New energy commercial vehicle operation simulator based on cloud big data model

Abstract

The invention discloses a new energy commercial vehicle operation simulator based on a cloud big data model, and the simulator comprises an algorithm controller which comprises a data collection module and a data processing module, the data collection module is responsible for collecting vehicle information from a CAN bus, and the data processing module is used for receiving the information; the intelligent remote communication module interacts with the data processing module through a CAN line and interacts with a cloud big data model through a 5G network or the Internet; the cloud big data model is used for calculating cloud big data model data according to the data uploaded by the intelligent remote communication module and other vehicle operation data; and the map API is used for providing path planning, charging station electricity price and highway charging standard information.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of intelligent networking, and particularly relates to a new energy commercial vehicle operation simulator based on a cloud big data model. BACKGROUND

[0002] Commercial vehicles are mainly used as a kind of cargo transport tool, and are highly sensitive to transportation cost. Accurate operation cost simulation has great value for logistics companies to calculate shipping quotes, individual drivers to assess shipping values, and vehicle fleets to estimate operation costs. With the rapid development of new energy vehicle technology, the proportion of new energy commercial vehicles in the freight market is rapidly increasing. However, due to the large difference between the operation mode and cost composition of new energy vehicles and fuel vehicles, the operation cost simulation method of traditional fuel vehicles is no longer applicable, and relying on manual experience judgment and actual situation often has a large error.

[0003] The Chinese invention patent disclosed "a freight cost calculation method based on big data" (publication number CN201910490286, publication date 2019.12.03) proposes a fuel vehicle cost calculation method based on big data, but this scheme is a cost calculation method for fuel vehicles, which is not applicable to new energy vehicles. And the parameters used in the scheme are fixed values, and do not have the ability to self-optimize. When the environment changes, the user needs to recalibrate the parameters. SUMMARY

[0004] Therefore, the present application relates to a new energy commercial vehicle operation simulator based on a big data analysis method. The user only needs to fill in the vehicle parameters when registering, and input the starting point, destination, weight of goods and delivery time when using, to obtain the optimal operation route and energy supplement plan for this operation, and then calculate the comprehensive cost of this operation. The present application has the characteristics of accurate calculation and convenient operation, and has good application prospect.

[0005] In order to solve the above problems existing in the prior art, the technical scheme adopted by the present application is:

[0006] A new energy commercial vehicle operation simulator based on a cloud big data model, comprising:

[0007] An algorithm controller containing a data acquisition module and a data processing module, the data acquisition module is responsible for collecting vehicle information from the CAN bus, and the data processing module is used for receiving information;

[0008] An intelligent remote communication module interacts with the data processing module through the CAN line, and interacts with the cloud big data model through the 5G network or the Internet;

[0009] a cloud big data model for calculating the cloud big data model data according to the data uploaded by the intelligent remote communication module and other vehicle operation data;

[0010] a map API for providing path planning, charging station electricity price and highway toll standard information.

[0011] an operation planning simulator including a path planning simulator for calculating an optimal path planning meeting the conditions and a power supplement planning simulator for calculating an optimal power supplement planning by obtaining an operation path from the path planning simulator;

[0012] an operation cost simulator including an energy cost calculator, a road toll cost calculator, a maintenance cost calculator, a depreciation cost calculator and an insurance cost calculator;

[0013] the energy cost calculator is configured to calculate a total energy consumption cost during the current operation;

[0014] the road toll cost calculator is configured to calculate a total road toll cost during the current operation;

[0015] the maintenance cost calculator is configured to calculate a maintenance cost during the current operation;

[0016] the depreciation cost calculator is configured to calculate a depreciation cost during the current operation;

[0017] the insurance cost calculator is configured to calculate an insurance cost during the current operation.

[0018] Further, the vehicle information includes GPS signals, a current battery level of the vehicle, total battery level of the vehicle and total mileage data of the vehicle, the data processing module is configured to accept user input information, map API information, CAN bus signals and cloud big data model data, and calculate operation planning and cost estimation. The user input data includes vehicle basic parameters, an operation starting point, a destination, a cargo weight and an estimated arrival time. The vehicle basic parameters include a type of the vehicle (traction, self-unloading, cargo carrying), purchase information (total vehicle price, down payment ratio, loan period and loan interest rate), vehicle self-weight and vehicle axle number. The vehicle basic parameters only need to be input by the user once when the operation simulator is used for the first time, and do not need to be repeatedly input when used again. The simulator allows the user to modify the parameters when the vehicle basic parameters change.

[0019] Further, the cloud big data model data includes average power consumption of the vehicle on an operation section, total maintenance cost of the vehicle in a whole life cycle, total insurance cost of the vehicle in the whole life cycle, total mileage of the vehicle in design, and is sent to the data processing module through the intelligent remote communication module.

[0020] Further, the map API is provided by a third-party map vendor, which can provide path planning, charging station electricity price and highway toll standard information for the algorithm controller.

[0021] Further, the energy cost calculator can obtain the charging electricity of each charging station along the route according to the energy supplement plan, multiply the electricity price of the charging station at different times, and add the electricity difference between the departure place and the destination multiplied by the average electricity price to obtain the total energy consumption cost during the operation period.

[0022] Further, the operation planning simulator reads the current electricity proportion of the vehicle, the total electricity of the vehicle from the CAN bus, the self-weight and the cargo weight of the vehicle from the user input information, and the average electricity consumption of the vehicle from the cloud big data model to calculate the optimal energy supplement plan, including the electricity proportion at the destination and the charging electricity of each charging station along the route.

[0023] Further, the road toll cost calculator is used to calculate the total road toll cost during the operation period, which can obtain the length of the toll road section according to the path planning, and obtain the toll price per kilometer of the toll road section according to the vehicle axle number in the vehicle basic information. The total road toll cost during the operation period is obtained by multiplying the length of the toll road section by the toll price.

[0024] Further, the maintenance cost calculator is used to calculate the maintenance cost during the operation period, which can obtain the total maintenance cost of the vehicle during the whole life cycle, and multiply the ratio of the total mileage during the operation period to the total designed mileage of the vehicle to obtain the maintenance cost during the operation period.

[0025] Further, the depreciation cost calculator is used to calculate the depreciation cost during the operation period, which can calculate the total cost of purchasing the vehicle according to the purchase information, and multiply the ratio of the operation distance of the route selected by the user to the total designed mileage of the vehicle corresponding to the vehicle basic parameters to obtain the depreciation cost during the operation period.

[0026] Further, the insurance cost calculator is used to calculate the insurance cost during the operation period, which can obtain the total premium of the vehicle during the whole life cycle, and multiply the ratio of the operation distance of the route selected by the user to the total designed mileage of the vehicle corresponding to the vehicle basic parameters to obtain the insurance cost during the operation period.

[0027] A new energy commercial vehicle operation simulation method based on a cloud big data model, comprising the following steps:

[0028] Step 1: The operation simulator obtains user input data;

[0029] Step 2: The path planning simulator obtains the current system time T1, calculates the maximum operation time Tm=T2-T1, and plans the optimal operation path.

[0030] Step 3: The energy supplement planning simulator obtains the operation path from the path planning simulator, establishes a mathematical model, and calculates the optimal energy supplement planning;

[0031] The energy supplement planning includes the proportion of electricity Pe when the vehicle arrives at the destination and the charging electricity Ei of each charging station on the operation path (i = 1, 2, 3, …, n), the value of i is equal to the number of all charging stations sorted by distance from the starting point, and the value of n is equal to the total number of charging stations.

[0032] Step 4: The energy cost calculator obtains the energy supplement planning from the energy supplement planning simulator and calculates the energy cost Ce;

[0033] Step 5: The road fare cost calculator obtains the operation path from the path planning simulator and calculates the road fare Cr cost;

[0034] Step 6: The maintenance cost calculator calculates the driving distance Sd according to the path planning, obtains the total vehicle maintenance cost Ct and the total vehicle design mileage St corresponding to the vehicle type from the cloud big data model, and calculates the maintenance cost;

[0035] Step 7: The depreciation cost calculator obtains the driving distance Sd, reads the total vehicle price V, down payment ratio p, and loan interest rate k input by the user, obtains the total vehicle design mileage St from the cloud big data model, and calculates the depreciation cost;

[0036] Step 8: The depreciation cost calculator obtains the driving distance Sd from the maintenance cost calculator, obtains the total vehicle design mileage St and the total life cycle insurance premium Cx from the cloud big data model, and calculates the insurance cost Cy;

[0037] Step 9: The energy cost Ce, road fare Cr cost, maintenance cost Cm, depreciation cost Cp, and insurance cost Cy are summed up to obtain the best cost.

[0038] Further, in step 1, when the user first uses the operation simulator, the vehicle basic parameters need to be input on the multimedia screen, including vehicle type, total vehicle price V, down payment ratio p, loan interest rate k, vehicle self-weight W0, and vehicle axle number. The vehicle type includes tractor, truck, and dump truck. When the user is not using the operation simulator for the first time, step 1 is skipped and the operation information is directly input, including the starting point a, destination b, cargo weight W1, and estimated arrival time T2.

[0039] Further, in step 2, the starting point a, destination b, and estimated arrival time T2 are obtained from the user input information, and then the map API is called, the path planning simulator obtains the current system time T1, calculates the maximum operation time Tm = T2-T1, and plans the optimal operation path

[0040] Further, in step 3, the energy supplement planning simulator reads the current proportion of electricity Ps of the vehicle, the total electricity Et of the vehicle from the CAN bus, reads the self-weight W0 of the vehicle and the weight W1 of the goods from the user input information, obtains the average electricity consumption of the vehicle under the current total weight of the vehicle and goods and the average electricity consumption of the vehicle under the current total weight of the vehicle and the operating section from the cloud big data model, establishes a mathematical model, and calculates the optimal energy supplement plan.

[0041] Further, in step 4, the energy cost of the new energy commercial vehicle is related to the energy supplement plan, the real-time electricity price, and the electricity difference between the departure and destination. The energy cost calculator obtains the energy supplement plan from the energy supplement planning simulator, calls the map API to obtain the charging electricity Ei (i = 1, 2, 3, …, n) of each charging station on the operating path in the energy supplement plan, the value of i is equal to the number of all charging stations sorted by distance from the departure location, and the value of n is equal to the total number of charging stations. Calculate the energy cost Ce, the calculation formula is as follows:

[0042]

[0043] Further, in step 5, the road toll cost of the new energy commercial vehicle is related to the length of the highway section and the toll rate of the highway section. According to the standard JT / T 489-2019, the toll rate of the highway section is related to the type and number of axles of the vehicle. The road toll cost calculator obtains the operating path from the path planning simulator, reads the vehicle type and number of axles input by the user, calls the map API to obtain the length Sj (j = 1, 2, 3, …, x) of all highway sections on the operating path and the toll rate Cj (j = 1, 2, 3, …, x) of each highway section, the value of j is equal to the number of all highway sections sorted by distance from the departure location, and the value of x is equal to the total number of highway sections. Calculate the road toll cost Cr, the calculation formula is as follows:

[0044]

[0045] Further, in step 6, the maintenance cost of the new energy commercial vehicle is related to the vehicle driving course and the vehicle unit mileage maintenance cost. The vehicle unit mileage maintenance cost is related to the type of the vehicle. The maintenance cost calculator calculates the driving mileage Sd according to the path planning, obtains the total maintenance cost Ct of the vehicle during the whole life cycle and the total designed mileage St of the vehicle corresponding to the type of the vehicle from the cloud big data model. Calculate the maintenance cost Cm, the calculation formula is as follows:

[0046]

[0047] Further, in step 7, the depreciation cost of the new energy commercial vehicle is related to the proportion of the total purchase cost and the operating mileage in the design mileage. The depreciation cost calculator obtains the driving mileage Sd from the maintenance cost calculator, reads the total price V of the vehicle, the down payment ratio p, and the loan interest rate k input by the user, and obtains the total design mileage St of the vehicle from the cloud big data model. The depreciation cost Cp is calculated, and the calculation formula is as follows:

[0048]

[0049] Further, in step 8, the insurance cost of the new energy commercial vehicle is related to the proportion of the total premium and the operating mileage in the design mileage. The depreciation cost calculator obtains the driving mileage Sd from the maintenance cost calculator, obtains the total design mileage St and the total premium Cx of the vehicle from the cloud big data model, and calculates the insurance cost Cy, and the calculation formula is as follows:

[0050]

[0051] Further, in step 9, the energy cost Ce, the road cost Cr, the maintenance cost Cm, the depreciation cost Cp, and the insurance cost Cy are summed up to obtain the best cost.

[0052] The vehicle-mounted multimedia screen displays the calculation result of the operation simulator to the user, and completes the operation simulation.

[0053] The beneficial effects of the present application are that when the new energy commercial vehicle user receives the order, the new energy commercial vehicle operation simulator can be used to make operation planning, calculate the operation cost and order income, improve the convenience of user operation, and improve the operation efficiency. BRIEF DESCRIPTION OF DRAWINGS

[0054] Figure 1 It is a system structure schematic diagram of the present application.

[0055] Figure 2 It is a structure schematic diagram of the data processing module in the present application.

[0056] Figure 3 It is a flow chart in the present application. DETAILED DESCRIPTION

[0057] The present application will be further described below in combination with the drawings and reference numerals.

[0058] In order to more clearly understand the above-mentioned purposes, features and advantages of the present application, the present application will be described in detail below in combination with the drawings and specific embodiments. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other without conflict.

[0059] The terms “first,” “second,” “third,” etc., are used only to distinguish descriptions and should not be interpreted as indicating or implying relative importance.

[0060] In the description of this invention, it should also be noted that, unless otherwise explicitly specified and limited, the terms "set," "install," "connect," and "link" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0061] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0062] Example 1:

[0063] like Figure 1 As shown, a new energy commercial vehicle operation simulator based on a cloud-based big data model includes:

[0064] The algorithm controller includes a data acquisition module and a data processing module. The data acquisition module is responsible for acquiring vehicle information from the CAN bus, and the data processing module is used to receive the information.

[0065] The intelligent remote communication module interacts with the data processing module via a CAN line and with the cloud-based big data model via a 5G network or the Internet.

[0066] The cloud-based big data model is used to calculate the data of the cloud-based big data model based on the data uploaded by the intelligent remote communication module and other vehicle operation data.

[0067] Map API is used to provide information on route planning, charging station electricity prices, and highway toll rates.

[0068] The operation planning simulator includes a route planning simulator and a power replenishment planning simulator. The route planning simulator is used to calculate the optimal route plan that meets the conditions. The power replenishment planning simulator obtains the operation route through the route planning simulator and calculates the optimal power replenishment plan.

[0069] The operating cost simulator includes an energy cost calculator, a toll cost calculator, a maintenance cost calculator, a depreciation cost calculator, and an insurance cost calculator.

[0070] The energy cost calculator is used to calculate the total energy consumption cost during this operation period;

[0071] The toll cost calculator is used to calculate the total toll cost during this operation.

[0072] The maintenance cost calculator is used to calculate the maintenance costs during this operation period;

[0073] The depreciation cost calculator is used to calculate the depreciation cost during this operating period;

[0074] The insurance cost calculator is used to calculate the insurance costs during this operation period.

[0075] Example 2:

[0076] Based on Example 1, such as Figure 2 As shown, the vehicle information includes GPS signal, current battery percentage, total battery level, and total mileage. The data processing module accepts user input, map API information, CAN bus signals, and cloud-based big data model data to calculate operational plans and cost estimates. User input includes basic vehicle parameters, departure point, destination, cargo weight, and estimated arrival time. Basic vehicle parameters include vehicle type (tractor, dump truck, cargo truck), purchase information (total vehicle price, down payment percentage, loan period, and loan interest rate), vehicle weight, and number of axles. These basic parameters only need to be entered once when using the operation simulator for the first time; subsequent uses do not require re-entry. The simulator allows users to modify vehicle parameters as they change.

[0077] The cloud-based big data model data includes the vehicle's average power consumption on the operating route, the total maintenance and repair costs throughout the vehicle's life cycle, the total insurance costs throughout the life cycle, and the vehicle's designed total mileage, and is sent to the data processing module through the intelligent remote communication module.

[0078] The map API is provided by a third-party map provider and can provide the algorithm controller with information on route planning, charging station electricity prices, and highway toll standards.

[0079] The energy cost calculator can obtain the charging capacity of each charging station along the route based on the energy replenishment plan, multiply it by the electricity price Ci of the charging station at different times along the route, add the difference in electricity consumption between the origin and destination multiplied by the average electricity price, and obtain the total energy consumption cost during this operation.

[0080] The operation planning simulator reads the vehicle's current battery percentage and total battery level from the CAN bus, the vehicle's weight and cargo weight from user input, and obtains the vehicle's average power consumption from a cloud-based big data model to calculate the optimal charging plan, including the battery percentage at the destination and the charging capacity of each charging station along the route.

[0081] The road toll cost calculator is configured to calculate the total road toll cost during the operation, and is capable of obtaining the length of the toll road section according to the path planning, and obtaining the toll price per kilometer of the toll road section according to the vehicle axle number in the vehicle basic information. The length of the toll road section multiplied by the toll price is the total road toll cost during the operation.

[0082] The maintenance cost calculator is configured to calculate the maintenance cost during the operation, and is capable of multiplying the total maintenance cost of the vehicle during the whole life cycle by the ratio of the total mileage during the operation to the total designed mileage of the vehicle to obtain the maintenance cost during the operation.

[0083] The depreciation cost calculator is configured to calculate the depreciation cost during the operation, and is capable of calculating the total cost of purchasing the vehicle according to the purchase information, and multiplying the ratio of the operation distance of the route planning selected by the user to the total designed mileage of the vehicle corresponding to the vehicle basic parameters to obtain the depreciation cost during the operation.

[0084] The insurance cost calculator is configured to calculate the insurance cost during the operation, and is capable of multiplying the total premium of the vehicle during the whole life cycle by the ratio of the operation distance of the route planning selected by the user to the total designed mileage of the vehicle corresponding to the vehicle basic parameters to obtain the insurance cost during the operation.

[0085] Embodiment 3: A new energy commercial vehicle operation simulation method based on a cloud big data model, comprising the following steps:

[0086] Step 1: The operation simulator obtains user input data.

[0087] Step 2: The path planning simulator obtains the current system time T1, calculates the maximum operation time Tm=T2-T1, and plans the optimal operation path.

[0088] Step 3: The energy supplement planning simulator obtains the operation path from the path planning simulator, establishes a mathematical model, and calculates the optimal energy supplement planning.

[0089] The energy supplement planning includes the proportion of the electric quantity Pe when the vehicle arrives at the destination and the charging electric quantity Ei (i=1, 2, 3, …, n) of each charging station on the operation path. The value of i is equal to the number of all charging stations sorted according to the distance from the starting point, and the value of n is equal to the total number of charging stations.

[0090] Step 4: The energy cost calculator obtains the energy supplement planning from the energy supplement planning simulator and calculates the energy cost Ce.

[0091] Step 5: The road toll cost calculator obtains the operation path from the path planning simulator and calculates the road toll cost Cr.

[0092] Step 6: The maintenance cost calculator calculates the driving distance Sd according to the path planning, obtains the total vehicle maintenance cost Ct and the total vehicle design mileage St corresponding to the vehicle type from the cloud big data model, and calculates the maintenance cost;

[0093] Step 7: The depreciation cost calculator obtains the driving distance Sd, reads the total vehicle price V, down payment ratio p, and loan interest rate k input by the user, obtains the total vehicle design mileage St from the cloud big data model, and calculates the depreciation cost;

[0094] Step 8: The depreciation cost calculator obtains the driving distance Sd from the maintenance cost calculator, obtains the total vehicle design mileage St and the total life cycle total insurance premium Cx from the cloud big data model, and calculates the insurance cost Cy;

[0095] Step 9: The energy cost Ce, the road cost Cr, the maintenance cost Cm, the depreciation cost Cp, and the insurance cost Cy are summed up to obtain the best cost.

[0096] Embodiment 4:

[0097] On the basis of embodiment 3, in step 1, when the user uses the operation simulator for the first time, the vehicle basic parameters need to be input on the multimedia screen, including the vehicle type, the total vehicle price V, the down payment ratio p, the loan interest rate k, the vehicle self-weight W0, and the vehicle axle number. The vehicle type includes a tractor, a truck, and a dump truck.

[0098] When the user is not using the operation simulator for the first time, step 1 is skipped, and the operation information is directly input, including the departure place a, the destination b, the cargo weight W1, and the expected arrival time T2.

[0099] Embodiment 5:

[0100] On the basis of embodiment 3, in step 2, the departure place a, the destination b, and the expected arrival time T2 are obtained from the user input information, then the current system time T1 is obtained by calling the map API, the path planning simulator calculates the maximum operation time Tm = T2-T1, and the optimal operation path is planned.

[0101] Embodiment 6:

[0102] On the basis of embodiment 3, in step 3, the energy supplement planning simulator reads the current vehicle power ratio Ps and the total vehicle power Et from the CAN bus, reads the vehicle self-weight W0 and the cargo weight W1 from the user input information, obtains the average power consumption of the vehicle under the current vehicle and cargo total weight and the operation section from the cloud big data model, establishes a mathematical model, and calculates the optimal energy supplement planning.

[0103] Embodiment 7:

[0104] On the basis of embodiment 6, in step 4: the energy cost of new energy commercial vehicle is related to the energy supplement plan, real-time electricity price Ci and the difference in electricity quantity between the departure and destination. The energy cost calculator obtains the energy supplement plan from the energy supplement plan simulator, calls the map API to obtain the charging electricity quantity Ei (i = 1, 2, 3, …, n) of each charging station on the operating path in the energy supplement plan, the value of i is equal to the number of all charging stations sorted by distance from the departure place, and the value of n is equal to the total number of charging stations. The energy cost Ce is calculated, and the calculation formula is as follows:

[0105]

[0106] Embodiment 8:

[0107] On the basis of embodiment 7, in step 5: the road toll cost of new energy commercial vehicle is related to the length of highway section and the toll rate of highway section. According to the standard JT / T 489-2019, the toll rate of highway section is related to the type and number of axles of vehicle. The road toll cost calculator obtains the operating path from the path planning simulator, reads the user input vehicle type and number of axles, calls the map API to obtain the length Sj (j = 1, 2, 3, …, x) of all highway sections on the operating path and the toll rate Cj (j = 1, 2, 3, …, x) of each highway section, the value of j is equal to the number of all highway sections sorted by distance from the departure place, and the value of x is equal to the total number of highway sections. The road toll cost Cr is calculated, and the calculation formula is as follows:

[0108]

[0109] Embodiment 9:

[0110] On the basis of embodiment 8, in step 6: the maintenance cost of new energy commercial vehicle is related to the vehicle driving course and the vehicle unit mileage maintenance cost. The vehicle unit mileage maintenance cost is related to the type of vehicle. The maintenance cost calculator calculates the driving mileage Sd according to the path planning, obtains the total maintenance cost Ct of the vehicle in the whole life cycle and the designed total mileage St of the vehicle corresponding to the type of vehicle from the cloud big data model. The maintenance cost Cm is calculated, and the calculation formula is as follows:

[0111]

[0112] Embodiment 10:

[0113] On the basis of embodiment 9, in step 7, the depreciation cost of the new energy commercial vehicle is related to the proportion of the total purchase cost and the operating mileage in the design mileage of the vehicle. The depreciation cost calculator obtains the driving mileage Sd from the maintenance cost calculator, reads the total price V of the vehicle, the down payment ratio p and the loan interest rate k input by the user, and obtains the total design mileage St of the vehicle from the cloud big data model. The depreciation cost Cp is calculated, and the calculation formula is as follows:

[0114]

[0115] Embodiment 11:

[0116] On the basis of embodiment 10, in step 8, the insurance cost of the new energy commercial vehicle is related to the proportion of the total premium and the operating mileage in the design mileage of the vehicle in the whole life cycle. The depreciation cost calculator obtains the driving mileage Sd from the maintenance cost calculator, obtains the total design mileage St and the total premium Cx of the vehicle in the whole life cycle from the cloud big data model, and calculates the insurance cost Cy, and the calculation formula is as follows:

[0117]

[0118] Embodiment 12:

[0119] On the basis of embodiment 11, in step 9, the energy cost Ce, the road cost Cr, the maintenance cost Cm, the depreciation cost Cp and the insurance cost Cy are summed up to obtain the best cost.

[0120] The vehicle-mounted multimedia screen displays the calculation result of the operation simulator to the user, and completes the operation simulation.

[0121] In the actual operation process of the vehicle, the operation simulator can collect vehicle information in real time through the CAN bus, record the actual total mileage and power change data of the vehicle from a place to b place, and count the actual operation driving mileage and total power consumption of the vehicle, together with the total weight of the vehicle and goods Ws, the data of the starting place a and the destination b, and return them to the cloud big data model through the intelligent remote communication module, for optimizing and iterating the average power consumption data model of the vehicle in the operation section. Wherein, the total weight of the vehicle and goods:

[0122] Ws+W0+W1

[0123] The present application is not limited to the above optional embodiments, anyone can derive other various forms of products under the inspiration of the present application, but regardless of any change in shape or structure, any technical solution falling within the scope defined by the claims of the present application falls within the protection scope of the present application.

Claims

1. A new energy commercial vehicle operation simulator based on a cloud-based big data model, characterized in that, include: The algorithm controller includes a data acquisition module and a data processing module. The data acquisition module is responsible for acquiring vehicle information from the CAN bus, and the data processing module is used to receive the information. The intelligent remote communication module interacts with the data processing module via a CAN line and with the cloud-based big data model via a 5G network or the Internet. The cloud-based big data model is used to calculate the data of the cloud-based big data model based on the data uploaded by the intelligent remote communication module and other vehicle operation data; Map API is used to provide information on route planning, charging station electricity prices, and highway toll rates; The operation planning simulator includes a route planning simulator and a power replenishment planning simulator. The route planning simulator is used to calculate the optimal route plan that meets the conditions. The power replenishment planning simulator obtains the operation route through the route planning simulator and calculates the optimal power replenishment plan. Operating cost simulator, including energy cost calculator, toll cost calculator, maintenance cost calculator, depreciation cost calculator and insurance cost calculator; The energy cost calculator is used to calculate the total energy consumption cost during this operation period; The toll cost calculator is used to calculate the total toll cost during this operation. The maintenance cost calculator is used to calculate the maintenance costs during this operation period; The depreciation cost calculator is used to calculate the depreciation cost during this operating period; The insurance cost calculator is used to calculate the insurance costs during this operation period.

2. A method for simulating the operation of new energy commercial vehicles based on a cloud-based big data model, characterized in that: Includes the following steps: Step 1: Use the operation simulator to obtain user input data; Step 2: The route planning simulator obtains the current system time T1, calculates the maximum operating time Tm = T2 - T1, and plans the optimal operating route; Step 3: The energy replenishment planning simulator obtains the operation path from the path planning simulator, establishes a mathematical model, and calculates the optimal energy replenishment plan; Step 4: The energy cost calculator obtains the energy replenishment plan from the energy replenishment planning simulator and calculates the energy cost Ce; Step 5: The toll cost calculator obtains the operating route from the route planning simulator and calculates the toll cost (Cr). Step 6: The maintenance cost calculator calculates the mileage Sd based on the route planning, obtains the total maintenance cost Ct and the total design mileage St of the vehicle corresponding to the vehicle type from the cloud big data model, and calculates the maintenance cost. Step 7: The depreciation cost calculator obtains the mileage Sd, reads the total vehicle price V, down payment ratio p, and loan interest rate k input by the user, obtains the vehicle's design total mileage St from the cloud big data model, and calculates the depreciation cost. Step 8: Depreciation Cost Calculator. Obtain the mileage Sd from the maintenance cost calculator, obtain the vehicle's total design mileage St and total life-cycle insurance premium Cx from the cloud big data model, and calculate the insurance cost Cy. Step 9: Sum the energy cost Ce, toll cost Cr, maintenance cost Cm, depreciation cost Cp, and insurance cost Cy to obtain the optimal cost.

3. The new energy commercial vehicle operation simulation method based on a cloud-based big data model according to claim 2, characterized in that: In step 1, when a user uses the operation simulator for the first time, they need to input basic vehicle parameters on the multimedia screen, including vehicle type, total vehicle price V, down payment ratio p, loan interest rate k, vehicle weight W0, and number of axles.

4. The new energy commercial vehicle operation simulation method based on a cloud-based big data model according to claim 2, characterized in that: In step 3, the energy replenishment planning simulator reads the vehicle's current battery percentage Ps and total battery Et from the CAN bus, reads the vehicle's weight W0 and cargo weight W1 from the user input information, and obtains the vehicle's average power consumption on the current total vehicle and cargo weight and the operating route from the cloud big data model.

5. The new energy commercial vehicle operation simulation method based on a cloud-based big data model according to claim 4, characterized in that: In step 4, the energy cost Ce is calculated using the following formula:

6. The new energy commercial vehicle operation simulation method based on a cloud-based big data model according to claim 5, characterized in that: In step 5, the formula for calculating the toll cost (Cr) is as follows:

7. The new energy commercial vehicle operation simulation method based on a cloud-based big data model according to claim 6, characterized in that: In step 6, the maintenance cost Cm is calculated using the following formula:

8. The new energy commercial vehicle operation simulation method based on a cloud-based big data model according to claim 7, characterized in that: In step 7, the formula for calculating depreciation cost Cp is as follows:

9. The new energy commercial vehicle operation simulation method based on a cloud-based big data model according to claim 8, characterized in that: In step 8, the insurance cost Cy is calculated using the following formula:

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