A truck energy-saving navigation system based on crowdfunding conditions

Abstract

The present invention discloses a truck energy-saving navigation system based on crowdfunding working conditions, which relates to the field of intelligent transportation technology and includes an on-board communication module and a cloud database module; the on-board communication module is used to obtain driving information and truck load; the cloud database module is connected to the on-board communication module; the cloud database module is used to calculate the fuel consumption required for each route between the departure point and the destination based on the matching fuel consumption data when matching fuel consumption data is screened out using the cloud database; the cloud database module is further used to use speed curves corresponding to different routes between the departure point and the destination to calculate the fuel consumption required for the route corresponding to the speed curve when matching fuel consumption data is not screened out using the cloud database. The present invention can estimate the fuel consumption required for each route between the departure point and the destination, allowing the driver to select a fuel-efficient route, thereby avoiding frequent reminders and reducing truck transportation fuel consumption.

Description

Technical Field

[0001] The present invention relates to the field of intelligent transportation technology, and in particular to a truck energy-saving navigation system based on crowdfunding working conditions. Background Art

[0002] With rising economic levels, the number of trucks engaged in intercity and even interprovincial transport is increasing. Due to the long distances covered, truck fuel consumption has become a significant component of freight costs. The current annual rise in gasoline prices has placed a significant financial burden on truck drivers, leading to increased freight costs and hindering the development of China's long-distance transport industry. Therefore, there is an urgent need for an energy-efficient navigation system for freight trucks. Currently, long-distance freight in China primarily relies on GPS navigation or GPS-based mapping software, such as apps like Amap and Baidu Maps. While these apps offer significant convenience, they only provide drivers with information on the distance and time required to reach their destination, without providing information on the fuel consumption of each route. Truck mileage and fuel consumption are not necessarily positively correlated. Due to China's complex terrain and the many hills involved in highway construction, fuel consumption varies significantly for trucks traveling the same distance. However, these mapping and navigation apps fail to address situations where drivers have ample time and want to save costs.

[0003] Despite widespread adoption of economical driving, most truck drivers rely solely on experience to reduce fuel consumption, using superficial methods like driving at a constant speed and shortening driving distances. Most truck drivers lack professional knowledge of vehicle fuel economy and are unable to determine the fuel consumption of a specific route based on data displayed by map apps. Currently, many patents rely on obtaining driving information from the vehicle, including acceleration, angular velocity, and the distance between the vehicle and other vehicles. This information is then uploaded to a CAN bus or other local area network via a data transmission platform. The data transmitted to the server via the CAN bus is then analyzed using a specific data processing method to provide effective and reasonable driving recommendations, ultimately enabling the vehicle to achieve economical driving and achieve energy conservation and environmental protection. For example, invention patent CN103050019A uses the vehicle's navigation device to upload the vehicle's GPS information and fuel consumption to a server. A data processing module then detects the driver's poor driving habits, ultimately providing real-time notifications to achieve fuel savings. Patent "CN108909617A" proposes an energy-saving driving strategy. This strategy is calculated by matching intersection traffic information with GPS information through a radio frequency transmitter. This strategy is then communicated to the driver via onboard voice prompts, ultimately achieving energy conservation. While the aforementioned patent can reduce fuel consumption to a certain extent through driver behavior and vehicle driving strategy, it cannot provide global advice and guidance at the vehicle route level. Specifically, it cannot estimate the fuel consumption required for each route from the departure point to the destination, allowing the driver to select fuel-efficient routes and reduce truck transportation fuel consumption. Furthermore, frequent driving behavior and strategy reminders can easily lead to driver fatigue, which is not conducive to the implementation of the solution.

[0004] In summary, how to estimate the fuel consumption required for each route between the departure point and the destination so that the driver can choose a fuel-efficient route, avoid frequent reminders, and reduce truck transportation fuel consumption has become an urgent problem to be solved by technicians in this field. Summary of the Invention

[0005] The purpose of the present invention is to provide a truck energy-saving navigation system based on crowdfunding working conditions, which can estimate the fuel consumption required for the route from the departure point to the destination so that the driver can choose a fuel-saving route.

[0006] To achieve the above object, the present invention provides the following solutions:

[0007] A truck energy-saving navigation system based on crowdfunding working conditions, the system comprising an on-board communication module and a cloud database module;

[0008] The vehicle communication module is used to obtain driving information and truck load; the driving information includes truck model, departure point and destination;

[0009] The cloud database module is connected to the on-board communication module; the cloud database module is configured to calculate the fuel consumption required for each route between the departure point and the destination based on the matching fuel consumption data when using the cloud database to screen out matching fuel consumption data; the cloud database includes the speed, fuel consumption, and load at each location of different models of vehicles traveling on any section of any route between the departure point and the destination; the matching fuel consumption data is the fuel consumption of the same vehicle at each location on each route between the departure point and the destination; the same vehicle is a vehicle of the same model and load as the truck;

[0010] The cloud database module is further configured to obtain a matching speed mode based on the matching speed data when the matching fuel consumption data is not filtered out using the cloud database, and obtain speed curves corresponding to different routes between the departure point and the destination based on the matching speed mode, and calculate the required fuel consumption for the route corresponding to the speed curve using the speed curve; the matching speed data is the speed of the same type of vehicle at each position on each route between the departure point and the destination; the same type of vehicle is a vehicle of the same type as a truck; and the matching speed mode is the mode of the speed of the same type of vehicle at each position on each route between the departure point and the destination.

[0011] Optionally, the system further includes a mobile APP module;

[0012] The mobile APP module is connected to the vehicle communication module and the cloud database module respectively;

[0013] The mobile APP module is used to input driving information and obtain the fuel consumption required for each route from the departure point to the destination calculated by the cloud database module through the vehicle communication module;

[0014] The mobile APP module is also used to send the driving information directly to the cloud database module when the on-board communication module fails, and directly receive the fuel consumption required for each route from the departure point to the destination sent by the cloud database module.

[0015] Optionally, the vehicle-mounted communication module is connected to the vehicle-mounted OBD interface of the truck;

[0016] The vehicle communication module is further used to obtain the vehicle OBD data of the current position sent by the vehicle OBD interface in real time; the vehicle OBD data includes truck speed, truck fuel consumption and truck load.

[0017] Optionally, the cloud database module is further configured to record the vehicle-mounted OBD data sent in real time by the vehicle-mounted communication module, and store the vehicle-mounted OBD data in the cloud database.

[0018] Optionally, the truck load corresponds to the change in air pressure of the truck tires; the truck load is determined based on the change in air pressure of the truck tires.

[0019] Optionally, the air pressure change of the truck tire is calculated using the formula PV = (V-ΔV)(P+ΔP) and calculate;

[0020] Where P is the air pressure of the truck tire, V is the volume of the truck tire, ΔV is the volume change of the truck tire, ΔP is the air pressure change of the truck tire, r2 is the outer diameter of the truck tire, and l is the contact length between the truck tire and the road surface.

[0021] Optionally, the cloud database module adds up the fuel consumption of the same vehicle at each location on any route between the departure point and the destination to obtain the required fuel consumption for the route from the departure point to the destination.

[0022] Optionally, the vehicle-mounted communication module is connected to the cloud database module via a 4G communication network.

[0023] Optionally, the mobile APP module is connected to the vehicle communication module via Bluetooth.

[0024] According to the specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0025] The present invention discloses a truck energy-saving navigation system based on crowdfunding working conditions, which is provided with an on-board communication module to obtain the truck load, truck model, departure point and destination; a cloud database module is provided to use the cloud database to match the fuel consumption data of vehicles with the same model and load as the truck, thereby obtaining the fuel consumption required for all routes (each route) between the departure point and the destination; when no match can be made, the cloud database module uses the cloud database to obtain the speed curve of the vehicle with the same type as the truck, and uses the speed curve to obtain the fuel consumption required for each route between the departure point and the destination, thereby realizing the estimation of the fuel consumption required for the route between the departure point and the destination, so as to enable the driver to select a fuel-saving route, avoid frequent reminders and reduce the fuel consumption of truck transportation. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0027] Figure 1 This is a structural diagram of an embodiment of a truck energy-saving navigation system based on crowdfunding working conditions of the present invention;

[0028] Figure 2 A schematic diagram of the system structure for implementing crowdfunding energy-saving navigation in an embodiment of the present invention;

[0029] Figure 3 Schematic diagram of the tire pressure load calculation model of the present invention;

[0030] Figure 4 A flow chart of a method for implementing energy-saving navigation in crowdfunding working conditions provided by an embodiment of the present invention;

[0031] Figure 5 A schematic diagram of an interface for implementing crowdfunding energy-saving navigation in an embodiment of the present invention. DETAILED DESCRIPTION

[0032] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0033] The purpose of the present invention is to provide a truck energy-saving navigation system based on crowdfunding working conditions, which can estimate the fuel consumption required for each route from the departure point to the destination, so that the driver can choose a fuel-saving route, avoid frequent reminders and reduce truck transportation fuel consumption.

[0034] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0035] Figure 1 This is a structural diagram of an embodiment of the truck energy-saving navigation system based on crowdfunding working conditions of the present invention. Figure 1 The truck energy-saving navigation system based on crowdfunding working conditions includes an on-board communication module 101 and a cloud database module 102.

[0036] The onboard communication module 101 is connected to the cloud database module 102 via a 4G communication network. The onboard communication module 101 is used to obtain driving information and truck load; driving information includes truck model, departure point, and destination. The onboard communication module 101 is connected to the truck's onboard OBD interface. The onboard communication module 101 is also used to obtain real-time onboard OBD data of the current location transmitted by the onboard OBD interface. This onboard OBD data includes truck speed, fuel consumption, and load.

[0037] The cloud database module 102 is connected to the on-board communication module 101; the cloud database module 102 is used to calculate the fuel consumption required for each route between the departure point and the destination based on the matching fuel consumption data when using the cloud database to filter out the matching fuel consumption data; the cloud database module 102 adds the fuel consumption of the same vehicle at each position on any route between the departure point and the destination to obtain the fuel consumption required for the route between the departure point and the destination; the cloud database includes the speed, fuel consumption and load at each position of different models of vehicles traveling on any section of any route between the departure point and the destination; the matching fuel consumption data is the fuel consumption of the same vehicle at each position on each route between the departure point and the destination; the same vehicle is a vehicle of the same model as the truck and has the same load as the truck.

[0038] The cloud database module 102 is also used to obtain a matching speed mode based on the matching speed data when no matching fuel consumption data is filtered out using the cloud database, and to obtain speed curves corresponding to different routes between the departure point and the destination based on the matching speed mode, that is, to obtain a speed curve corresponding to each route between the departure point and the destination, and to calculate the required fuel consumption for the route corresponding to the speed curve using the speed curve; the matching speed data is the speed of the same type of vehicle at each position on each route between the departure point and the destination; the same type of vehicle is a vehicle of the same type as a truck; the matching speed mode is the mode of the speed of the same type of vehicle at each position on each route between the departure point and the destination.

[0039] The cloud database module 102 is further configured to record the vehicle-mounted OBD data sent in real time by the vehicle-mounted communication module 101 and store the vehicle-mounted OBD data in the cloud database.

[0040] The truck load in the vehicle OBD data corresponds to the change in the air pressure of the truck tires. The truck load is determined based on the change in the air pressure of the truck tires. The change in the air pressure of the truck tires is calculated using the formula PV = (V-ΔV)(P+ΔP) and Calculation; where P is the air pressure of the truck tire, V is the volume of the truck tire, ΔV is the volume change of the truck tire, ΔP is the air pressure change of the truck tire, r2 is the outer diameter of the truck tire, and l is the contact length between the truck tire and the road surface.

[0041] The crowdfunding-based truck energy-saving navigation system also includes a mobile app module. The mobile app module is connected to the onboard communication module 101 and the cloud database module 102. The mobile app module is used to input driving information and obtain the fuel consumption calculated by the cloud database module 102 for each route between the departure point and the destination through the onboard communication module 101. The mobile app module is also used to directly transmit driving information to the cloud database module 102 and directly receive the fuel consumption calculated by the cloud database module 102 for each route between the departure point and the destination in the event of a malfunction of the onboard communication module 101.

[0042] Specifically, the mobile APP module is connected to the vehicle communication module 101 via Bluetooth.

[0043] The technical solution of the present invention is described below with a specific embodiment:

[0044] Figure 2 This is a schematic diagram of the system structure for realizing crowdfunding energy-saving navigation in an embodiment of the present invention. Figure 2 The present invention implements a crowdfunding working condition energy-saving navigation system (a truck energy-saving navigation system based on crowdfunding working conditions) mainly includes:

[0045] The on-board communication module, primarily connected to the vehicle's OBD interface, is used to obtain the truck's CAN bus data and information entered by the driver via the mobile software interface. CAN bus data is required for interaction between the vehicle's various control modules. Therefore, the CAN bus can capture data such as vehicle speed, various temperatures, and throttle position. This information can be uploaded to the on-board communication device via the OBD interface.

[0046] The cloud database module connects to the on-board communication device (on-board communication module) via the 4G communication network and receives CAN bus data as well as the truck's model and driving data. The cloud database module can directly match the fuel consumption information of vehicles of the same model on each section of the corresponding route, using this information to calculate the fuel consumption of the entire route. Another method is to use an algorithm to calculate the vehicle's fuel consumption based on a speed curve formed by the speed mode of vehicles of the same type and information entered by the driver, and use this fuel consumption data as the vehicle's estimated fuel consumption. The estimated fuel consumption is transmitted to the on-board communication module via the 4G module (4G communication network) and ultimately displayed on the user's mobile app. In the event of a malfunction in the on-board communication device, the cloud database module can directly connect to the mobile app module to achieve full functionality. When the on-board communication device is functioning normally, the cloud database module can temporarily close the direct connection to the mobile app module.

[0047] The mobile app module connects to the vehicle communication module via Bluetooth, which in turn connects to the cloud database module via the 4G network. This enables real-time communication, ensuring data sharing between users and the big data platform, and providing accurate fuel consumption predictions. Drivers can use the mobile app to input vehicle type information, departure and destination information as initial information, which is then transmitted to the cloud database module for matching.

[0048] The present invention realizes the fuel consumption estimation of the driving route through the coordinated action of the on-board communication module, the cloud database module and the mobile APP module. The data acquisition part is mainly divided into a software part and a hardware part. The software part is mainly the mobile APP, and the hardware part is mainly the on-board OBD interface. The software can not only display the distance and time from the departure point to the destination, but also remind the driver of the fuel consumption required for each route. This allows the driver to choose a more fuel-efficient route according to his own situation to reduce transportation costs. The interactive interface of the software requires the user to input the model of the vehicle currently being driven, so that the big data platform can obtain the basic parameters of the current vehicle for horizontal comparison. The hardware part mainly obtains the current vehicle's fuel consumption, vehicle speed, mileage and other data through the CAN bus, and then sends it to the on-board communication module through the on-board OBD interface for data transmission.

[0049] Since vehicle load is highly correlated with fuel consumption and difficult to measure directly, the present invention uses tire pressure to estimate vehicle load. Figure 3 This is a schematic diagram of the tire pressure load calculation model of the present invention. Figure 3 Where r1 represents the inner diameter of the tire, see Figure 3 The present invention calculates the truck's cargo capacity using a model based on tire pressure sensors pre-installed in the tires. Truck load estimation primarily measures the change in tire pressure before and after loading to estimate the load mass. Since the temperature change inside the tire before and after loading is negligible, the volume of gas inside the tire decreases and the pressure increases after loading. The ideal gas state equation yields:

[0050] PV=(V-ΔV)(P+ΔP)

[0051]

[0052] The above formula can be used to calculate the tire pressure change ΔP, and the corresponding pressure change can be used to determine the corresponding load mass. Therefore, the tire pressure sensor can be used to determine the load mass of the truck.

[0053] The cloud-based database module first requires building a big data platform in the cloud. The data sources for this big data platform are primarily existing software and websites, as well as trucks using the platform. If the speed curves of similar vehicles are used to estimate the fuel consumption of the vehicle type entered by the driver, the big data platform must estimate the vehicle's speed curve along a specific route. First, after obtaining the driver's input of vehicle type, departure point, and destination, the big data platform determines the route from the departure point to the destination and matches similar data based on vehicle type. The big data platform then uses this matched data to obtain the mode of speed at each location along the route and combine them to create a speed curve for the route. Since the speed curve is solely dependent on the vehicle's driving conditions, different routes have different driving conditions. When a vehicle passes through these conditions, a corresponding speed curve is generated. By crowdsourcing these conditions, speed curves corresponding to different routes can be generated. The vehicle's fuel consumption along the corresponding route is estimated based on the speed curve and the driver's input of vehicle type and other data. The vehicle's instantaneous fuel consumption is determined by the engine's instantaneous power and fuel consumption rate under the vehicle's driving conditions at that moment. First, calculating the instantaneous engine power requires calculating the instantaneous vehicle power. This power is determined by vehicle speed, acceleration, gross vehicle weight, altitude change, and windage parameters—calculated by the energy changes in the vehicle's gross mass, including kinetic energy, gravitational potential energy, and windage losses. Given known parameters such as vehicle transmission efficiency, the instantaneous engine power can be calculated from the vehicle's instantaneous power. Furthermore, different engine models have different universal characteristic diagrams. Knowing the engine speed (vehicle speed) and engine torque (vehicle acceleration) allows the calculation of the fuel consumption rate at that operating point. The vehicle parameters required for these calculations are obtained through a big data platform. Therefore, the speed curve is mapped to the fuel consumption of the corresponding vehicle model. Once the vehicle speed curve is obtained, the estimated fuel consumption can be derived from this correspondence. If the fuel consumption of the same vehicle model is directly used to estimate the fuel consumption of the vehicle model entered by the driver, the final fuel consumption for the same route will vary due to differences in basic truck parameters and cargo capacity. Therefore, the mobile app module's interactive interface is used to obtain basic vehicle parameters. Then, based on these basic vehicle parameters and factors affecting fuel consumption, such as cargo mass, a search is conducted on the big data platform for similar vehicles. The big data platform can capture fuel consumption at every location along the route, allowing drivers to change routes without affecting fuel consumption estimates, minimizing costs. If the big data platform fails to match a specific vehicle, a speed curve is formed by summarizing the speed modes of each point along the route for vehicles of the same type.

[0054] The cloud-based database module includes a decision-making component, which comprehensively analyzes the data provided by the on-board communication module. If a match is found for the fuel consumption data of a vehicle of the same model on the route, the decision-making component calculates the data based on the fuel consumption data obtained from the big data platform and selects the value that appears most frequently. The driver's fuel consumption data for the vehicle model entered is calculated based on the data from the same vehicle on the route. This becomes the estimated fuel consumption for this route under the same conditions, allowing the driver to compare the data. This data is then sent to the on-board communication module and displayed on the mobile app. If a match is not found for the same vehicle model, the estimated fuel consumption is calculated based on the speed curve and basic truck information filtered by the big data platform. Furthermore, the mobile app connects to the cloud-based database module in the event of communication problems with the on-board communication module, ensuring the platform's continued operation. The decision-making component also compares the estimated fuel consumption obtained from the big data platform with the truck's current fuel level, prompting the driver to refuel at an appropriate gas station.

[0055] The present invention provides an energy-saving navigation system for long-distance freight trucks based on big data (a truck energy-saving navigation system based on crowdfunding working conditions), which includes an on-board communication module, a cloud database module, and a mobile APP module. The present invention mainly realizes the fuel consumption estimation function by building a big data platform. Among them, the on-board communication module is mainly responsible for collecting on-board OBD data. It can be connected to the mobile APP module and can remotely interact with the cloud database module. The cloud database module first needs to build a big data platform (cloud database). The main data sources of this big data platform include trucks using the truck energy-saving navigation system based on crowdfunding working conditions of the present invention and various websites. The truck energy-saving navigation system based on crowdfunding working conditions of the present invention can record the speed curve and fuel consumption corresponding to the truck's driving conditions in the process of providing information prompts to the driver, and ensure the rationality and accuracy of the fuel consumption estimation while improving the big database. The cloud database module uses the on-board communication module mounted on the vehicle to collect the truck's attribute information and dynamic information, and uses navigation, intelligent information processing and other technologies to provide truck drivers with route selection, fuel consumption estimation, integrated navigation and other services to achieve energy-saving and safe driving of the truck. The mobile APP module includes an interactive terminal for the driver to input information and a display terminal for displaying the received data.

[0056] The present invention utilizes two methods to work together to estimate fuel consumption and ensure the reliability of the system. Since the speed curve of a vehicle is more closely related to the operating conditions and less closely related to the vehicle parameters. For a fixed route, its operating conditions are determined, so the speed curve of vehicles of the same type traveling on the road under normal circumstances can be estimated. After the driver inputs the vehicle model information, the speed curve corresponds one-to-one with the fuel consumption of the vehicle model. The system crowdfunds the speed of vehicles of the same type at each position on the route, and draws a speed curve based on the speed mode, and can calculate the fuel consumption of the corresponding vehicle on each route through an algorithm. Since the matching of vehicles of the same type only requires a simple distinction between large trucks, medium trucks and small trucks, this method has lower data requirements, but the accuracy of fuel consumption estimation is slightly lacking.

[0057] The truck energy-saving navigation system based on the crowdfunding working condition of the present invention is installed on vehicles of different models traveling on the road. The truck energy-saving navigation system of the present invention collects a large amount of data. After the big data platform collects a large amount of data, it can match the driving data of vehicles of the same model in the big database (cloud database) according to the information such as the model (model), departure place and destination input by the driver. After matching the vehicle, the system calculates the fuel consumption of each route from the departure place to the destination through the big data platform based on the route information. This method must first ensure that the information such as the matched model and the load of the vehicle is consistent with the data input by the driver, and secondly, it must ensure that there is fuel consumption data for each section of the road from the departure place to the destination. Although this method is relatively accurate, it has high requirements for data. Therefore, combining the two methods can better estimate the fuel consumption of the route.

[0058] The embodiment of the present invention obtains vehicle speed curves and route fuel consumption information through a big data platform. The data is authentic and reliable. By analyzing the data, the fuel consumption of each route can be estimated, thereby making effective and reasonable suggestions. This can save the cost of long-distance transportation to the greatest extent and promote the development of long-distance transportation in China.

[0059] Figure 4 Flowchart of the method for realizing energy-saving navigation in crowdfunding working condition provided by the embodiment of the present invention. Figure 4 The present invention provides an embodiment of a method for truck energy-saving navigation, the specific steps of which include:

[0060] A1. Set the connection method for each module. The onboard communication module is connected to the vehicle's OBD interface, through which it can obtain the vehicle's CAN bus data. The mobile app module is connected to the onboard communication module via Bluetooth. The cloud database module is connected to the onboard communication module via the 4G communication network. The cloud database module and the mobile app module have a backup data transmission interface. If the onboard communication module fails, the system can communicate through this backup interface and continue to provide route fuel consumption estimation services.

[0061] A2. Set the information flow. Based on the driver's input, the mobile app module sends information such as vehicle model, departure point, and destination to the vehicle communication module. The vehicle communication module transmits data obtained from the vehicle's OBD interface and the mobile app module to the cloud database module. The cloud database module uses the vehicle model information to search for information such as the vehicle's fuel consumption per 100 kilometers. Based on the departure and destination information, the cloud database module retrieves specific route information, estimated mileage, and estimated travel time from the database.

[0062] A3. Route fuel consumption data screening. After obtaining the truck's basic parameters, the cloud-based database module enters this information into a large database for matching. After determining the route and vehicle type, the database filters the data by setting matching ranges based on parameters such as vehicle load, and records the data for the corresponding route. If no vehicle of the same model is matched, the database immediately matches the data of vehicles of the same type.

[0063] A4. Route fuel consumption estimation. If the cloud database module matches the data of vehicles of the same model, the database will filter and record the data that meets the requirements for the corresponding route, extract the vehicle fuel consumption data, calculate the fuel consumption value of the corresponding route, and use the mode as the estimated fuel consumption required for the truck to travel on the corresponding route. Since there may be multiple routes between the departure and destination, the database repeatedly filters the data according to different routes to obtain the estimated fuel consumption of the truck for all routes. The estimated fuel consumption corresponding to all routes is sent to the mobile APP module through the on-board communication module. The driver can reasonably plan the travel route based on the estimated fuel consumption of each route. If the cloud database module does not match the data of vehicles of the same model, the speed curve formed by the speed mode of each point on the route of the same type of vehicle is summarized, and the fuel consumption value of the vehicle on the corresponding route is calculated based on the speed curve. The estimated fuel consumption of multiple routes can be calculated using the same method.

[0064] A5. Database update and function development. During driving, the cloud database module extracts the truck's fuel consumption, throttle opening, mileage and other information in real time from the on-board communication module to expand the database, while monitoring the truck's fuel consumption and promptly reminding the driver to refuel at the appropriate location. The data during vehicle driving is an important way and source for the cloud database module to obtain data. By extracting these data, the database can clearly know the relationship between the driver's driving behavior and fuel consumption on the road after data analysis. The database can eventually make a detailed analysis of the actual fuel consumption and the estimated fuel consumption, and provide the driver's behavior that increases fuel consumption due to his own poor operation, helping the driver to reasonably plan long-distance driving and objectively promote truck energy saving. Since the data is continuously collected on the line, the present invention can also estimate the fuel consumption data of each section of the road before reaching the destination, so that the driver can have a clear understanding of the sections where his fuel consumption is too high.

[0065] In summary, the essence of the present invention is to provide different driving routes for the driver to choose from once they have determined their starting and ending points. The cloud-based database module then filters and analyzes the database to provide fuel consumption estimates for each route. During driving, the vehicle and the cloud-based database module share data, improving the database while reducing fuel consumption.

[0066] The present invention is based on the current urgent need for a reliable energy-saving navigation with global fuel consumption estimation to guide the driving of trucks, thereby reducing fuel consumption and lowering the cost of long-distance transportation. It provides a truck energy-saving navigation method based on crowdfunding working conditions, and based on the spatiotemporal multi-speed (the mode is the maximum possible value in statistics) map, realizes fuel consumption calculation and route recommendation based on multi-speed travel. The present invention provides a truck with an energy-saving navigation system that can plan routes and estimate route fuel consumption based on the vehicle's own information. When the truck driver is ready to choose a route, the present invention can match the data collected by the big data platform with the vehicle type input by the driver, and reasonably calculate the estimated fuel consumption of each path for the driver to choose. The navigation device can also provide the driver with the fuel consumption required for each section of the route, making it convenient for the driver to change routes and plan refueling locations and times at any time, to a certain extent, ensuring the driver's energy-saving needs and reducing the cost of long-distance transportation. Figure 5 This is a schematic diagram of the interface for realizing crowdfunding energy-saving navigation provided by an embodiment of the present invention, see Figure 5 ,for Figure 5 The navigation device provides the driver with three routes at the starting point and the end point, namely Plan 1, Plan 2 and Plan 3, and reasonably calculates the estimated fuel consumption of each route for the driver to choose.

[0067] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0068] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The above examples are only intended to help understand the method and core concept of the present invention. At the same time, those skilled in the art will find that the specific implementation methods and application scopes may vary based on the concept of the present invention. In summary, the contents of this specification should not be construed as limiting the present invention.

Claims

1. A truck energy-saving navigation system based on crowdfunding working conditions, characterized in that: The system includes an on-board communication module and a cloud database module; The vehicle communication module is used to obtain driving information and truck load; the driving information includes truck model, departure point and destination; The cloud database module is connected to the on-board communication module; the cloud database module is configured to calculate the fuel consumption required for each route between the departure point and the destination based on the matching fuel consumption data when using the cloud database to screen out matching fuel consumption data; the cloud database includes the speed, fuel consumption, and load at each location of different models of vehicles traveling on any section of any route between the departure point and the destination; the matching fuel consumption data is the fuel consumption of the same vehicle at each location on each route between the departure point and the destination; the same vehicle is a vehicle of the same model and load as the truck; The cloud database module is further configured to obtain a matching speed mode based on the matching speed data when the matching fuel consumption data is not filtered out using the cloud database, and obtain speed curves corresponding to different routes between the departure point and the destination based on the matching speed mode, and calculate the required fuel consumption for the route corresponding to the speed curve using the speed curve; the matching speed data is the speed of the same type of vehicle at each position on each route between the departure point and the destination; the same type of vehicle is a vehicle of the same type as a truck; and the matching speed mode is the mode of the speed of the same type of vehicle at each position on each route between the departure point and the destination.

2. The truck energy-saving navigation system based on crowdfunding working conditions according to claim 1 is characterized in that: The system also includes a mobile APP module; The mobile APP module is connected to the vehicle communication module and the cloud database module respectively; The mobile APP module is used to input driving information and obtain the fuel consumption required for each route from the departure point to the destination calculated by the cloud database module through the vehicle communication module; The mobile APP module is also used to send the driving information directly to the cloud database module when the on-board communication module fails, and directly receive the fuel consumption required for each route from the departure point to the destination sent by the cloud database module.

3. The truck energy-saving navigation system based on crowdfunding working conditions according to claim 1 is characterized in that: The vehicle-mounted communication module is connected to the vehicle-mounted OBD interface of the truck; The vehicle communication module is further used to obtain the vehicle OBD data of the current position sent by the vehicle OBD interface in real time; the vehicle OBD data includes truck speed, truck fuel consumption and truck load.

4. The truck energy-saving navigation system based on crowdfunding working conditions according to claim 3 is characterized in that: The cloud database module is further configured to record the vehicle-mounted OBD data sent in real time by the vehicle-mounted communication module, and store the vehicle-mounted OBD data in the cloud database.

5. The truck energy-saving navigation system based on crowdfunding working conditions according to claim 1 is characterized in that: The truck load corresponds to the change in air pressure of the truck tires; the truck load is determined based on the change in air pressure of the truck tires.

6. The truck energy-saving navigation system based on crowdfunding working conditions according to claim 5 is characterized in that: The truck tire pressure change is calculated using the formula PV = (V - ΔV) (P + ΔP) and calculate; Where P is the air pressure of the truck tire, V is the volume of the truck tire, ΔV is the volume change of the truck tire, ΔP is the air pressure change of the truck tire, r2 is the outer diameter of the truck tire, and l is the contact length between the truck tire and the road surface.

7. The truck energy-saving navigation system based on crowdfunding working conditions according to claim 1 is characterized in that: The cloud database module adds up the fuel consumption of the same vehicle at each position on any route between the departure point and the destination to obtain the required fuel consumption for the route between the departure point and the destination.

8. The truck energy-saving navigation system based on crowdfunding working conditions according to claim 1 is characterized in that: The vehicle-mounted communication module is connected to the cloud database module via a 4G communication network.

9. The truck energy-saving navigation system based on crowdfunding working conditions according to claim 2 is characterized in that: The mobile APP module is connected to the vehicle communication module via Bluetooth.

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