrode. Storage degradation depends on the SOC and temperature at each point in time. Generally, the higher the SOC at each point in time and the higher the temperature at each point in time, the faster the storage degradation rate.

[0046] Cycle degradation is degradation that progresses as the number of charge / discharge cycles increases. It is mainly caused by cracking or peeling due to expansion or contraction of the active material. Cycle degradation depends on the current rate, the SOC range used, and the temperature. In general, the higher the current rate, the wider the SOC range used, and the higher the temperature, the faster the cycle degradation rate.

[0047] 4A-4C are diagrams showing schematic examples of a storage degradation rate characteristic map, a charge cycle degradation rate characteristic map, and a discharge cycle degradation rate characteristic map. FIG. 4A shows a schematic example of a storage degradation rate characteristic map. The X axis represents SOC [%], the Y axis represents temperature [°C], and the Z axis represents storage degradation rate [% / √h]. It is known that storage degradation progresses according to the 0.5 power law (square root) of time h (hours). As shown in FIG. 4A, the higher the SOC, the faster the storage degradation rate.

[0048] Figure 4B shows a rough example of a charge cycle degradation rate characteristic map. The X axis shows the SOC usage range [%], the Y axis shows the current rate [C], and the Z axis shows the charge cycle degradation rate [% / √Ah]. Cycle degradation is assumed to progress according to the 0.5 power law (square root) of ampere-hours (Ah). As shown in Figure 4B, when charging in a low SOC range, the charge cycle degradation rate increases. Also, when charging in a high SOC range, the charge cycle degradation rate increases, although not as fast as in a low SOC range.

[0049] Figure 4C shows a schematic example of a discharge cycle degradation rate characteristic map. The X axis represents the SOC usage range [%], the Y axis represents the current rate [C], and the Z axis represents the discharge cycle degradation rate [% / √Ah]. The lower the SOC range, the faster the discharge cycle degradation rate.

[0050] The cycle degradation characteristics are also affected by temperature, although this influence is less significant than that of the current rate. Therefore, to improve the accuracy of estimating the cycle degradation rate, it is preferable to prepare cycle degradation characteristics that define the relationship between the SOC usage range and the cycle degradation rate for each two-dimensional combination of multiple current rates and multiple temperatures. On the other hand, when generating a simple cycle degradation rate characteristic map, it is sufficient to treat the temperature as room temperature and simply prepare cycle degradation rate characteristics for each of multiple current rates.

[0051] The storage deterioration rate characteristic, the charge cycle deterioration rate characteristic, and the discharge cycle deterioration rate characteristic may be defined by a function instead of a map.

[0052] Returning to Figure 3, the time-of-day electricity rate table 124 is a table that describes the electricity rates for each time period contracted with the electric power company. Nighttime electricity rates are often set lower than daytime electricity rates. Also, daytime electricity rates often adopt a pay-as-you-go system in which the electricity rate per kWh increases in stages as the cumulative amount of electricity used increases.

[0053] Japanese electric power companies offer a variety of rate plans, including (a) a plan that sets rates according to usage regardless of time of day or day of the week, (b) a plan with low rates from 1:00 AM to 9:00 AM, (c) a plan with low rates from 9:00 PM to 5:00 AM, (d) a plan with low rates from 9:00 PM to 9:00 AM, (e) a plan with low rates from 11:00 PM to 7:00 AM, (f) a plan with low rates from 10:00 PM to 8:00 AM, (g) a plan with low rates on weekends, (h) a summer plan that divides time periods into three, with higher rates during peak hours (1:00 PM to 4:00 PM) and lower rates during the night (11:00 PM to 7:00 AM), and (i) a plan with detailed rates based on "season" and "time of day," with low rates from 11:00 PM to 7:00 AM.

[0054] In the case of a large-scale business such as the delivery business in this embodiment, it is possible to set up a more detailed, customized rate plan through an individual contract between the business and the electric power company.

[0055] The operation unit 13 is a user interface such as a keyboard, mouse, or touch panel, and accepts operations by a user of the computing system 1. The display unit 14 includes a display such as a liquid crystal display or an organic EL display, and displays images generated by the processing unit 11. The communication unit 15 executes communication processing for communicating with the charging adapter 6, the electric vehicle 3, or the charger 4 via the network 2 or directly.

[0056] The input information acquisition unit 111 acquires the target SOC, charging start time, and charging end time when charging the battery module 41 mounted on the electric vehicle 3, which are input from the operation unit 13. The time from the charging start time to the charging end time is the time available for charging.

[0057] The battery data acquisition unit 112 acquires battery data of the battery module 41 from the vehicle control unit 30 of the electric vehicle 3 via the communication unit 15. The battery data includes at least the current SOC of the plurality of cells E1-En included in the battery module 41. The battery data may further include the current SOH and temperature of the plurality of cells E1-En.

[0058] The route search unit 113 sets multiple nodes at a predetermined interval within the SOC interval between the acquired target SOC and the current SOC. For example, the nodes are set at intervals of 0.5%. Note that the nodes may also be set at other intervals, such as 1%, 5%, or 10%.

[0059] The route search unit 113 sets multiple nodes at a predetermined interval within the chargeable time between the acquired charging start time and charging end time. For example, the nodes are set at 30-minute intervals. Note that the nodes may also be set at other intervals, such as 3-minute intervals, 5-minute intervals, 10-minute intervals, or 15-minute intervals.

[0060] The route search unit 113 sets paths between the set matrix nodes. The cost allocation unit 114 refers to a storage deterioration rate characteristic map 121 and a charge cycle deterioration rate characteristic map 122, and assigns a deterioration cost to the path between each node. The route search unit 113 searches for a charging route that minimizes the total deterioration cost of the path between the nodes. The charging plan creation unit 115 creates a charging plan based on the found charging route. The charging plan output unit 116 transmits the created charging plan to the charger 4 via the charging adapter 6. A specific example will be described below.

[0061] FIG. 5 is a diagram showing an example of a charging path search. FIG. 5 shows an example where the starting SOC is 40% and the target SOC is 80%. The current SOC acquired by the battery data acquisition unit 112 is set as the starting SOC. The amount of power corresponding to the SOC width between the target SOC and the starting SOC corresponds to the required charging amount. The path search unit 113 searches for the optimal path from the starting SOC to the target SOC within the limited time available for charging.

[0062] Fig. 6 is a diagram for explaining an example of allocation of deterioration costs to paths. As shown in Fig. 5, in the charging path according to this embodiment, charging can be paused in units of ΔT [s]. During the period when charging is paused, only storage deterioration progresses.

[0063] 6, the cost allocation unit 114 refers to the storage deterioration speed characteristic map 121 and calculates the deterioration amount as the deterioration cost for each of the following cases: when the SOC stays at 40% for a unit time (ΔT), when the SOC stays at 50% for a unit time (ΔT), when the SOC stays at 60% for a unit time (ΔT), when the SOC stays at 70% for a unit time (ΔT), and when the SOC stays at 80% for a unit time (ΔT). During the rest period, the SOC basically does not change, so the movement occurs horizontally between nodes.

[0064] When the cell temperature is 40°C or less, the temperature has little effect on the storage degradation rate, so the cost allocation unit 114 can assume the temperature to be room temperature. In this case, the cost allocation unit 114 calculates the storage degradation rate between each horizontal node based on the room temperature and SOC. The cost allocation unit 114 multiplies the storage degradation rate between each horizontal node by a unit time (ΔT) to calculate the degradation amount between each horizontal node.

[0065] The cost allocation unit 114 may assume that the current temperature of the cell acquired by the battery data acquisition unit 112 will continue until the charging end time. In this case, the cost allocation unit 114 calculates the storage deterioration rate between each horizontal node based on the acquired temperature and SOC. The cost allocation unit 114 multiplies each storage deterioration rate between each horizontal node by a unit time (ΔT) to calculate the deterioration amount between each horizontal node.

[0066] The cost allocation unit 114 may also obtain weather forecast information for the area where the charger 4 is installed from a weather forecast server (not shown) and estimate the temperature between each horizontal node from the charging start time to the charging end time. In this case, the cost allocation unit 114 calculates the storage deterioration rate between each horizontal node based on the estimated temperature and SOC between each horizontal node. The cost allocation unit 114 multiplies the storage deterioration rate between each horizontal node by a unit time (ΔT) to calculate the deterioration amount between each horizontal node.

[0067] On the other hand, during charging, both charge cycle degradation and storage degradation progress. As shown in Fig. 6, the cost assignment unit 114 calculates the current rate (0.1 C in the example shown in Fig. 6) for changing from SOC 40% to SOC 50% per unit time (ΔT), the current rate (0.2 C in the example shown in Fig. 6) for changing from SOC 40% to SOC 60% per unit time (ΔT), the current rate (0.3 C in the example shown in Fig. 6) for changing from SOC 40% to SOC 70% per unit time (ΔT), and the current rate (0.4 C in the example shown in Fig. 6) for changing from SOC 40% to SOC 80% per unit time (ΔT). During charging, the SOC increases, resulting in movement between nodes in the upper right direction.

[0068] Although not shown in Figure 6, the cost allocation unit 114 also calculates the current rate required to reach SOC 60% from SOC 50% in unit time (ΔT), the current rate required to reach SOC 70% from SOC 50% in unit time (ΔT), the current rate required to reach SOC 80% from SOC 50% in unit time (ΔT), the current rate required to reach SOC 70% from SOC 60% in unit time (ΔT), the current rate required to reach SOC 80% from SOC 60% in unit time (ΔT), and the current rate required to reach SOC 80% from SOC 70% in unit time (ΔT).

[0069] The cost allocation unit 114 determines the charge cycle degradation rate for each path between nodes in the upper right direction by referring to a charge cycle degradation rate characteristics map 122 based on the SOC range and current rate. The cost allocation unit 114 determines the storage degradation rate by referring to a storage degradation rate characteristics map 121 based on the SOC and temperature. The SOC used to determine the storage degradation rate may be, for example, the average value between the upper and lower limits of the SOC range.

[0070] The cost allocation unit 114 calculates the charge cycle degradation amount of the path between the nodes in the upper right direction by multiplying the identified charge cycle degradation rate by the amount of current (Ah) corresponding to the unit SOC (ΔSOC) for each path between the nodes in the upper right direction. The cost allocation unit 114 calculates the storage degradation amount of the path between the nodes in the upper right direction by multiplying the identified storage degradation rate by the unit time (ΔT) for each path between the nodes in the upper right direction. The cost allocation unit 114 calculates the final degradation amount by adding up the calculated charge cycle degradation amount and storage degradation amount for each path between the nodes in the upper right direction.

[0071] In reality, however, the charging path cannot necessarily pass through all paths between nodes, and is subject to limitations due to current or time.

[0072] Figure 7 is a diagram specifically explaining the current and time limitations of the paths. First, because time does not reverse, there are no paths that transition to the left. Also, in the case of charging, the SOC does not generally decrease, so there are paths that transition to the upper right or right, and there are no paths that transition to the lower right.

[0073] The specifications of the charger 4 stipulate upper limits for the charging power and charging current for each charger 4. Therefore, charging cannot exceed the upper limit of the charging current of the charger 4. Similarly, the specifications of the electric vehicle 3 stipulate upper limits for the charging power and charging current for each electric vehicle 3. Therefore, charging cannot exceed the upper limit of the charging current of the electric vehicle 3.

[0074] The calculation system 1 stores the upper limit values ​​of the charging power and the charging current for each charger 4 and for each electric vehicle 3 in an upper limit value table (not shown) in the storage unit 12. The upper limit values ​​of the charging power and the charging current for each charger 4 and for each electric vehicle 3 may be input by a user from the operation unit 13, or may be acquired from the charger 4 or the electric vehicle 3 when the calculation system 1 and the charger 4 or the electric vehicle 3 communicate for the first time.

[0075] The cost allocation unit 114 sets as invalid paths those paths between the nodes calculated in FIG. 6 where the current rate required to pass through the path exceeds the upper limit of the charging current of the charger 4 or the electric vehicle 3.

[0076] In the example shown in FIG. 7, paths P1 and P2 are set as invalid paths due to current limitations. In this way, the angle of the transition to the upper right is limited by the limit based on the upper current limit. Path P3 is an invalid path due to the limits based on the remaining time and the upper current limit. If path P3 is passed, it will no longer be possible to reach the target SOC within the remaining time and within the range of the permitted angle of the transition to the upper right. Therefore, path P3 is set as an invalid path.

[0077] The route search unit 113 searches for a charging route that minimizes the total degradation amount of paths between nodes. Specifically, the route search unit 113 calculates the total storage degradation amount and the total charging cycle degradation amount of each charging route based on the following (Equation 1) and (Equation 2). The route search unit 113 adds up both amounts to calculate the total degradation amount of each charging route. The route search unit 113 selects the charging route that minimizes the total degradation amount.

[0078] Total storage deterioration amount =√(Σ(ΔT*Ks^2)) ···(Formula 1) Storage degradation rate Ks [% / √h] = Storage degradation map (SOC [%], temperature [℃]) Total charge cycle degradation = √(Σ(ΔAh*Kc^2)) (Equation 2) Charge cycle degradation rate Kc [% / √Ah] = Charge cycle degradation map (SOC [%], current rate [C]) The route search unit 113 can use an existing route search algorithm to search for a charging route that minimizes the total degradation of paths between nodes. For example, the Dijkstra algorithm can be used as the route search algorithm. Route search algorithms are generally used in car navigation systems.

[0079] 8A-8B are diagrams for explaining an example of a charging route search using the Dijkstra algorithm (part 1). FIGS. 9A-9B are diagrams for explaining an example of a charging route search using the Dijkstra algorithm (part 2). First, as an initial process, the route search unit 113 sets the distances to all nodes to undetermined (∞). Next, the distance to node a is set to 0. The following is an iterative process.

[0080] The route search unit 113 selects the node with the shortest distance from among the nodes whose distances are not yet determined, and determines the distance. In the example shown in FIG. 8A, the distance to node a is determined to be 0 (see the star). Next, the route search unit 113 calculates the distances to nodes b, c, and d connected to node a. In the example shown in FIG. 8A, the distances to nodes b, c, and d are 2, 4, and 6. If the distances to nodes b, c, and d are shorter than the previous distances, the route search unit 113 updates the previous distances to the newly calculated distances. In the example shown in FIG. 8A, the distances to nodes b, c, and d are updated from ∞, ∞, and ∞ to 2, 4, and 6.

[0081] Next, the route search unit 113 selects the node with the shortest distance from among the nodes whose distances are not yet determined, and determines the distance. In the example shown in FIG. 8B, the distance to node b is determined to be 2 (see the star). Next, the route search unit 113 calculates the total distance via node ab for nodes e, f, and g connected to node b. In the example shown in FIG. 8B, the distances to nodes e, f, and g via node ab are 5, 6, and 8. If the distances to nodes e, f, and g are shorter than the previous distances, the route search unit 113 updates the previous distances to the newly calculated distances. In the example shown in FIG. 8B, the distances to nodes e, f, and g are updated from ∞, ∞, and ∞ to 5, 6, and 8.

[0082] Next, the route search unit 113 selects the node with the shortest distance from among the nodes whose distances are not yet determined, and determines the distance. In the example shown in FIG. 9A, the distance to node c is determined to be 4 (see the star). Next, the route search unit 113 calculates the total distance via node a for nodes e, f, and g connected to node c. In the example shown in FIG. 9A, the distances to nodes e, f, and g via node a are 4, 5, and 7. If the distances to nodes e, f, and g are shorter than the previous distances, the route search unit 113 updates the previous distances to the newly calculated distances. In the example shown in FIG. 9A, the distances to nodes e, f, and g are updated from 5, 6, and 8 to 4, 5, and 7.

[0083] Next, the route search unit 113 selects the node with the shortest distance from among the nodes whose distances are undetermined, and determines the distance. In the example shown in FIG. 9B, the distance to node e is determined to be 4 (see the star). Next, the route search unit 113 calculates the total distance via node ace for nodes h, i, and j connected to node e. In the example shown in FIG. 9B, the distances to nodes h, i, and j via node ace are 9, 10, and 11. If the distances to nodes h, i, and j are shorter than the previous distances, the route search unit 113 updates the previous distances to the newly calculated distances. In the example shown in FIG. 9A, the distances to nodes h, i, and j are updated from ∞, ∞, and ∞ to 9, 10, and 11. This process is repeated until the distances to all nodes are determined.

[0084] When the route search unit 113 searches for a charging route that minimizes the amount of deterioration, the charging plan creation unit 115 converts the found charging route into a charging plan that is specified by a charging start time and a current value for each unit time interval. The charging plan output unit 116 transmits the charging plan created by the charging plan creation unit 115 to the charging adapter 6, the electric vehicle 3, or the charger 4 via the communication unit 15.

[0085] For example, the data format of the charging plan includes the charging start time [s] and the target charging amount [Ah], and also specifies multiple data slots for storing current values ​​for each unit time interval (for example, every 3 minutes).

[0086] The computing system 1 may create a plan for adjusting the temperature in the power supply system 40 when the battery module 41 in the electric vehicle 3 is charged from the charger 4. In this case, the computing system 1 transmits the temperature adjustment plan to the battery management unit 42 in the electric vehicle 3 directly or via the charging adapter 6. For example, the data format of the temperature adjustment plan defines multiple data slots for storing target temperature values ​​for each unit time (for example, every three minutes). Upon receiving the temperature adjustment plan, the battery management unit 42 adjusts the temperature in the battery module 41 in accordance with the temperature adjustment plan. For example, the battery management unit 42 adjusts the temperature in the battery module 41 by controlling the output of a fan, cooler, or heater (not shown).

[0087] 5 to 9, we have described an example of searching for a charging path that minimizes the amount of deterioration during charging when the SOC and SOH of multiple series-connected cells E1 to En are ideally matched. In reality, the SOC or SOH of multiple series-connected cells E1 to En often do not match.

[0088] 10A-10C are diagrams showing specific examples of variations in SOC and SOH between two series-connected cells E1 and E2. The example shown in FIG. 10A shows an example in which variations in SOH occur between two series-connected cells E1 and E2. Specifically, the SOC of cells E1 and E2 is the same at 100%. The SOH of cell E1 is 100% and that of cell E2 is 90%, meaning that cell E2 is more degraded.

[0089] The example shown in Figure 10B shows a variation in SOC between two series-connected cells E1 and E2. Specifically, the SOH of cells E1 and E2 is the same at 100%. The SOC of cell E1 is 100% and that of cell E2 is 80%, meaning that cell E2 has a lower capacity.

[0090] The example shown in Figure 10C shows variations in both SOC and SOH between two series-connected cells E1 and E2. Specifically, the SOC of cell E1 is 80% and that of cell E2 is 100%, meaning that cell E1 has a lower capacity. The SOH of cell E1 is 100% and that of cell E2 is 90%, meaning that cell E2 is more degraded.

[0091] If there is a difference between the two series-connected cells E1 and E2, the charging path that minimizes the degradation of cell E1 may differ from the charging path that minimizes the degradation of cell E2. Therefore, it is necessary to set an index for determining the charging path for all the series-connected cells.

[0092] The first index is an index aimed at minimizing the overall deterioration of multiple cells connected in series. The path search unit 113 searches for a charging path that minimizes the deterioration of the cell with the lowest SOH among the multiple cells connected in series. Charging based on this charging path minimizes the burden on the cell with the lowest SOH. Among multiple cells connected in series, the cell with the lowest SOH becomes a bottleneck, and the lifespan of the cell with the lowest SOH determines the lifespan of the entire multiple cells. When the first index is used, the lifespan of the entire battery module 41 can be extended.

[0093] The second index is an index aimed at minimizing the SOH variation among multiple series-connected cells. The path search unit 113 searches for a charging path that minimizes the difference in degradation among multiple series-connected cells. Specifically, the path search unit 113 sets a cost for each path (horizontal and upper-right movement in the case of charging) based on the difference in degradation (the sum of the differences for the number of cell combinations) and searches for a charging path that minimizes the difference in degradation. Charging based on this charging path can reduce the SOH variation among multiple series-connected cells. SOH variation among multiple series-connected cells reduces the overall usable capacity of the multiple cells and shortens their lifespan. In contrast, a charging path determined using the second index can reduce SOH variation, contributing to an increase in usable capacity and an extension of their lifespan. In particular, SOH variation among cells is likely to occur in power supply systems 40 that do not include a cell balancing circuit (equalization circuit).

[0094] The third index is an index intended to prevent a reduction in the next day's driving distance. The route search unit 113 searches for a charging route that minimizes the amount of deterioration of the cell with the lowest actual capacity among the multiple cells connected in series. The actual capacity of a cell (i.e., the capacity that can actually be discharged) is defined as SOC x SOH. In charging based on this charging route, the cell with the lowest actual capacity is reliably charged to the target SOC. The available capacity of the entire multiple cells connected in series depends on the capacity of the cell with the lowest actual capacity. In contrast, in a charging route determined using the third index, the cell with the lowest actual capacity is reliably charged to the target SOC, thereby preventing a decrease in the available capacity of the entire multiple cells connected in series.

[0095] FIG. 11 is a diagram showing an example of a charging path search when the SOC and SOH of two cells E1 and E2 are different. In the example shown in FIG. 11, the SOC of cell E1 before charging starts is 60% and the SOH is 100%. The SOC of cell E2 before charging starts is 50% and the SOH is 90%. In the example shown in FIG. 11, the unit SOC (ΔSOC) of cell E1 is set in 10% increments. The unit SOC (ΔSOC) of cell E2 is set in 9% increments. The unit SOC (ΔSOC) of cell E2 is calculated by multiplying the unit SOC of cell E1 (ΔSOC = 10%) by the SOH of cell E2 / the SOH of cell E1 (= 90% / 100%).

[0096] For example, when a first index is set in the route search unit 113, the route search unit 113 searches for a charging route that minimizes the amount of deterioration of the cell E2. Also, when a third index is set in the route search unit 113, the route search unit 113 searches for a charging route that minimizes the amount of deterioration of the cell E2.

[0097] In the examples shown in Figures 5 to 11, the route search unit 113 searches for a charging route that minimizes the deterioration cost during charging. In this regard, the route search unit 113 may also search for a charging route that minimizes the electricity fee for charging. The cost allocation unit 114 refers to the time-of-day electricity rate table 124 and allocates a fee cost to the path between each node. The fee cost is the electricity fee required to pass through each path. If a pay-as-you-go time period is included in the charging time, the electricity fee per kWh during the pay-as-you-go time period changes depending on the accumulated charging amount.

[0098] In addition, in countries or regions where electricity is traded on the market, such as PJM (Pennsylvania, New Jersey, Maryland) in the United States, the cost allocation unit 114 obtains the most recent market price for the time period in which charging is performed and allocates the market price to the path between each node.

[0099] The route search unit 113 searches for a charging route that minimizes the total fee cost of the path between nodes. The charging plan creation unit 115 creates a charging plan based on the found charging route. The charging plan output unit 116 transmits the created charging plan to the charger 4 via the charging adapter 6 or directly.

[0100] 12 is a flowchart showing the flow of charging plan creation processing by the computing system 1 according to the embodiment. The user selects one of four indices for determining a charging route: (a) minimizing the deterioration level of the cell with the lowest SOH among multiple cells connected in series, (b) minimizing the difference in deterioration levels between multiple cells connected in series, (c) minimizing the deterioration level of the cell with the lowest actual capacity among multiple cells connected in series, or (d) minimizing the electricity fee.

[0101] When the input information acquiring unit 111 acquires an index selected by the user input from the operation unit 13, it sets the selected index in the route searching unit 113 (S10). The user can switch between the four indexes as appropriate. Alternatively, the processing unit 11 may be provided with an index switching unit (not shown), which switches the index according to a predetermined rule. For example, the index switching unit selects index (c) when the SOH of the entire battery module 41 is higher than a first set value, and switches from index (c) to index (a) when the SOH falls below the first set value. Alternatively, for example, the index switching unit selects index (c) when the SOH variation of the multiple cells E1-En in the battery module 41 is smaller than a second set value, and switches from index (c) to index (b) when the variation exceeds the second set value.

[0102] The input information acquisition unit 111 acquires the target SOC, charging start time, and charging end time when charging the battery module 41 mounted on the electric vehicle 3, which are input from the operation unit 13 (S11). The battery data acquisition unit 112 acquires battery data (including the current SOC) of the multiple cells E1-En included in the battery module 41 from the vehicle control unit 30 of the electric vehicle 3 via the communication unit 15 (S12).

[0103] The route search unit 113 sets a plurality of nodes at a predetermined interval within the SOC interval between the acquired target SOC and current SOC (S13).The route search unit 113 sets a plurality of nodes at a predetermined interval within the chargeable time between the acquired charging start time and charging end time (S14).

[0104] The route search unit 113 sets paths between each of the set matrix nodes. The cost allocation unit 114 sets paths between nodes that do not satisfy the current limit or time limit as invalid (S15). The cost allocation unit 114 refers to at least one of the storage deterioration rate characteristic map 121, the charge cycle deterioration rate characteristic map 122, and the time-of-day electricity rate table 124, and assigns costs to the paths between each of the nodes (S16).

[0105] The route search unit 113 applies a route search algorithm to search for a charging route that minimizes the cost according to the set determination index (S17). The charging plan creation unit 115 creates a charging plan based on the found charging route (S18). The charging plan output unit 116 transmits the created charging plan to the charger 4 via the charging adapter 6 or directly (S19).

[0106] Fig. 13 is a diagram showing a second configuration example of the computing system 1 according to the embodiment. In the first configuration example shown in Fig. 3, it is assumed that the target SOC is input by the user. In the second configuration example, a function of automatically calculating the target SOC is added.

[0107] In configuration example 2, the processing unit 11 further includes a delivery plan creation unit 117, a power consumption prediction unit 118, and an SOC usage range identification unit 119, in addition to an input information acquisition unit 111, a battery data acquisition unit 112, a route search unit 113, a cost allocation unit 114, a charging plan creation unit 115, and a charging plan output unit 116.

[0108] The delivery plan creation unit 117 creates a delivery plan for the next day for each electric vehicle 3 owned by the delivery company based on order information from an order management system (not shown). The delivery plan also includes a delivery route. The power consumption prediction unit 118 calculates the driving distance of the electric vehicle 3 required for delivery the next day based on the delivery route included in the delivery plan. The power consumption prediction unit 118 calculates the amount of power consumption required to drive the calculated distance as a predicted value for power consumption for the next day.

[0109] Based on the predicted power consumption for the next day, the SOC usage range determination unit 119 derives multiple candidates for the SOC usage range of the battery module 41 for the next day. For example, if the predicted power consumption for the next day corresponds to a DOD (Depth of Discharge) of 50% for the battery module 41, the SOC usage range determination unit 119 derives multiple candidates for the SOC usage range, such as 100-50%, 90-40%, 80-30%, 70-20%, 60-10%, and 50-0%. In this example, the candidates are derived in 10% increments, but the candidates may be derived in other increments.

[0110] The route search unit 113 sets multiple nodes at predetermined intervals within the SOC usage range for each of multiple SOC usage range candidates. The route search unit 113 sets multiple nodes at predetermined intervals within the delivery time between the delivery start time and delivery end time based on the delivery plan for the next day. The route search unit 113 sets paths between each of the set matrix-like nodes. The cost allocation unit 114 refers to the storage degradation rate characteristic map 121 and the discharge cycle degradation rate characteristic map 123 and allocates degradation costs to the paths between each of the nodes.

[0111] The route search unit 113 searches for a discharge route that minimizes the total degradation cost of the path between nodes for each of multiple SOC usage range candidates.The route search unit 113 identifies the SOC usage range of the discharge route that minimizes the total degradation cost among the multiple SOC usage range candidates.The route search unit 113 sets the upper limit SOC of the identified SOC usage range as the target SOC for charging.

[0112] Fig. 14 is a diagram showing an example of a discharge route search. Fig. 14 shows an example of creating a discharge plan based on a delivery plan in which power consumption of 40% DOD is predicted. The route search unit 113 searches for an optimal route from the optimal upper limit SOC to the optimal lower limit SOC within the delivery time of the next day. In the example shown in Fig. 14, a discharge route with an upper limit SOC of 80% and a lower limit SOC of 40% is selected as the optimal route.

[0113] The method of assigning deterioration costs to paths between nodes is the same as that for searching for a charging route described above, except that the relationship is reversed.

[0114] 15 is a flowchart showing the flow of the process of deriving a target SOC by the calculation system 1 according to the embodiment. The delivery plan creation unit 117 creates a delivery plan for the next day for the electric vehicle 3 based on order information from an order management system (not shown) (S20). The power consumption prediction unit 118 calculates the travel distance for the electric vehicle 3 required for delivery the next day based on the delivery route included in the delivery plan, and predicts the amount of power consumption required to travel that distance (S21).

[0115] The SOC usage range determination unit 119 derives multiple candidates for the SOC usage range of the battery module 41 for the next day based on the predicted power consumption for the next day (S22). The route search unit 113 sets multiple nodes at a predetermined interval within an SOC section between an upper limit SOC and a lower limit SOC of the SOC usage range for each of the multiple SOC usage range candidates (S23). The route search unit 113 sets multiple nodes at a predetermined interval within the delivery time between the delivery start time and the delivery end time (S24).

[0116] The route search unit 113 sets paths between the set matrix nodes. The cost assignment unit 114 sets paths between nodes that do not satisfy the current limit and time limit as invalid (S25). The cost assignment unit 114 refers to the storage deterioration rate characteristic map 121 and the discharge cycle deterioration rate characteristic map 123 and assigns a deterioration cost to the path between each node (S26).

[0117] The route search unit 113 applies a route search algorithm to search for a discharge route that minimizes the deterioration cost according to the determination index (S27). In configuration example 2, the determination index is selected from the following three indexes: (a) minimizing the deterioration amount of the cell with the lowest SOH among the multiple cells connected in series, (b) minimizing the difference in deterioration amount between the multiple cells connected in series, and (c) minimizing the deterioration amount of the cell with the lowest actual capacity among the multiple cells connected in series.

[0118] The route search unit 113 identifies the SOC usage range of the discharge route with the smallest degradation cost among the multiple candidate SOC usage ranges for the discharge route with the smallest degradation cost (S28).The route search unit 113 sets the upper limit SOC of the identified SOC usage range as the target SOC for charging (S29).

[0119] In the flowchart shown in FIG. 15, the route search unit 113 identifies the SOC usage range of the discharge route with the smallest degradation cost among the discharge routes with the smallest degradation cost among multiple SOC usage range candidates. In this regard, the SOC usage range may be identified by the following process. For each of multiple (i) SOC usage range candidates, the route search unit 113 calculates the total degradation amount [i] of the discharge route with the smallest degradation cost. For each of multiple (i) SOC usage range candidates, the route search unit 113 calculates the total degradation amount [i] of the charge route with the smallest degradation cost from the current SOC to the upper limit SOC of each SOC usage range. For each of multiple (i) SOC usage range candidates, the route search unit 113 adds the total degradation amount [i] of the discharge route with the smallest degradation cost and the total degradation amount [i] of the charge route with the smallest degradation cost. The route search unit 113 identifies the SOC usage range with the smallest added total degradation amount [i]. In this case, there is no need to search for a new charging route, and a charging plan is created based on the charging route that minimizes the deterioration cost calculated above.

[0120] Alternatively, the SOC usage range may be identified by the following process. The route search unit 113 calculates the total deterioration amount [i] of the discharge route by applying a predicted discharge pattern to each of multiple (i) SOC usage range candidates. For example, the route search unit 113 calculates the total deterioration amount [i] of the discharge route when applying a discharge pattern corresponding to a predicted driving pattern based on the delivery plan to each of the SOC usage range candidates of 100-50%, 90-40%, 80-30%, 70-20%, 60-10%, and 50-0%. For each of multiple (i) SOC usage range candidates, the route search unit 113 calculates the total deterioration amount [i] of the charge route that minimizes the deterioration cost from the current SOC to the upper limit SOC of each SOC usage range candidate. For each of multiple (i) SOC usage range candidates, the route search unit 113 adds the total deterioration amount [i] of the discharge route and the total deterioration amount [i] of the charge route. The route search unit 113 identifies the SOC usage range in which the summed total deterioration amount [i] is the smallest. In this case, there is no need to search for a new charging route, and a charging plan is created based on the charging route in which the deterioration cost calculated above is the smallest.

[0121] 16 is a diagram illustrating a third configuration example of the calculation system 1 according to the embodiment. The third configuration example also has a function of creating a discharge plan. In the third configuration example, the processing unit 11 further includes a discharge plan creation unit 1110 and a discharge plan output unit 1111 in addition to an input information acquisition unit 111, a battery data acquisition unit 112, a route search unit 113, a cost allocation unit 114, a charging plan creation unit 115, a charging plan output unit 116, a delivery plan creation unit 117, a power consumption prediction unit 118, and an SOC use range identification unit 119.

[0122] 17 is a flowchart showing the flow of the discharge plan creation process by the calculation system 1 according to the embodiment. The processes of steps S20 to S28 in the flowchart shown in FIG. 17 are the same as steps S20 to S28 in the flowchart shown in FIG.

[0123] The route search unit 113 identifies the SOC range of the discharge route with the smallest degradation cost among the discharge routes with the smallest degradation cost among multiple candidate SOC usage ranges (S28). The discharge plan creation unit 1110 creates a discharge plan based on the discharge route with the smallest degradation cost in the identified SOC usage range (S210). Specifically, the discharge plan creation unit 1110 converts the identified discharge route into a discharge plan defined by the driving start time (discharge start time) and the current value for each unit time section.

[0124] For example, the data format of the discharge plan includes the travel start time [s] and the predicted power consumption [Ah], and defines multiple data slots for storing the current value for each unit time interval. Note that the discharge plan creation unit 1110 may convert the current value for each unit time interval into the speed of the electric vehicle 3, and store the recommended speed of the electric vehicle 3 for each unit time interval in multiple data slots.

[0125] The discharge plan output unit 1111 transmits the created discharge plan to the electric vehicle 3 via the charging adapter 6 or directly (S211).

[0126] When the vehicle control unit 30 of the electric vehicle 3 receives the discharge plan, it displays the recommended speed for each time period on an in-vehicle display (for example, a car navigation system display or a meter display). If the electric vehicle 3 is an autonomous vehicle, it will travel at a speed as close as possible to the recommended speed for each time period within the range of safety standards.

[0127] The processing shown in the flowchart in Fig. 17 is processing assuming that the battery can be charged up to an optimal upper limit SOC before delivery begins. In this regard, when creating a discharge plan using the current SOC as the discharge start SOC, the processing is as follows: The SOC usage range specifying unit 119 converts the power consumption predicted by the power consumption prediction unit 118 into a DOD of the battery module 41. The SOC usage range specifying unit 119 sets the current SOC as the upper limit SOC of the SOC usage range, and sets the value obtained by subtracting the DOD from the upper limit SOC as the lower limit SOC of the SOC usage range.

[0128] The route search unit 113 sets multiple nodes within the SOC use range determined by the SOC use range specification unit 119, and sets multiple nodes within the available driving time (available discharge time) between the driving start time (discharge start time) and the driving end time (discharge end time). The cost assignment unit 114 refers to the storage deterioration rate characteristic map 121 and the discharge cycle deterioration rate characteristic map 123, and assigns a deterioration cost to the path between each node. The route search unit 113 searches for a discharge route that passes through multiple nodes and reaches from the upper limit SOC of the SOC use range at the driving start time to the lower limit SOC of the SOC use range at the driving end time, and that minimizes the total deterioration cost of the paths between the nodes.

[0129] As described above, according to this embodiment, it is possible to create a charging plan or a discharging plan that minimizes costs such as secondary battery degradation. When charging an electric vehicle 3 used in a delivery business or the like, it is desirable to create a charging plan that minimizes the amount of secondary battery degradation at night when electricity rates are low. The SOC at the start of charging and the available charge time available for charging change daily. It is necessary to create an optimal charging plan in response to such changes in the SOC at the start of charging and the available charge time.

[0130] In this embodiment, charging from the current SOC to the target SOC is considered as a path problem. That is, by referring to the storage deterioration rate characteristic map 121 and the charge cycle deterioration rate characteristic map 122, a deterioration amount is set as the passage cost of each path, and a path with the minimum deterioration amount is searched for, thereby making it possible to create an optimal charging plan.

[0131] This method can search for a charging pattern that minimizes the amount of degradation within a specified time (chargeable time), and can simultaneously perform optimization control of the three elements of current control, time control, and stored SOC. Previously, it was not possible to simultaneously calculate and determine the three elements of current control, time control, and stored SOC using a single system.

[0132] In addition, in this embodiment, battery data (SOC, SOH) of multiple cells E1-En can be input and controlled to minimize the amount of deterioration of the entire battery module 41. Control can also be performed to suppress the increase in the SOH difference between multiple cells E1-En. These control modes can be easily switched by switching the route path cost index depending on the purpose.

[0133] The present disclosure has been described above based on the embodiments. The embodiments are merely examples, and it will be understood by those skilled in the art that various modifications are possible in the combination of the respective components and processing steps, and that such modifications are also within the scope of the present disclosure.

[0134] In the above-described embodiment, four determination indices are used as an example. However, a determination indices may be provided that aim to both suppress cell degradation and reduce electricity costs. For example, the route search unit 113 calculates the degradation cost and the electricity cost for each selectable charging route, and calculates the total cost by weighted addition or weighted averaging of both, and identifies the charging route that minimizes the total cost.

[0135] In the above-described embodiment, an example has been described in which the charging plan is transmitted from the computing system 1 to the charger 4 via the charging adapter 6. In this regard, the charging adapter 6 is not essential and can be omitted. In this case, the charging plan is transmitted to the charger 4 directly from the computing system 1 or via the electric vehicle 3.

[0136] Furthermore, the index for minimizing the electricity charge is not essential and can be omitted. In that case, the time-of-day electricity charge table 124 can be omitted.

[0137] In the above-described embodiment, an example has been described in which a charging plan or a discharging plan is created for a battery module 41 mounted on an electric vehicle 3. In this regard, the electric vehicle 3 may be a two-wheeled electric motorcycle (electric scooter) or an electric bicycle. The electric vehicle 3 also includes low-speed electric vehicles 3 such as golf carts and land cars used in shopping malls, entertainment facilities, etc. Furthermore, the objects on which the battery module 41 is mounted are not limited to electric vehicles 3. For example, electric ships, railroad cars, multicopters (drones), and other electric moving objects are also included.

[0138] The embodiment may be specified by the following items.

[0139] [Item 1] a route search unit (113) that sets a plurality of nodes within an SOC interval between a target SOC (State Of Charge) and a current SOC when charging a secondary battery (41) mounted on an electric vehicle (3), sets the plurality of nodes within a chargeable time between a charging start time and a charging end time, and searches for a charging route that passes through the plurality of nodes and reaches the target SOC at the charging end time from the current SOC at the charging start time; a charging plan creation unit (115) that creates a charging plan based on the searched charging route; a cost allocation unit (114) that allocates a deterioration amount or an electricity charge cost to a path between each node by referring to at least one of a storage deterioration characteristic (121) defined by at least one element including at least one of the SOC and temperature of the secondary battery (41), a charge cycle deterioration characteristic (122) that defines a cycle deterioration rate during charging defined by at least one element including at least one of the SOC of the secondary battery (41) and a current rate of a charging current, and an electricity rate table (124) by time period; The route search unit (113) searches for a charging route that minimizes the total cost of paths between nodes. A computing system (1) characterized by:

[0140] This allows for the creation of a charging plan that minimizes charging costs.

[0141] [Item 2] the charging plan creation unit (115) creates a charging plan including a charging start time and a current value for each time interval; The computing system (1) according to item 1, characterized in that

[0142] This makes it possible to optimally control the current supplied from the charger (4) to the secondary battery (41) mounted on the electric vehicle (3).

[0143] [Item 3] the cost allocation unit (114) sets, as an invalid path, a path between the nodes whose current rate required to pass through the path exceeds an upper limit of the charging current; 3. The computing system (1) according to item 1 or 2.

[0144] This makes it possible to prevent an unrealizable charging plan from being created.

[0145] [Item 4] The secondary battery (41) includes a plurality of cells (E1-En) connected in series, the path search unit (113) searches for a charging path that minimizes the amount of deterioration of a cell having the lowest SOH (State Of Health) among the plurality of cells (E1-En); 4. The computing system (1) according to any one of items 1 to 3.

[0146] This makes it possible to create a charging plan that minimizes the amount of deterioration of the entire plurality of cells (E1-En).

[0147] [Item 5] The secondary battery (41) includes a plurality of cells (E1-En) connected in series, the path search unit (113) searches for a charging path that minimizes a difference in deterioration amount between the plurality of cells (E1-En); 4. The computing system (1) according to any one of items 1 to 3.

[0148] This makes it possible to create a charging plan that leads to a reduction in the variation in the amount of deterioration among the plurality of cells (E1-En).

[0149] [Item 6] The secondary battery (41) includes a plurality of cells (E1-En) connected in series, the path search unit (113) searches for a charging path that minimizes the amount of deterioration of the cell with the lowest actual capacity among the plurality of cells (E1-En); 4. The computing system (1) according to any one of items 1 to 3.

[0150] This makes it possible to create a charging plan that can avoid a reduction in the travelable distance of the electric vehicle (3).

[0151] [Item 7] The route search unit (113) searches for a charging route that minimizes the total electricity charges for the path between the nodes. 4. The computing system (1) according to any one of items 1 to 3.

[0152] This makes it possible to create a charging plan that minimizes electricity charges.

[0153] [Item 8] The route search unit (113) is capable of switching a determination index for the cost of the charging route to be minimized. 8. The computing system (1) according to any one of items 1 to 7,

[0154] This allows for flexible control according to the situation.

[0155] [Item 9] a SOC usage range determination unit (119) that derives a plurality of candidates for a usage range of the SOC of the secondary battery (41) based on the amount of power predicted to be required the next time the electric vehicle (3) is used; the route search unit (113) sets a plurality of nodes within the SOC use range for each of the derived plurality of SOC use range candidates, and sets the plurality of nodes within a use time between a next use start time and a next use end time of the electric vehicle (3); the cost allocation unit (114) allocates a degradation cost to a path between each node by referring to the storage degradation characteristic (121) and a discharge cycle degradation characteristic (123) that defines a cycle degradation rate during discharge defined by at least one element including at least one of an SOC of the secondary battery (41) and a current rate of a discharge current; the route search unit (113) searches for a discharge route that minimizes the total degradation cost of paths between nodes for each of the plurality of SOC use range candidates, identifies an SOC use range of the discharge route that minimizes the total degradation cost among the discharge routes that minimize the total degradation cost, and sets the upper limit value of the identified SOC use range as the target SOC. 9. The computing system (1) according to any one of items 1 to 8.

[0156] This allows the target SOC during charging to be automatically determined.

[0157] [Item 10] a SOC usage range determination unit (119) that derives a plurality of candidates for a usage range of the SOC of the secondary battery (41) based on the amount of power predicted to be required the next time the electric vehicle (3) is used; The path search unit (113) calculates the deterioration amount of the discharge path based on a predicted discharge pattern for each of the derived candidates for the SOC use range, calculates the deterioration amount of the charge path that minimizes the deterioration cost from the current SOC to the upper limit SOC of each candidate for the SOC use range, determines the SOC use range that minimizes the sum of the deterioration amount of the discharge path and the deterioration amount of the charge path, and sets the upper limit value of the determined SOC use range as the target SOC. 9. The computing system (1) according to any one of items 1 to 8.

[0158] This allows the target SOC during charging to be automatically determined.

[0159] [Item 11] a process of setting a plurality of nodes within an SOC interval between a target SOC and a current SOC when charging a secondary battery (41) mounted on an electric vehicle (3), and setting the plurality of nodes within a chargeable time between a charging start time and a charging end time; a process of allocating a deterioration amount or an electricity cost to a path between each node by referring to at least one of a storage deterioration characteristic (121) defined by at least one element including at least one of the SOC and temperature of the secondary battery (41), a charge cycle deterioration characteristic (122) defining a cycle deterioration rate during charging defined by at least one element including at least one of the SOC of the secondary battery (41) and a current rate of a charging current, and an electricity rate table (124) by time period; a process of searching for a charging route that minimizes the total cost of paths between nodes among charging routes that pass through a plurality of nodes from the current SOC at the charging start time to the target SOC at the charging end time; A process of creating a charging plan based on the discovered charging route; A charging plan creation program that causes a computer to execute the above.

[0160] This allows for the creation of a charging plan that minimizes charging costs.

[0161] [Item 12] a route search unit (113) that sets a plurality of nodes within a SOC usage range when discharging from a secondary battery (41) mounted on an electric vehicle (3), sets the plurality of nodes within a dischargeable time between a discharge start time and a discharge end time, and searches for a discharge route that passes through the plurality of nodes and reaches a lower limit SOC of the SOC usage range at the discharge end time from an upper limit SOC of the SOC usage range at the discharge start time; a discharge plan creation unit (1110) that creates a discharge plan based on the discovered discharge path; a cost allocation unit (114) that allocates a degradation cost to a path between each node by referring to a storage degradation characteristic (121) that is defined by at least one element including at least one of the SOC and temperature of the secondary battery (41) and a discharge cycle degradation characteristic (123) that defines a cycle degradation rate during discharge that is defined by at least one element including at least one of the SOC of the secondary battery (41) and a current rate of a discharge current, The route search unit (113) searches for a discharge route that minimizes the total degradation cost of paths between nodes. A computing system (1) characterized by:

[0162] This allows for the creation of a discharge plan that minimizes the discharge cost.

[0163] [Item 13] A process of setting a plurality of nodes within a SOC usage range when discharging from a secondary battery (41) mounted on an electric vehicle (3) and setting the plurality of nodes within a dischargeable time between a discharge start time and a discharge end time; a process of allocating a deterioration cost to a path between each node by referring to a storage deterioration characteristic (121) defined by at least one element including at least one of the SOC and temperature of the secondary battery (41) and a discharge cycle deterioration characteristic (123) that defines a cycle deterioration rate during discharge defined by at least one element including at least one of the SOC of the secondary battery (41) and a current rate of a discharge current; a process of searching for a discharge route that passes through a plurality of nodes from an upper limit SOC of the SOC usage range at the discharge start time to a lower limit SOC of the SOC usage range at the discharge end time, and that minimizes the total degradation cost of the paths between the nodes; A process of creating a discharge plan based on the discovered discharge route; A discharge plan creation program that causes a computer to execute the above.

[0164] This allows for the creation of a discharge plan that minimizes the discharge cost. [Explanation of symbols]

[0165] 1 Calculation system, 2 Network, 3 Electric vehicle, 4 Charger, 5 Commercial power system, 6 Charging adapter, 11 Processing unit, 111 Input information acquisition unit, 112 Battery data acquisition unit, 113 Route search unit, 114 Cost allocation unit, 115 Charging plan creation unit, 116 Charging plan output unit, 117 Delivery plan creation unit, 118 Power consumption prediction unit, 119 SOC usage range identification unit, 1110 Discharge plan creation unit, 1111 Discharge plan output unit, 12 Memory unit, 121 Storage deterioration rate characteristic map, 122 Charging cycle deterioration rate characteristic map, 123 Discharge cycle deterioration rate characteristic map, 124 Time-of-day electricity rate table, 13 Operation unit, 14 Display unit, 15 Communication unit, 30 Vehicle control unit, 34 Motor, 35 Inverter, 36 wireless communication unit, 36a antenna, 40 power supply system, 41 battery module, 42 battery management unit, 43 voltage measurement unit, 44 temperature measurement unit, 45 current measurement unit, 46 battery control unit, E1-En cell, RY1, RY2 relay, T1, T2 temperature sensor, Rs shunt resistor.

Claims

1. a route search unit that sets a plurality of nodes within an SOC interval between a target SOC (State Of Charge) and a current SOC when charging a secondary battery mounted on an electric vehicle, sets the plurality of nodes within a chargeable time between a charging start time and a charging end time, and searches for a charging route that passes through the plurality of nodes and reaches the target SOC at the charging end time from the current SOC at the charging start time; a charging plan creation unit that creates a charging plan based on the searched charging route; a cost allocation unit that allocates a deterioration amount or an electricity cost to a path between each node by referring to at least one of a storage deterioration characteristic defined by at least one element including at least one of an SOC and a temperature of the secondary battery, a charge cycle deterioration characteristic that defines a cycle deterioration rate during charging defined by at least one element including at least one of an SOC and a current rate of a charging current of the secondary battery, and an electricity rate table by time period; the route search unit searches for a charging route that minimizes the total cost of paths between nodes; A computing system comprising:

2. the charging plan creation unit creates a charging plan including a charging start time and a current value for each time interval.

2. The computing system according to claim 1.

3. the cost allocation unit sets, as an invalid path, a path between the nodes whose current rate required to pass through the path exceeds an upper limit of a charging current; 3. The computing system according to claim 1 or 2.

4. the secondary battery includes a plurality of cells connected in series; The path search unit searches for a charging path that minimizes the amount of deterioration of a cell having the lowest SOH (State of Health) among the plurality of cells.

4. The computing system according to claim 1, wherein the first and second inputs are input to the first and second inputs.

5. the secondary battery includes a plurality of cells connected in series; the route search unit searches for a charging route that minimizes a difference in deterioration amount among the plurality of cells; 4. The computing system according to claim 1, wherein the first and second inputs are input to the first and second inputs.

6. the secondary battery includes a plurality of cells connected in series; the path search unit searches for a charging path that minimizes the amount of deterioration of a cell having the lowest actual capacity among the plurality of cells; 4. The computing system according to claim 1, wherein the first and second inputs are input to the first and second inputs.

7. the route search unit searches for a charging route that minimizes the total electricity cost of the path between the nodes; 4. The computing system according to claim 1, wherein the first and second inputs are input to the first and second inputs.

8. The route search unit is capable of switching a determination index for the cost of the charging route to be minimized.

8. The computing system according to claim 1, wherein the first and second inputs are connected to the first and second inputs.

9. an SOC usage range determination unit that derives a plurality of candidates for an SOC usage range of the secondary battery based on an amount of power predicted to be required the next time the electric vehicle is used; the route search unit sets a plurality of nodes within the SOC use range for each of the derived plurality of SOC use range candidates, and sets the plurality of nodes within a use time between a next use start time and a next use end time of the electric vehicle; the cost allocation unit allocates a degradation cost to a path between each node by referring to the storage degradation characteristic and a discharge cycle degradation characteristic that defines a cycle degradation rate during discharge defined by at least one element including at least one of an SOC of the secondary battery and a current rate of a discharge current; the route search unit searches for a discharge route that minimizes a total degradation cost of paths between nodes for each of the plurality of SOC use range candidates, identifies an SOC use range of the discharge route that minimizes the total degradation cost among the discharge routes that minimize the total degradation cost, and sets an upper limit value of the identified SOC use range as the target SOC.

9. The computing system according to claim 1, wherein the first and second inputs are connected to the first and second inputs.

10. an SOC usage range determination unit that derives a plurality of candidates for an SOC usage range of the secondary battery based on an amount of power predicted to be required the next time the electric vehicle is used; the path search unit calculates the deterioration amount of the discharge path based on a predicted discharge pattern for each of the derived candidates for the SOC use range, calculates the deterioration amount of the charge path that minimizes the deterioration cost from the current SOC to the upper limit SOC of each candidate for the SOC use range, determines the SOC use range that minimizes the sum of the deterioration amount of the discharge path and the deterioration amount of the charge path, and sets the upper limit value of the determined SOC use range as the target SOC.

9. The computing system according to claim 1, wherein the first and second inputs are connected to the first and second inputs.

11. a process of setting a plurality of nodes within an SOC interval between a target SOC and a current SOC when charging a secondary battery mounted on an electric vehicle, and setting the plurality of nodes within a chargeable time between a charging start time and a charging end time; a process of allocating a deterioration amount or an electricity cost to a path between each node by referring to at least one of a storage deterioration characteristic defined by at least one element including at least one of an SOC and a temperature of the secondary battery, a charge cycle deterioration characteristic defining a cycle deterioration rate during charging defined by at least one element including at least one of an SOC and a current rate of a charging current of the secondary battery, and an electricity rate table by time period; a process of searching for a charging route that minimizes a total cost of paths between nodes among charging routes that pass through a plurality of nodes and that are from the current SOC at the charging start time to the target SOC at the charging end time; A process of creating a charging plan based on the discovered charging route; A charging plan creation program that causes a computer to execute the above.

12. a route search unit that sets a plurality of nodes within an SOC usage range when discharging from a secondary battery mounted on an electric vehicle, sets the plurality of nodes within a dischargeable time between a discharge start time and a discharge end time, and searches for a discharge route that passes through the plurality of nodes and reaches from an upper limit SOC of the SOC usage range at the discharge start time to a lower limit SOC of the SOC usage range at the discharge end time; a discharge plan creation unit that creates a discharge plan based on the discovered discharge route; a cost allocation unit that allocates a degradation cost to a path between each node by referring to a storage degradation characteristic that defines a storage degradation rate defined by at least one element including at least one of an SOC and a temperature of the secondary battery, and a discharge cycle degradation characteristic that defines a cycle degradation rate during discharge defined by at least one element including at least one of an SOC and a current rate of a charging current of the secondary battery, the route search unit searches for a discharge route that minimizes the total degradation cost of paths between nodes; A computing system comprising:

13. A process of setting a plurality of nodes within an SOC usable range when discharging from a secondary battery mounted on an electric vehicle, and setting the plurality of nodes within a dischargeable time between a discharge start time and a discharge end time; a process of allocating a deterioration cost to a path between each node by referring to a storage deterioration characteristic defined by at least one element including at least one of an SOC and a temperature of the secondary battery, and a discharge cycle deterioration characteristic defining a cycle deterioration rate during discharge defined by at least one element including at least one of an SOC and a current rate of a discharge current of the secondary battery; a process of searching for a discharge route that passes through a plurality of nodes and reaches from an upper limit SOC of the SOC usage range at the discharge start time to a lower limit SOC of the SOC usage range at the discharge end time, and that minimizes a total degradation cost of paths between the nodes; A process of creating a discharge plan based on the discovered discharge route; A discharge plan creation program that causes a computer to execute the above.

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