CN115472013A - New energy automobile energy management test platform based on virtual traffic scene - Google Patents
New energy automobile energy management test platform based on virtual traffic scene Download PDFInfo
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- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
- G08G1/0125—Traffic data processing
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- G01M—TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
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- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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Abstract
The invention relates to a new energy automobile energy management test platform based on a virtual traffic scene, which is characterized in that: the test platform comprises a current entity, a virtual test scene and a controller platform which is respectively connected with the current entity and the virtual test scene; the driving scene information, the road traffic information and the new energy vehicle technology are deeply fused, the energy management optimization calibration efficiency is greatly improved, and the product competitiveness is favorably improved. In addition, the energy management strategy can be verified in real time by the application of the new energy vehicle energy management test platform, so that the product verification time can be greatly saved, the product development cost can be reduced, and the economic benefit is remarkable.
Description
Technical Field
The invention relates to the technical field of automatic driving control and energy management of new energy vehicles, in particular to a new energy vehicle energy management test platform based on a virtual traffic scene.
Background
With the advancement of an automatic driving system of a new energy vehicle and the deep research of an Energy Management System (EMS), a Global Positioning System (GPS), a Geographic Information System (GIS), an Intelligent Transportation System (ITS) and a communication technology are gradually popularized, and more external information acquisition channels are provided for the new energy vehicle. Particularly, with the continuous development of technologies such as mobile internet and big data platform, the research on the online optimization strategy of automatic driving strategy control and energy management based on technologies such as vehicle-road communication (V2I), vehicle-vehicle communication (V2V) and intelligent sensing has received attention from scholars at home and abroad. In practical application, the effectiveness of an Energy Management Strategy (EMS) is usually verified only after the overall performance of a controller and a whole vehicle is fully tested, complex traffic information coupling exists in an intelligent network automobile under the scene of vehicle-to-vehicle communication (V2I) and vehicle-to-vehicle communication (V2V), and multidimensional input information brings greater challenges for the formulation, test calibration and test work of a new energy management strategy.
The current testing means mainly comprises model in-loop testing, software in-loop testing, hardware in-loop testing, real vehicle field testing and the like. In the hardware loop test, only the tested controller is real hardware, vehicle dynamics, roads, drivers and the like are virtual models, deviation exists between the tested hardware loop test and real vehicle dynamics, road conditions, drivers and the like of automobiles, and the effectiveness of test results is difficult to guarantee. Although real vehicle field testing or road testing is more real, the problems of high time cost, high labor cost, high material cost, low safety, low repeatability of testing environment and the like exist.
Therefore, aiming at the problems of poor safety of real vehicle test, high cost of people, difficult scene repeatability, low test efficiency and the like of the new energy vehicle energy management strategy in the intelligent networking environment, how to deeply fuse the multi-source information of the intelligent networking environment and give consideration to the safety and reliability of vehicle driving, and the construction of the new energy vehicle efficient energy management strategy test platform facing the intelligent networking scene has important significance for the development of the whole vehicle controller.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the new energy automobile energy management controller testing efficiency and safety based on multi-source input information in the intelligent internet traffic scene are improved, the controller testing cost is reduced, and the problem that the control performance of the controller is difficult to evaluate due to the fact that a real traffic scene is difficult to reproduce is solved. Aiming at the technical problem, the invention provides a new energy automobile energy management strategy test platform based on a virtual traffic scene, which associates a new energy real automobile to be tested, the virtual traffic scene and an energy management controller and realizes the test of a whole automobile controller under a virtual reproducible complex traffic scene.
The technical scheme adopted by the invention is as follows:
the utility model provides a new energy automobile energy management test platform based on virtual traffic scene which characterized in that: the test platform comprises a present entity, a virtual test scene and a controller platform which is respectively connected with the present entity and the virtual test scene;
the real body comprises a new energy real vehicle and a rotary drum test bed, and the new energy real vehicle runs on the rotary drum test bed;
the virtual test scene comprises a virtual traffic scene model and a whole vehicle dynamics model, the virtual traffic scene model provides driving scene information and road traffic information, and the whole vehicle dynamics model outputs corresponding vehicle dynamics performance evaluation according to vehicle input information.
As a further preferred embodiment of the invention, the structural composition of the controller platform differs depending on whether the driver is in the loop:
when a driver is in the environment control, the controller platform only comprises a whole vehicle energy management control module, and the tested new energy real vehicle is controlled by the driver;
when no driver is in the control loop, the controller platform comprises an automatic driving control module and an energy management control module, and the measured new energy real vehicle is controlled by the automatic driving control module.
As a further preferred embodiment of the present invention, the virtual traffic scene model provides driving scene information to the actualization body and provides required road traffic information to the energy management control module when there is a driver in-loop control.
As a further preferred embodiment of the present invention, when there is a driver in the loop control, the driver performs corresponding operation on the vehicle according to the driving scene information, and inputs the corresponding operation information into the virtual traffic scene model, the vehicle dynamics model and the energy management control module.
As a further preferred embodiment of the present invention, when there is a driver in the loop control, the energy management control module obtains vehicle state information of the new energy real vehicle to be detected, and forms different power source control signals according to road traffic information obtained from the virtual traffic scene model and corresponding operations performed by the driver on the vehicle, and sends the different power source control signals to the new energy real vehicle.
As a further preferred embodiment of the present invention, the virtual traffic scene model provides driving scene information to the automatic driving control module and provides required road traffic information to the energy management control module when there is no driver in-loop control.
As a further preferred embodiment of the present invention, when there is no driver in-loop control, the automatic driving control module performs corresponding operation on the vehicle according to the driving scenario information and the acquired vehicle state information of the measured new energy real vehicle, and inputs the corresponding operation information into the new energy real vehicle, the entire vehicle dynamics model and the energy management control module, and the corresponding operation information is input into the virtual traffic scenario model through the new energy real vehicle.
As a further preferred embodiment of the present invention, when there is no driver in-loop control, the energy management control module obtains vehicle state information of the new energy real vehicle to be tested, obtains road traffic information from the virtual traffic scene model, and performs corresponding operations on the vehicle by the automatic driving control module, forms different power source control signals, and sends the different power source control signals to the new energy real vehicle.
As a further preferred embodiment of the present invention, the driving scene information at least includes vehicle speed information, vehicle position information, and traffic light signal information around the new energy real vehicle to be detected;
the road traffic information at least comprises traffic flow density information, road section average speed information and road gradient information.
In a further preferred embodiment of the present invention, the operation of the vehicle includes at least an operation of an accelerator pedal opening, a brake pedal opening, and a steering wheel angle of the vehicle.
Compared with the prior art, the invention has the following beneficial effects:
1) The invention provides a new energy automobile energy management test platform based on a virtual traffic scene, which is built, driving scene information, road traffic information and new energy automobile technology are deeply fused, the energy management optimization calibration efficiency is greatly improved, and the product competitiveness is favorably improved. In addition, the energy management strategy can be verified in real time by the application of the new energy vehicle energy management test platform, so that the product verification time can be greatly saved, the product development cost can be reduced, and the economic benefit is remarkable.
2) The invention provides a new energy automobile energy management test platform based on a virtual traffic scene, which improves the test efficiency and safety of a new energy automobile energy management controller based on multi-source input information under an intelligent networking traffic scene, and reduces the test cost of the controller;
3) The invention provides a new energy automobile energy management test platform based on a virtual traffic scene, aiming at the problem that actual traffic behaviors are time-varying and cannot be reproduced, the reproduction of different intelligent network connection traffic scenes can be realized through modeling of behaviors such as the virtual traffic scene and traffic flow, and the problem that the control effect contrast of different energy management strategies is inaccurate due to the fact that the traffic scenes cannot be reproduced in an actual road test is solved;
4) The invention provides a new energy automobile energy management test platform based on a virtual traffic scene. On one hand, the real vehicle to be tested decides the motion of the vehicle according to the surrounding virtual traffic elements by an on-loop driver or a vehicle automatic driving module, on the other hand, the motion behavior of the real vehicle to be tested is fed back to the virtual test scene, the motion of the surrounding vehicle is influenced, the overall traffic flow behavior in the road section is further influenced, particularly the road section traffic flow characteristics under the congestion working condition, and through bidirectional information interaction between the virtual test scene and the current entity, a more accurate evaluation test is provided for the energy management strategy based on the complex traffic scene.
Drawings
FIG. 1 is a logical block diagram of an energy management test platform with driver in-loop management according to the present invention.
FIG. 2 is a logical block diagram of the energy management test platform without driver in loop management according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that the terms "upper", "lower", "inner", "outer", "front", "rear", "both ends", "one end", "the other end", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of description and simplicity of description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it is to be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "disposed," "connected," and the like are to be construed broadly, such as "connected," which may be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in a specific case to those of ordinary skill in the art.
The invention provides a new energy automobile energy management test platform based on a virtual traffic scene, which can realize deep fusion of driving scene information, road traffic information, an automatic driving technology and an energy management strategy and realize new energy real automobile energy management tests under different environments according to the driving requirements of a tested new energy real automobile. The technical solution of the present invention is further explained with reference to the accompanying drawings and specific embodiments.
The invention provides a new energy automobile energy management test platform based on a virtual traffic scene, as shown in fig. 1-2, wherein the test platform comprises a current entity, a virtual test scene and a controller platform respectively connected with the current entity and the virtual test scene;
the reality body comprises a new energy real vehicle and a drum test bed, and the new energy real vehicle runs on the drum test bed;
the virtual test scene comprises a virtual traffic scene model and a whole vehicle dynamics model, the virtual traffic scene model provides driving scene information and road traffic information, and the whole vehicle dynamics model outputs corresponding vehicle dynamics performance evaluation according to vehicle input information.
In this embodiment, as shown in fig. 1-2, the structural composition of the controller platform differs depending on whether the driver is in the loop:
when a driver is in-loop control, the controller platform only comprises a whole vehicle energy management control module, and the tested new energy real vehicle is controlled by the driver; this is a first embodiment of the present invention, as shown in FIG. 1;
when no driver is in the environment control, the controller platform comprises an automatic driving control module and an energy management control module, and the measured new energy real vehicle is controlled by the automatic driving control module; this is a second embodiment of the present invention, as shown in FIG. 2.
The technical solution of the present invention is further described below by a first embodiment and a second embodiment, respectively.
[ first embodiment ]
Fig. 1 shows a first embodiment provided by the present invention, in which when a driver is in the loop control, the driver performs the driving control of the vehicle on the drum test stand without intervention of the automatic driving control module.
The virtual traffic scene model provides driving scene information to a real object through a display or a screen and provides road traffic information to an energy management control module. In the embodiment, the driving scene information at least comprises vehicle speed information, vehicle position information and traffic light signal information around the new energy real vehicle to be detected; the road traffic information at least comprises traffic flow density information, road section average speed information and road gradient information. In this embodiment, traffic scene data collected by a video detector, a floating car, a high-definition satellite map and the like is analyzed, and a virtual traffic scene model can be established by using traffic simulation software such as PRESCAN and VISSIM, wherein the VISSIM is used for simulating overall traffic flow behaviors of vehicles on a selected road section, and the PRESCAN is used for simulating microscopic traffic flow information near the main car and can provide a driving scene of a main car view angle. On the basis of the verification of the modeling precision of the selected traffic scene, a rich test scene library for simulating traffic behaviors under different scenes such as urban working conditions, suburban working conditions, high-speed working conditions and the like is formed by modifying scene parameters.
The method comprises the steps of collecting real target vehicle information, preferably establishing a whole vehicle dynamic model of a target new energy real vehicle on the basis of MATLAB/SIMULINK or Carsim software and the like, and simulating vehicle yaw velocity, roll angle, pitch angle, vertical acceleration and other responses of the vehicle under different accelerator pedal, brake pedal and steering wheel turning angles by adopting the whole vehicle dynamic model carried by PRESCAN software to realize the evaluation of vehicle dynamic performance. The virtual traffic scene model and the whole vehicle dynamics model form a virtual test scene of the test platform.
The energy management control module acquires vehicle state information of the detected new energy real vehicle, road traffic information acquired from the virtual traffic scene model and corresponding operation of a driver on the vehicle form different power source control signals and send the different power source control signals to the new energy real vehicle.
And at the moment, the vehicle input information is correspondingly operated by the driver according to the driving scene information and is input into the whole vehicle dynamics model. In this embodiment, the corresponding operation on the vehicle includes at least operations on an accelerator pedal opening degree, a brake pedal opening degree, and a steering wheel angle of the vehicle.
A driver operates a steering wheel, an accelerator pedal and a brake pedal of a detected vehicle in a current entity according to visual driving scenes such as surrounding vehicles, pedestrians and traffic light signals provided by a virtual traffic scene model, and dynamic performance indexes such as vehicle yaw angle, roll angle, pitch angle and vertical acceleration are evaluated by inputting an accelerator pedal opening degree, a brake pedal opening degree and a steering wheel corner signal into the whole vehicle dynamic model in the virtual testing scene in corresponding driving decisions.
In the embodiment, the controller platform realizes energy management control on the tested real vehicle, namely, control on different power sources is completed according to the type of the tested new energy vehicle. The controller platform can be a whole vehicle controller of the tested real vehicle, or an industrial personal computer, or a rapid prototype controller.
When the controller platform adopts an industrial personal computer or a rapid prototype controller, related control signals of the prototype controller need to be shielded, because the complete vehicle controller of the tested new energy real vehicle can realize the automatic driving function and the energy management strategy of the vehicle. However, some control algorithms are too complex, such as a deep reinforcement learning algorithm, which is difficult to implement on the original vehicle controller, and if a more powerful industrial personal computer or a fast prototype controller is used to replace the original vehicle controller to perform a test of a related algorithm, a control signal of the original vehicle controller and a signal of the industrial personal computer or the fast prototype controller are repeated, so that the signal of the original vehicle controller needs to be shielded, or the signal of the vehicle controller is not sent to each execution mechanism.
The energy management control of the controller platform carries out decision-making of different power source control signals according to vehicle state information such as accelerator pedal opening and brake pedal opening information, vehicle speed, battery state of charge (SOC) and the like operated by a driver and information such as road traffic flow density, road section average vehicle speed, road gradient and the like provided by the virtual traffic scene model, wherein the control signals depend on the type of a detected vehicle. Once the model of the new energy real vehicle to be tested is selected, the control signal output by the energy management control module is correspondingly determined. Preferably, when the tested vehicle is a hybrid vehicle, the energy management control module makes a decision to obtain control signals of the engine, the torques of all motors, the braking torque of the motor and the like; when the vehicle to be tested is a fuel cell vehicle, the energy management control module makes a decision to obtain control signals of the output power of the fuel cell and the battery, the braking torque of the motor and the like; when the tested vehicle is a pure electric vehicle, the energy management control module makes a decision to obtain control signals such as battery output power, driving motor torque, motor braking torque and the like.
[ second embodiment ]
As shown in fig. 2, a second embodiment provided by the present invention is shown, in this embodiment, when there is no driver in-loop control, the new energy real vehicle currently being tested has an autopilot function through the autopilot control module, and the new energy real vehicle can complete longitudinal autopilot facing a complex traffic scene on the drum test bed according to the controller platform without the need of the driver in-loop.
The virtual traffic scene model provides driving scene information to the automatic driving control module and road traffic information to the energy management control module. In this embodiment, the driving scene information at least includes vehicle speed information, vehicle position information, and traffic light signal information around the new energy real vehicle to be detected; the road traffic information at least comprises traffic flow density information, road section average speed information and road gradient information. The traffic scene data collected by the video detector, the floating vehicles, the high-definition satellite map and the like are analyzed, and a virtual traffic scene model can be established by utilizing traffic simulation software such as PRESCAN and VISSIM, wherein the VISCAN is used for simulating the overall traffic flow behavior of the vehicles on a selected road section, and the PRESCAN is used for simulating microscopic traffic flow information near the main vehicle and providing a driving scene of a main vehicle view angle. On the basis of the verification of the modeling precision of the selected traffic scene, a rich test scene library for simulating traffic behaviors under different scenes such as urban working conditions, suburban working conditions, high-speed working conditions and the like is formed by modifying scene parameters.
At the moment, the vehicle input information is subjected to corresponding operations (including but not limited to acceleration, braking, steering and the like) by the automatic driving control module according to the driving scene information and is input into the whole vehicle dynamics model and the energy management control module. The method comprises the steps of collecting real target vehicle information, preferably establishing a target new energy automobile whole vehicle dynamics model based on MATLAB/SIMULINK or Carsim software and the like, and simulating vehicle yaw velocity, roll angle, pitch angle, vertical acceleration and other responses of a vehicle under different accelerator pedal, brake pedal and steering wheel turning angles by adopting a whole vehicle dynamics model carried by PRESCAN software to realize the evaluation of vehicle dynamics performance. The virtual traffic scene model and the whole vehicle dynamics model form a virtual test scene of the test platform.
In this embodiment, the controller platform not only implements automatic driving control on the measured real vehicle, but also implements energy management control on the measured real vehicle, that is, implements control on different power sources according to the type of the measured new energy vehicle. The controller platform can be a whole vehicle controller of the tested real vehicle, or an industrial personal computer, or a rapid prototype controller. The energy management control module acquires vehicle state information of the new energy real vehicle to be detected, road traffic information acquired from the virtual traffic scene model and corresponding operation of the automatic driving control module on the vehicle form different power source control signals and send the different power source control signals to the new energy real vehicle.
An automatic driving control module in a controller platform obtains vehicle state information such as current vehicle speed and yaw velocity and traffic information such as surrounding vehicle speed, position, traffic light signals and pedestrians provided by a virtual traffic scene model, decides to obtain an accelerator pedal opening, a brake pedal opening and a steering wheel corner, the accelerator pedal opening and the brake pedal opening are input to a tested vehicle on a rotary drum test bed to control longitudinal motion of the vehicle, and are input to an energy management control module to provide basis for decision of a power source, and in addition, the decided steering wheel corner is input to a whole vehicle dynamics model in a virtual test scene together with the accelerator pedal opening and the brake pedal opening to evaluate dynamic performance indexes such as vehicle yaw angle, roll angle, pitch angle and vertical acceleration in corresponding driving decision. The energy management control module is used for carrying out decision making on different power source control signals according to the obtained information of the opening degree of an accelerator pedal and the opening degree of a brake pedal, vehicle state information such as vehicle speed and battery state of charge (SOC) and information such as road traffic flow density, road section average speed and road gradient provided by the virtual traffic scene model, wherein the control signals depend on the type of the detected vehicle. Once the model of the new energy real vehicle to be tested is selected, the control signal output by the energy management control module is correspondingly determined. Preferably, when the tested vehicle is a hybrid vehicle, the energy management control module makes a decision to obtain control signals of the engine, the torques of all motors, the braking torque of the motor and the like; when the vehicle to be tested is a fuel cell vehicle, the energy management control module makes a decision to obtain control signals of the output power of the fuel cell and the battery, the braking torque of the motor and the like; when the tested vehicle is a pure electric vehicle, the energy management control module makes a decision to obtain control signals such as battery output power, driving motor torque, motor braking torque and the like.
The speed and steering wheel angle information of the new energy real vehicle to be measured on the rotary drum test bed are simultaneously input into the virtual traffic scene model to control the longitudinal and transverse movement of the virtual main vehicle, so that the movement of surrounding vehicles is influenced, the behavior of the virtual traffic flow is further influenced, and the simulation of the mutual influence characteristic of the main vehicle and the traffic flow behavior is realized through the virtual traffic scene model.
Based on a new energy automobile energy management strategy test platform aiming at automatic driving or a driver-in-the-loop, the real vehicle verification of the new energy automobile energy management strategy facing multi-source information and complex traffic flow behaviors under different traffic scenes can be realized, and an optimal, reliable and effective energy management strategy is obtained. Based on the reproducible advantage of the virtual traffic scene, the difficult problem of strategy evaluation deviation caused by the fact that traffic flow behaviors of the real vehicle under different strategies cannot be completely consistent during the road test can be solved.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (10)
1. The utility model provides a new energy automobile energy management test platform based on virtual traffic scene which characterized in that: the test platform comprises a current entity, a virtual test scene and a controller platform which is respectively connected with the current entity and the virtual test scene;
the real body comprises a new energy real vehicle and a rotary drum test bed, and the new energy real vehicle runs on the rotary drum test bed;
the virtual test scene comprises a virtual traffic scene model and a whole vehicle dynamics model, the virtual traffic scene model provides driving scene information and road traffic information, and the whole vehicle dynamics model outputs corresponding vehicle dynamics performance evaluation according to vehicle input information.
2. The new energy automobile energy management test platform based on the virtual traffic scene as claimed in claim 1, characterized in that: the structural composition of the controller platform differs depending on whether the driver is in the loop:
when a driver is in-loop control, the controller platform only comprises a whole vehicle energy management control module, and the tested new energy real vehicle is controlled by the driver;
when no driver is in the control loop, the controller platform comprises an automatic driving control module and an energy management control module, and the measured new energy real vehicle is controlled by the automatic driving control module.
3. The new energy automobile energy management test platform based on the virtual traffic scene according to claim 2, characterized in that:
when a driver is in the loop control, the virtual traffic scene model provides driving scene information for the real entity and provides required road traffic information for the energy management control module.
4. The new energy automobile energy management test platform based on the virtual traffic scene as claimed in claim 3, characterized in that:
when a driver is in the loop control, the driver correspondingly operates the vehicle according to the driving scene information and inputs the corresponding operation information into the virtual traffic scene model, the whole vehicle dynamics model and the energy management control module.
5. The new energy automobile energy management test platform based on the virtual traffic scene as claimed in claim 4, characterized in that:
when a driver is in the environment control, the energy management control module acquires the vehicle state information of the detected new energy real vehicle, and road traffic information acquired from the virtual traffic scene model and corresponding operation of the driver on the vehicle form different power source control signals and send the different power source control signals to the new energy real vehicle.
6. The new energy automobile energy management test platform based on the virtual traffic scene according to claim 2, characterized in that:
when no driver is in the loop control, the virtual traffic scene model provides driving scene information to the automatic driving control module and provides required road traffic information to the energy management control module.
7. The new energy automobile energy management test platform based on the virtual traffic scene according to claim 6, characterized in that:
when no driver is in the environment control, the automatic driving control module carries out corresponding operation on the vehicle according to the driving scene information and the acquired vehicle state information of the tested new energy real vehicle, inputs the corresponding operation information into the new energy real vehicle, the whole vehicle dynamic model and the energy management control module, and inputs the corresponding operation information into the virtual traffic scene model through the new energy real vehicle.
8. The new energy automobile energy management test platform based on the virtual traffic scene as claimed in claim 7, characterized in that:
when no driver is in the loop control, the energy management control module acquires the vehicle state information of the tested new energy real vehicle, acquires the road traffic information from the virtual traffic scene model and performs corresponding operation on the vehicle by the automatic driving control module to form different power source control signals and send the different power source control signals to the new energy real vehicle.
9. The new energy automobile energy management test platform based on the virtual traffic scene according to any one of claims 1 to 8, wherein:
the driving scene information at least comprises vehicle speed information, vehicle position information and traffic light signal information around the new energy real vehicle to be detected;
the road traffic information at least comprises traffic flow density information, road section average speed information and road gradient information.
10. The new energy automobile energy management test platform based on the virtual traffic scene according to any one of claims 4 or 7, wherein:
the corresponding operation on the vehicle at least comprises the operation on the opening degree of an accelerator pedal, the opening degree of a brake pedal and the steering wheel angle of the vehicle.
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