Commercial vehicle fuel-saving cruise simulation test method, device and equipment and storage medium

Abstract

The invention discloses a commercial vehicle fuel-saving cruise simulation test method, device and equipment and a storage medium. The method comprises the following steps: constructing an environment road model, a vehicle dynamics model and an engine fuel consumption model; in the fuel-saving cruise simulation test process, the current vehicle speed, the current position and the corresponding gradient sequence are obtained; inputting the current vehicle speed, the gradient sequence and preset fixed parameters into an oil-saving cruise control model for processing, and outputting cruise control parameters; the engine driving torque, the target gear, the engine rotating speed change and the engine torque change included in the cruise control parameters are input into an engine fuel consumption model to be processed, and the instantaneous fuel consumption rate is output; inputting the cruise control parameters, the current vehicle speed and the road gradient into the vehicle dynamics model for processing, and outputting the vehicle acceleration; and updating the current vehicle speed and the current position according to the vehicle acceleration, and returning to execute the step of acquiring the gradient sequence. According to the invention, the fuel-saving cruise function of the commercial vehicle is tested through simulation.

Description

Technical Field

[0001] The present invention relates to the field of vehicle testing technology, and in particular to a commercial vehicle fuel-saving cruise simulation test method, device, electronic equipment and storage medium. Background Art

[0002] As a means of transporting goods, commercial vehicles are most concerned about timeliness and fuel consumption. Therefore, it is very necessary to develop a fuel-saving cruise function for commercial vehicles. The fuel-saving cruise function usually takes fuel saving as its main goal, relies on map information input, and performs predictive vehicle speed control based on the characteristics of the terrain ahead.

[0003] Since the fuel-saving cruise function of commercial vehicles requires verification and iteration, its effectiveness needs to be validated. Currently, this can be verified through real-vehicle testing. However, this method is time-consuming and resource-intensive, requiring the accumulation of extensive mileage data to obtain fuel-saving rate values, hindering algorithm development, optimization, and commercialization. Therefore, a new commercial vehicle fuel-saving cruise testing method is urgently needed. Summary of the Invention

[0004] The present invention provides a commercial vehicle fuel-saving cruise simulation test method, device, electronic equipment and storage medium.

[0005] According to one aspect of the present invention, a commercial vehicle fuel-saving cruise simulation test method is provided, comprising:

[0006] Construct an environmental road model, a vehicle dynamics model that reflects the characteristics of real commercial vehicles, and an engine fuel consumption model;

[0007] During the fuel-saving cruise simulation test, the current vehicle speed and current position are obtained, and the current position and the slope sequence of the preset distance ahead of the current position are obtained from the environmental road model;

[0008] Inputting the current vehicle speed, slope sequence, and preset fixed parameters into a fuel-saving cruise control model for processing and outputting cruise control parameters; wherein the cruise control parameters include engine driving torque, braking deceleration, and target gear position;

[0009] The cruise control parameters, including engine driving torque, target gear, and calculated engine speed change, engine torque change, and current vehicle speed, are input into the engine fuel consumption model for processing, and the instantaneous fuel consumption rate is output;

[0010] The cruise control parameters, current vehicle speed, road slope at current location, and vehicle weight are input into the vehicle dynamics model for processing, and the vehicle acceleration at the next moment is output;

[0011] The current vehicle speed and the current position are updated according to the vehicle acceleration at the next moment, and the step of obtaining the current position and the slope sequence of the preset distance ahead of the current position from the environmental road model is returned to be executed.

[0012] According to another aspect of the present invention, a commercial vehicle fuel-saving cruise simulation test device is provided, comprising:

[0013] Model building module, used to build environmental road models, vehicle dynamics models reflecting the characteristics of real commercial vehicles, and engine fuel consumption models;

[0014] A data acquisition module is used to obtain the current vehicle speed and current position during the fuel-saving cruise simulation test, and to obtain the current position and the slope sequence of a preset distance ahead of the current position from the environmental road model;

[0015] A cruise control module, configured to input the current vehicle speed, slope sequence, and preset fixed parameters into a fuel-saving cruise control model for processing and output cruise control parameters; wherein the cruise control parameters include engine drive torque, brake deceleration, and target gear position;

[0016] The fuel consumption calculation module is used to input cruise control parameters including engine driving torque, target gear, and calculated engine speed change, engine torque change, and current vehicle speed into the engine fuel consumption model for processing and output instantaneous fuel consumption rate;

[0017] The acceleration calculation module is used to input the cruise control parameters, current vehicle speed, road slope at the current location, and vehicle weight into the vehicle dynamics model for processing and output the vehicle acceleration at the next moment;

[0018] The updating module is used to update the current vehicle speed and current position according to the vehicle acceleration at the next moment, and return to execute the step of obtaining the current position and the slope sequence of the preset distance ahead of the current position from the environmental road model.

[0019] According to another aspect of the present invention, an electronic device is provided, comprising:

[0020] at least one processor; and

[0021] a memory communicatively connected to the at least one processor; wherein,

[0022] The memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can perform the commercial vehicle fuel-saving cruise simulation test method according to an embodiment of the present invention.

[0023] According to another aspect of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the commercial vehicle fuel-saving cruise simulation test method according to an embodiment of the present invention when executed.

[0024] The technical solution of the embodiment of the present invention achieves the effect of testing the fuel-saving cruise function of a commercial vehicle through simulation.

[0025] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of 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 creative work.

[0027] Figure 1 1 is a flow chart of a commercial vehicle fuel-saving cruise simulation test method provided according to an embodiment of the present invention;

[0028] Figure 2 1 is a flow chart of a commercial vehicle fuel-saving cruise simulation test method provided according to an embodiment of the present invention;

[0029] Figure 3 2 is a schematic structural diagram of a commercial vehicle fuel-saving cruise simulation test device provided according to an embodiment of the present invention;

[0030] Figure 4 The present invention is a schematic structural diagram of an electronic device for implementing a commercial vehicle fuel-saving cruise simulation test method according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described 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 should fall within the scope of protection of the present invention.

[0032] Example 1

[0033] Figure 1A flowchart of a commercial vehicle fuel-saving cruise simulation test method is provided for an embodiment of the present invention. This embodiment is applicable to scenarios for testing the fuel-saving cruise effect of commercial vehicles. The method can be executed by a commercial vehicle fuel-saving cruise simulation test device. The commercial vehicle fuel-saving cruise simulation test device can be implemented in the form of hardware and / or software. The commercial vehicle fuel-saving cruise simulation test device can be configured in an electronic device, such as a server device.

[0034] like Figure 1 As shown, the commercial vehicle fuel-saving cruise simulation test method includes:

[0035] S101. Construct an environmental road model, a vehicle dynamics model that reflects the characteristics of a real commercial vehicle, and an engine fuel consumption model.

[0036] In an embodiment of the present invention, constructing an environmental road model includes obtaining map slope information and operating condition information on a real commercial vehicle operating route, and constructing the environmental road model based on the map slope information and operating condition information. The environmental road model thus constructed can truly represent the commercial vehicle operating route.

[0037] In an embodiment of the present invention, a vehicle dynamics model that reflects the characteristics of a real commercial vehicle is constructed, including: first, constructing a first neural network model to be trained; wherein the input of the first neural network model includes the vehicle weight, engine drive torque, transmission gear, brake deceleration, vehicle speed, and road slope; the output of the first neural network is vehicle acceleration; and the hidden layer of the first neural network is set to include 13 neurons according to the Kolmogorov theorem. On the basis of determining the model structure, the training samples can be constructed as follows: specifically: the vehicle weight, engine driving torque, transmission gear, braking deceleration, vehicle speed, and road slope are used as factors of the orthogonal experiment; wherein, factors refer to the variables that affect the control of commercial vehicles that need to be examined in the orthogonal experiment, and the number of levels of each factor is M, where M is a preset constant; for each factor, M levels are uniformly taken within the value range of the factor; wherein level refers to the value of the factor; illustratively, each factor uniformly takes 9 levels within its value range, for example, vehicle weight, covering the range from no load to full load, is divided into 9 levels according to a 10% load gradient; vehicle speed, covering 0-maximum speed, takes 9 levels at equal speed intervals (such as 0, 10, 20...80 km / h); according to the number of factors and the number of levels, select the corresponding orthogonal table; for example, the number of factors n=6, the number of levels M=9, and the orthogonal table L is selected. 81 (9 6); wherein, the orthogonal table is a table constructed by the mathematical orthogonal Latin square theory, which is a tool for orthogonal test design and has orthogonality (the number of different numbers in each column appears the same number of times, and the permutations and combinations of numbers in any two columns are complete and uniform); multiple test cases are generated according to the orthogonal table; wherein, each test case is composed of different levels of different factors; it can be understood that the orthogonal table ensures that each level of each factor appears the same number of times in the test through mathematical arrangement, and the level combinations between factors are evenly distributed to avoid data bias. Furthermore, for any test case, the real commercial vehicle is controlled to run according to the test case, and the vehicle acceleration of the real commercial vehicle is collected, and the test case and vehicle acceleration are used as a training sample; for example, a test case is set as: "vehicle weight 5 tons, drive torque 300N·m, 3rd gear, braking deceleration 0.5m / s 2 , speed 40km / h, slope 2%, "When the commercial vehicle operates according to these parameters, the vehicle acceleration output of the commercial vehicle is recorded; each set of test cases can be repeated 1-2 times to ensure data reliability, and finally the six factors (input parameters) in the test case and the vehicle acceleration (output) are used as a training sample. Through the above method, a large number of training samples can be generated, some of which can be used as training sets and some as test sets; based on the constructed training samples (such as samples in the training set), the first neural network model to be trained is trained using a preset model training method (such as the LM optimization algorithm), and tested using samples in the test set, ultimately obtaining a vehicle dynamics model that conforms to the characteristics of the actual vehicle.

[0038] In an embodiment of the present invention, an engine fuel consumption model that reflects the characteristics of a real commercial vehicle is constructed, including: constructing a second neural network model to be trained; wherein the inputs of the second neural network model include engine driving torque, transmission gear, vehicle speed, engine speed change, and engine driving torque change; the output of the second neural network model is the instantaneous fuel consumption rate; and the hidden layer of the neural network is set to include 11 neurons according to the Kolmogorov theorem. Engine driving torque, transmission gear, vehicle speed, engine speed change, and engine driving torque change are used as factors (input parameters) of the orthogonal experiment; wherein the number of levels of each factor is M, where M is a preset constant; for each factor, M levels are uniformly taken within the factor's value range; specifically, each factor takes 9 levels within its physical range. For example, for driving torque, it covers 0-100% from idle to maximum torque, divided into 9 levels with an 11.1% gradient. Based on the number of factors and levels, a corresponding orthogonal table is selected; multiple test cases are generated based on the orthogonal table; each test case is composed of different levels of different factors; for any test case, a real commercial vehicle is controlled to operate according to the test case, and the instantaneous fuel consumption rate of the real commercial vehicle is collected, and the test case and the instantaneous fuel consumption rate are used as a training sample; for example, the test case is "drive torque 400N·m, 5th gear, vehicle speed 60km / h, speed change +200rpm, torque change +50N·m". When a real commercial vehicle operates according to this parameter combination, the instantaneous fuel consumption data of the real commercial vehicle is recorded; for each set of experiments, the corresponding relationship between the five input parameters and the instantaneous fuel consumption rate (output) is recorded to construct a training sample. Through the above method, a large number of training samples can be generated, some of which can be used as training sets and some as test sets; based on the training samples (e.g., samples in the training set), the second neural network model to be trained is trained using a preset model training method (e.g., LM optimization algorithm), and tested using samples in the test set, ultimately obtaining an engine fuel consumption model that conforms to the characteristics of the real vehicle.

[0039] It can be understood that according to the vehicle's motion state, the engine fuel consumption model can be divided into an idle fuel consumption model and a non-idle (driving) fuel consumption model. The idle fuel consumption model directly obtains the idle instantaneous fuel consumption rate through actual vehicle testing; while the non-idle fuel consumption model can be constructed in the above manner, that is, the neural network-based engine fuel consumption model constructed above is a non-idle fuel consumption model.

[0040] After constructing the environmental road model, the vehicle dynamics model reflecting the characteristics of a real commercial vehicle, and the engine fuel consumption model in the above manner, these three models can be loaded into the simulation environment and the fuel-saving cruise simulation test can be carried out according to the subsequent steps.

[0041] S102 . During the fuel-saving cruise simulation test, obtain the current vehicle speed and the current position, and obtain the current position and a slope sequence at a preset distance ahead of the current position from the environmental road model.

[0042] In this embodiment of the present invention, at the start of a fuel-efficient cruise simulation test, the current vehicle speed can be a pre-set initial speed, and the current position is a pre-set starting position. During the fuel-efficient cruise simulation test, the current vehicle speed is the instantaneous speed calculated based on vehicle acceleration, and the current position refers to the position of the vehicle dynamics model within the environmental road model at that moment. After obtaining the current position, the current position and the slope sequence at a pre-set distance ahead of the current position can be obtained from the environmental road model.

[0043] S103: Input the current vehicle speed, slope sequence and preset fixed parameters into the fuel-saving cruise control model for processing, and output cruise control parameters.

[0044] In the experimental embodiment of the present invention, the fuel-efficient cruise control model refers to a functional module that implements fuel-efficient cruise control for commercial vehicles. The preset fixed parameters are relatively fixed parameters set externally during the simulation test process, including the target cruise speed, vehicle parameters (including vehicle weight, transmission gear / ratio setting, final drive ratio, transmission efficiency, wheel radius, drag coefficient, etc.), and road resistance coefficient. Optionally, the fixed parameters can be manually set.

[0045] In this embodiment of the present invention, the current vehicle speed, current location, and the slope sequence at a preset distance ahead of the current location require continuous updating during the fuel-efficient cruise control process. Therefore, these two parameters can be defined as dynamic parameters. Furthermore, because the slope sequence is transmitted from the environmental road model to the fuel-efficient cruise control model, a signal processing module that communicates with the control module is pre-defined to facilitate information transfer. This module implements data adaptation to ensure that the transmitted information meets the input requirements of the fuel-efficient cruise control model.

[0046] In the embodiment of the present invention, the cruise control parameters include engine driving torque, braking deceleration, and target gear.

[0047] S104: Input the cruise control parameters including the engine driving torque, the target gear, and the calculated engine speed change, engine torque change, and current vehicle speed into the engine fuel consumption model for processing, and output the instantaneous fuel consumption rate.

[0048] In an embodiment of the present invention, the engine speed change can be determined based on the engine speed at the current moment and the engine speed at the previous moment; the engine torque change can be determined based on the engine torque at the current moment and the engine torque at the previous moment; and then the engine speed change, engine torque change, current vehicle speed, and cruise control parameters including engine drive torque and target gear are input into the engine fuel consumption model for processing, and the instantaneous fuel consumption rate is output.

[0049] S105: Input the cruise control parameters, the current vehicle speed, the road at the current location, the weight and slope of the vehicle into the vehicle dynamics model for processing, and output the vehicle acceleration at the next moment.

[0050] Optionally, cruise control parameters, including engine torque, braking deceleration, target gear, current vehicle speed, road slope, and vehicle weight, are input into a vehicle dynamics model for processing, outputting the vehicle acceleration at the next moment. This transmission process can be mediated by a signal processing module communicating with the control module.

[0051] S106: Update the current vehicle speed and current position according to the vehicle acceleration at the next moment, and return to the step of obtaining the current position and the slope sequence of the preset distance ahead of the current position from the environmental road model.

[0052] According to step S105, the vehicle acceleration at the next moment is obtained, and the latest vehicle speed and vehicle position can be calculated based on the vehicle acceleration, thereby updating the current vehicle speed and current position; then, based on the updated current speed and current position, steps S102-S106 are continued until the fuel-saving cruise simulation test is completed.

[0053] The embodiment of the present invention realizes the testing of the fuel-saving cruise function of a commercial vehicle through simulation, and establishes a vehicle dynamics model and an engine fuel consumption model that simulate the characteristics of the actual vehicle through a neural network, which can better reflect the fuel consumption results and improve the simulation effect.

[0054] Example 2

[0055] Figure 2 The present invention provides a flowchart of a commercial vehicle fuel-saving cruise simulation test method. Figure 2 ,The commercial vehicle fuel-saving cruise simulation test method includes the following steps:

[0056] S201. Construct an environmental road model, a vehicle dynamics model reflecting the characteristics of a real commercial vehicle, and an engine fuel consumption model.

[0057] S202 . During the fuel-saving cruise simulation test, obtain the current vehicle speed and the current position, and obtain the current position and a slope sequence at a preset distance ahead of the current position from the environmental road model.

[0058] S203: Input the current vehicle speed, slope sequence, and preset fixed parameters into the fuel-saving cruise control model for processing, and output cruise control parameters, wherein the cruise control parameters include engine driving torque, braking deceleration, and target gear.

[0059] S204: Input the cruise control parameters including the engine driving torque, the target gear, and the calculated engine speed change, engine torque change, and current vehicle speed into the engine fuel consumption model for processing, and output the instantaneous fuel consumption rate.

[0060] S205: Input the cruise control parameters, the current vehicle speed, the road slope at the current position, and the vehicle weight into the vehicle dynamics model for processing, and output the vehicle acceleration at the next moment.

[0061] S206: Update the current vehicle speed and current position according to the vehicle acceleration at the next moment, and return to the step of obtaining the current position and the slope sequence of the preset distance ahead of the current position from the environmental road model.

[0062] In the embodiment of the present invention, the specific implementation of steps S201-S206 can refer to the description of the above embodiment and will not be repeated here.

[0063] S207. Evaluate the performance of the fuel-saving cruise control model based on the fuel-saving cruise simulation test results.

[0064] Optionally, after the fuel-saving cruise simulation test is completed, the cumulative fuel consumption in the fuel-saving cruise state is calculated based on the multiple instantaneous fuel consumption rates obtained, and the cumulative fuel consumption is used as an evaluation indicator for the fuel-saving cruise control model. Specifically, the cumulative fuel consumption can be calculated based on the vehicle movement during the simulation and the instantaneous fuel filter.

[0065] After the fuel-saving cruise simulation test, the comfort level during the fuel-saving cruise state is determined based on the vehicle acceleration and jerk obtained. Comfort is then used as an evaluation metric for the fuel-saving cruise control model. Specifically, the vehicle acceleration and jerk at each moment during the fuel-saving cruise simulation test are calculated and weighted together to obtain a weighted result at each moment. The mean of these weighted results is then calculated; the smaller the mean, the higher the comfort level.

[0066] The timeliness of fuel-efficient cruise control is determined based on the deviation between the real-time speed and the set cruising speed, as well as the average speed during the simulation. This timeliness is then used as an evaluation metric for the fuel-efficient cruise control model. Specifically, the sum of squares of the deviation between the real-time speed and the set cruising speed is calculated, and this sum of squares represents the degree of consistency with the set cruising speed. Additionally, the average speed during the simulation is calculated; a higher value indicates better timeliness.

[0067] The safety of the fuel-saving cruise control model is determined based on vehicle motion under different operating conditions, wherein the operating conditions include at least one of a long downhill slope, a steep downhill slope, a long uphill slope, frequent driver override, and frequent cruise speed switching. For example, in long and steep downhill slopes, the maximum vehicle speed of the vehicle dynamics model under the condition is calculated based on vehicle acceleration. A determination is made as to whether the maximum speed exceeds the vehicle system's upper speed limit and whether overspeed instability will occur. The timely and reasonable braking in this scenario is also determined. In long uphill slopes, the vehicle system's ability to balance power and economy is tested, and whether the pursuit of economy results in excessively low speeds. This is determined, for example, by determining whether the average speed under the condition is below a preset speed threshold. In frequent driver overrides, the rationality of the interaction between the vehicle system and the driver is tested, and whether there is any interference with the driver's normal driving that could affect vehicle safety. In frequent target cruise speed switching, the system's responsiveness and stability to changing operating conditions are tested, and whether drastic changes in the target speed may lead to unsafe rapid acceleration or deceleration.

[0068] The above evaluation results can be output and scored separately to measure the performance of the system under test, so that algorithm developers can understand the advantages and disadvantages of this software.

[0069] In the embodiment of the present invention, in addition to evaluating the fuel-saving cruise control model based on fuel consumption, the model is also evaluated based on indicators such as comfort, timeliness, and safety, thereby achieving a comprehensive evaluation of the fuel-saving cruise control model.

[0070] Example 3

[0071] Figure 3 The present invention provides a schematic diagram of a commercial vehicle fuel-saving cruise simulation test device. Figure 3 , the commercial vehicle fuel-saving cruise simulation test device includes:

[0072] Model building module 301, used to build an environmental road model, a vehicle dynamics model reflecting the characteristics of a real commercial vehicle, and an engine fuel consumption model;

[0073] The data acquisition module 302 is used to obtain the current vehicle speed and current position during the fuel-saving cruise simulation test, and obtain the current position and the slope sequence of a preset distance ahead of the current position from the environmental road model;

[0074] The cruise control module 303 is configured to input the current vehicle speed, slope sequence, and preset fixed parameters into the fuel-saving cruise control model for processing and output cruise control parameters; wherein the cruise control parameters include engine driving torque, braking deceleration, and target gear position;

[0075] The fuel consumption calculation module 304 is used to input the cruise control parameters including the engine driving torque, the target gear, and the calculated engine speed change, engine torque change, and current vehicle speed into the engine fuel consumption model for processing and output the instantaneous fuel consumption rate;

[0076] The acceleration calculation module 305 is used to input the cruise control parameters, current vehicle speed, road slope at current location, and vehicle weight into the vehicle dynamics model for processing and output the vehicle acceleration at the next moment;

[0077] The updating module 306 is configured to update the current vehicle speed and the current position according to the vehicle acceleration at the next moment, and return to the step of obtaining the current position and the slope sequence of the preset distance ahead of the current position from the environmental road model.

[0078] In some embodiments, in constructing a vehicle dynamics model that reflects the characteristics of a real commercial vehicle, the model construction module 301 is specifically used to:

[0079] Constructing a first neural network model to be trained; wherein the input of the first neural network model includes the vehicle weight, engine drive torque, transmission gear, brake deceleration, vehicle speed, and road slope; and the output of the first neural network is vehicle acceleration;

[0080] The vehicle weight, engine driving torque, transmission gear, braking deceleration, vehicle speed, and road slope are used as factors in the orthogonal experiment; the number of levels of each factor is M, where M is a preset constant;

[0081] For each factor, M levels are uniformly selected within the value range of the factor;

[0082] Select the corresponding orthogonal array according to the number of factors and levels; generate multiple test cases based on the orthogonal array; each test case is composed of different levels of different factors;

[0083] For any test case, control a real commercial vehicle to run according to the test case and collect the vehicle acceleration of the real commercial vehicle. The test case and vehicle acceleration are used as a training sample.

[0084] Based on the training samples, the first neural network model to be trained is trained through a preset model training method to obtain a vehicle dynamics model that conforms to the characteristics of the actual vehicle.

[0085] In some embodiments, in constructing an engine fuel consumption model that reflects the characteristics of a real commercial vehicle, the model construction module 301 is specifically used to:

[0086] Constructing a second neural network model to be trained; wherein the input of the second neural network model includes engine driving torque, transmission gear, vehicle speed, engine speed change, and engine driving torque change; and the output of the second neural network model is instantaneous fuel consumption rate;

[0087] The engine driving torque, transmission gear, vehicle speed, engine speed change, and engine driving torque change are used as factors in the orthogonal experiment; wherein the number of levels of each factor is M, where M is a preset constant;

[0088] For each factor, M levels are uniformly selected within the value range of the factor;

[0089] Select the corresponding orthogonal array according to the number of factors and levels; generate multiple test cases based on the orthogonal array; each test case is composed of different levels of different factors;

[0090] For any test case, control a real commercial vehicle to operate according to the test case and collect the instantaneous fuel consumption rate of the real commercial vehicle. The test case and the instantaneous fuel consumption rate are used as a training sample.

[0091] Based on the training samples, the second neural network model to be trained is trained through a preset model training method to obtain an engine fuel consumption model that conforms to the characteristics of the actual vehicle.

[0092] In some embodiments, in terms of constructing the environmental road model, the model construction module 301 is specifically used to:

[0093] Obtain map slope information and working condition information on real commercial vehicle operation routes, and build an environmental road model based on the map slope information and working condition information.

[0094] In some embodiments, including:

[0095] The first evaluation module is used to calculate the cumulative fuel consumption in the fuel-saving cruise state according to the multiple instantaneous fuel consumption rates obtained after the fuel-saving cruise simulation test is completed, and use the cumulative fuel consumption as an evaluation indicator of the fuel-saving cruise control model.

[0096] In some embodiments, further comprising:

[0097] The second evaluation module is used to determine the comfort of the fuel-saving cruise state based on the obtained vehicle acceleration and jerk after the fuel-saving cruise simulation test is completed, and use the comfort as an evaluation indicator of the fuel-saving cruise control model;

[0098] The third evaluation module is used to determine the timeliness of fuel-saving cruise control based on the deviation between the real-time vehicle speed and the set cruising speed and the average vehicle speed during the simulation process, and use the timeliness as an evaluation indicator of the fuel-saving cruise control model.

[0099] In some embodiments, further comprising:

[0100] The fourth evaluation module is used to determine the safety of the fuel-saving cruise control model based on the vehicle's motion under different operating conditions; wherein the operating conditions include long downhill slopes, steep downhill slopes, long uphill slopes, frequent driver takeovers, and frequent changes in cruise speed.

[0101] The commercial vehicle fuel-saving cruise simulation test device provided by the embodiment of the present invention can execute the commercial vehicle fuel-saving cruise simulation test method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0102] Example 4

[0103] Figure 4 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0104] like Figure 4 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0105] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0106] Processor 11 can be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any other suitable processor, controller, microcontroller, etc. Processor 11 executes the various methods and processes described above, such as executing the commercial vehicle fuel-efficient cruise simulation test method.

[0107] In some embodiments, the commercial vehicle fuel-saving cruise simulation test method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the commercial vehicle fuel-saving cruise simulation test method described above can be performed. Alternatively, in other embodiments, the processor 11 can be configured to execute the commercial vehicle fuel-saving cruise simulation test method in any other appropriate manner (for example, by means of firmware).

[0108] Various embodiments of the systems and techniques described above can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system that includes at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0109] Computer programs for implementing the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable commercial vehicle fuel-efficient cruise simulation test device, such that when executed by the processor, the computer programs implement the functions / operations specified in the flowcharts and / or block diagrams. The computer programs can be executed entirely on the machine, partially on the machine, as a standalone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0110] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0111] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0112] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0113] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0114] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0115] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A commercial vehicle fuel-saving cruise simulation test method, characterized in that: include: Construct an environmental road model, a vehicle dynamics model that reflects the characteristics of real commercial vehicles, and an engine fuel consumption model; During the fuel-saving cruise simulation test, the current vehicle speed and the current position are obtained, and the current position and a slope sequence at a preset distance ahead of the current position are obtained from the environmental road model; Inputting the current vehicle speed, the slope sequence, and preset fixed parameters into a fuel-saving cruise control model for processing, and outputting cruise control parameters; wherein the cruise control parameters include engine driving torque, braking deceleration, and target gear position; Inputting the cruise control parameters, including the engine driving torque, the target gear, and the calculated engine speed change, engine torque change, and current vehicle speed, into the engine fuel consumption model for processing and outputting an instantaneous fuel consumption rate; Inputting the cruise control parameter, the current vehicle speed, the road slope at the current position, and the vehicle weight into the vehicle dynamics model for processing, and outputting the vehicle acceleration at the next moment; The current vehicle speed and the current position are updated according to the vehicle acceleration at the next moment, and the step of obtaining the current position and the slope sequence at a preset distance ahead of the current position from the environmental road model is returned to be executed.

2. The method according to claim 1, characterized in that Build a vehicle dynamics model that reflects the characteristics of real commercial vehicles, including: Constructing a first neural network model to be trained; wherein the input of the first neural network model includes vehicle weight, engine drive torque, transmission gear, brake deceleration, vehicle speed, and road slope; and the output of the first neural network is vehicle acceleration; The vehicle weight, engine driving torque, transmission gear, braking deceleration, vehicle speed, and road slope are used as factors in the orthogonal test; wherein the number of levels of each factor is M, where M is a preset constant; For each factor, M levels are uniformly selected within the value range of the factor; Select the corresponding orthogonal array according to the number of factors and levels; generate multiple test cases based on the orthogonal array; each test case is composed of different levels of different factors; For any test case, controlling a real commercial vehicle to operate according to the test case, collecting the vehicle acceleration of the real commercial vehicle, and using the test case and the vehicle acceleration as a training sample; Based on the training samples, the first neural network model to be trained is trained through a preset model training method to obtain a vehicle dynamics model that conforms to the characteristics of the actual vehicle.

3. The method according to claim 1, characterized in that Build an engine fuel consumption model that reflects the characteristics of real commercial vehicles, including: Constructing a second neural network model to be trained; wherein the input of the second neural network model includes engine driving torque, transmission gear, vehicle speed, engine speed change, and engine driving torque change; and the output of the second neural network model is instantaneous fuel consumption rate; The engine driving torque, transmission gear, vehicle speed, engine speed change, and engine driving torque change are used as factors of the orthogonal test; wherein the number of levels of each factor is M, where M is a preset constant; For each factor, M levels are uniformly selected within the value range of the factor; Select the corresponding orthogonal array according to the number of factors and levels; generate multiple test cases based on the orthogonal array; each test case is composed of different levels of different factors; For any test case, controlling a real commercial vehicle to operate according to the test case, collecting the instantaneous fuel consumption rate of the real commercial vehicle, and using the test case and the instantaneous fuel consumption rate as a training sample; Based on the training samples, the second neural network model to be trained is trained through a preset model training method to obtain an engine fuel consumption model that conforms to the characteristics of the actual vehicle.

4. The method according to claim 1, wherein Building an environmental road model includes: Obtain map slope information and operating condition information on a real commercial vehicle operating route, and construct an environmental road model based on the map slope information and the operating condition information.

5. The method according to claim 1, wherein Also includes: After the fuel-saving cruise simulation test is completed, the cumulative fuel consumption in the fuel-saving cruise state is calculated based on the obtained multiple instantaneous fuel consumption rates, and the cumulative fuel consumption is used as an evaluation indicator of the fuel-saving cruise control model.

6. The method according to claim 1, characterized in that Also includes: After the fuel-saving cruise simulation test is completed, the comfort of the fuel-saving cruise state is determined based on the obtained vehicle acceleration and jerk, and the comfort is used as an evaluation index of the fuel-saving cruise control model; The timeliness of the fuel-saving cruise is determined according to the deviation between the real-time vehicle speed and the set cruising speed and the average vehicle speed during the simulation, and the timeliness is used as an evaluation index of the fuel-saving cruise control model.

7. The method according to claim 1, characterized in that Also includes: The safety of the fuel-saving cruise control model is determined based on the vehicle's motion under different operating conditions, including long downhill slopes, steep downhill slopes, long uphill slopes, frequent driver takeovers, and frequent switching of cruise speeds.

8. A commercial vehicle fuel-saving cruise simulation test device, characterized in that: include: Model building module, used to build environmental road models, vehicle dynamics models reflecting the characteristics of real commercial vehicles, and engine fuel consumption models; a data acquisition module, configured to acquire the current vehicle speed and current position during the fuel-saving cruise simulation test, and to acquire the current position and a slope sequence at a preset distance ahead of the current position from the environmental road model; a cruise control module, configured to input the current vehicle speed, the slope sequence, and preset fixed parameters into a fuel-saving cruise control model for processing, and output cruise control parameters; wherein the cruise control parameters include engine driving torque, braking deceleration, and target gear; a fuel consumption calculation module, configured to input the cruise control parameters, including the engine driving torque, the target gear, and the calculated engine speed change, the engine torque change, and the current vehicle speed, into the engine fuel consumption model for processing and output an instantaneous fuel consumption rate; an acceleration calculation module, configured to input the cruise control parameters, the current vehicle speed, the road slope at the current position, and the vehicle weight into the vehicle dynamics model for processing, and output the vehicle acceleration at the next moment; An updating module is used to update the current vehicle speed and the current position according to the vehicle acceleration at the next moment, and return to execute the step of obtaining the current position and the slope sequence of a preset distance ahead of the current position from the environmental road model.

9. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method according to any one of claims 1 to 7 when executed.

Images