New energy vehicle braking particulate matter emission control method, device, equipment and medium

Abstract

The application relates to a new energy vehicle braking particulate emission control method, device, equipment and medium, which comprises the following steps: predicting a braking event of a new energy vehicle in a current driving cycle according to navigation or memory travel or intelligent driving road coordination data; determining a braking energy distribution weight of the target new energy vehicle according to an actual vehicle weight, a current battery residual capacity and a current motor state; determining recoverable electric braking energy and mechanical braking energy of the target new energy vehicle according to the actual total braking energy and the braking energy distribution weight; calculating and determining the braking wear degree of the target new energy vehicle corresponding to the braking event; determining the actual emission amount of braking particulate matter corresponding to the braking event according to the braking wear; and feeding back the emission reduction effect of the current driving to the driver according to the predicted emission amount and the actual emission amount of the braking particulate matter. The application makes the braking particulate emission control strategy more suitable for real driving conditions, and realizes energy saving and environmental protection collaborative optimization.

Description

Technical Field

[0001] This application relates to the field of new energy vehicles, and in particular to a method for controlling particulate matter emissions from braking in new energy vehicles, a corresponding device, electronic equipment, and a computer-readable storage medium. Background Technology

[0002] With the rapid popularization of new energy vehicles and the continuous improvement of vehicle intelligence, non-exhaust emissions have become a key focus of vehicle pollutant control.

[0003] In the era of traditional gasoline-powered vehicles, the industry primarily focused on controlling engine exhaust emissions, with relatively limited research on non-exhaust emissions such as brake wear and tire wear. After exhaust emissions were effectively controlled, particulate matter generated by brake wear has become one of the main sources of non-exhaust particulate matter emissions from roads. It contains a large number of metal microparticles and ultrafine particles, significantly impacting the atmospheric environment and human health. With the advancement of regulations, brake particulate matter emissions have been included in mandatory control, with clear testing methods and emission limits set for light-duty vehicles.

[0004] Current methods for controlling brake particulate matter emissions mainly include the following technical approaches: First, reducing wear rates by improving brake pad and disc materials or structures, but this significantly increases the cost of the braking system; second, adding brake particulate matter capture, filtration, and suction devices, which requires occupying space around the wheels and increasing air and pipeline structures, limiting their practical application; and third, relying on the brake energy recovery system of new energy vehicles to reduce the use of mechanical braking, but existing energy recovery strategies only focus on energy recovery efficiency and braking safety, without actively optimizing based on the mechanism of brake particulate matter generation, and cannot achieve emission prediction and source reduction from the perspective of intelligent vehicle control.

[0005] In summary, existing technologies for controlling brake particulate emissions reduce wear rates by improving brake pad and disc materials or structures, but this significantly increases the cost of the braking system. Furthermore, existing energy recovery strategies only focus on energy recovery efficiency and braking safety, without actively optimizing based on the mechanism of brake particulate generation, and cannot achieve emission prediction and source reduction from the perspective of vehicle intelligent control. The applicant has made corresponding explorations to address these issues. Summary of the Invention

[0006] The purpose of this application is to solve the above-mentioned problems by providing a method, device, electronic equipment and computer-readable storage medium for controlling particulate matter emissions from braking of new energy vehicles.

[0007] To achieve the various objectives of this application, the following technical solution is adopted:

[0008] A method for controlling particulate matter emissions from braking in new energy vehicles, proposed to meet one of the purposes of this application, includes:

[0009] The target new energy vehicle acquires vehicle-road cooperative data and vehicle status data in the target route, and predicts each braking event of the target new energy vehicle in the target route and its corresponding braking data based on the vehicle-road cooperative data.

[0010] In each actual braking event, the actual total braking energy corresponding to the target new energy vehicle is calculated and determined; based on the instantaneous longitudinal deceleration, wheel-end instantaneous total braking force, and current vehicle speed in the vehicle state data, the actual vehicle weight of the target new energy vehicle is calculated and determined; based on the actual vehicle weight, current remaining battery power, and current motor status, the braking energy allocation weight of the target new energy vehicle in the corresponding braking event is determined; based on the actual total braking energy and according to the braking energy allocation weight, the recyclable electric braking energy and mechanical braking energy of the target new energy vehicle are determined.

[0011] In each predicted braking event, the predicted emission of braking particulate matter for the braking event is calculated and determined based on the vehicle speed, the target vehicle speed in the braking data, the average deceleration, and the vehicle weight correction coefficient related to the actual vehicle weight, combined with the braking energy distribution weight of the mechanical braking.

[0012] Based on the mechanical braking energy, braking contact surface state, braking contact surface temperature, and braking dynamics parameters, the braking wear depth of the target new energy vehicle in the corresponding braking event is calculated and determined, and the actual emission amount of braking particulate matter in the corresponding braking event is determined based on the braking wear depth.

[0013] Based on the predicted and actual emissions of braking particulate matter corresponding to each braking event, the total predicted and actual emissions of braking particulate matter along the target route are determined. The total predicted and actual emissions are then uploaded to a cloud server to provide feedback to the driver on the emission reduction effect of this driving experience, thereby completing the prediction of braking particulate matter emissions from new energy vehicles.

[0014] Optionally, the vehicle status data includes instantaneous longitudinal deceleration, instantaneous total braking force at the wheel ends, current vehicle speed, current remaining battery power, and current motor status;

[0015] The braking data includes the target vehicle speed and average deceleration for each braking event;

[0016] The vehicle-road cooperative data includes road traffic signals, traffic flow data, and roadside perception information.

[0017] Optionally, the step of calculating and determining the actual weight of the target new energy vehicle based on the instantaneous longitudinal deceleration, the instantaneous total braking force at the wheel ends, and the current vehicle speed in the vehicle state data includes:

[0018] In each actual braking event, the instantaneous total braking force at the wheel ends, air density, drag coefficient, vehicle frontal area, current vehicle speed, and instantaneous longitudinal deceleration of the target new energy vehicle are obtained.

[0019] The air resistance of the target new energy vehicle during the corresponding braking event is calculated and determined based on the air density, the drag coefficient, the vehicle's frontal area, and the current vehicle speed.

[0020] The first difference between the instantaneous total braking force at the wheel end and the air resistance is calculated and determined to determine the effective braking force of the target new energy vehicle in the corresponding braking event.

[0021] Calculate the first product between the gravitational acceleration and the rolling resistance coefficient to determine the equivalent deceleration corresponding to the rolling resistance, and calculate the first sum between the instantaneous longitudinal deceleration and the equivalent deceleration to determine the total equivalent deceleration of the target new energy vehicle in the corresponding braking event.

[0022] A first ratio between the effective braking force of the target new energy vehicle and the total equivalent deceleration is calculated to determine the actual vehicle weight of the target new energy vehicle in the corresponding braking event.

[0023] Optionally, the step of calculating and determining the actual total braking energy corresponding to the target new energy vehicle includes:

[0024] In each actual braking event, the actual vehicle weight, current vehicle speed, and target vehicle speed of the target new energy vehicle at the corresponding braking event are obtained;

[0025] Calculate and determine a third difference between the first squared value of the current vehicle speed and the second squared value of the target vehicle speed;

[0026] The fifth product of half the determined value, the actual vehicle weight, and the third difference is calculated to determine the actual total braking energy of the target new energy vehicle in the corresponding braking event.

[0027] Optionally, the steps of determining the braking energy allocation weight of the target new energy vehicle in the corresponding braking event based on the actual vehicle weight, the current remaining battery charge, and the current motor status, and determining the recoverable electric braking energy and mechanical braking energy of the target new energy vehicle according to the actual total braking energy and the braking energy allocation weight, include:

[0028] Obtain the actual vehicle weight, current remaining battery power, and current motor status of the target new energy vehicle at the corresponding braking event;

[0029] The braking load level of the target new energy vehicle is determined based on the actual vehicle weight, the battery rechargeable capacity threshold of the target new energy vehicle is determined based on the current remaining battery power, and the maximum regenerative braking power of the target new energy vehicle is determined based on the current motor status.

[0030] The upper limit of the motor braking capacity is determined based on the battery rechargeable capacity threshold and the maximum regenerative braking power of the motor, and the braking energy distribution weights of motor braking and mechanical braking are determined based on the braking load level.

[0031] Based on the braking energy allocation weight, the actual total braking energy of the target new energy vehicle in the corresponding braking event is divided into recoverable motor braking energy and mechanical braking energy that needs to be dissipated.

[0032] Optionally, in each predicted braking event, the step of calculating and determining the predicted emission of braking particulate matter for the braking event, based on the vehicle speed, the target vehicle speed in the braking data, the average deceleration, and the vehicle weight correction factor related to the actual vehicle weight, combined with the braking energy distribution weight of the mechanical braking, includes:

[0033] In each predicted braking event, the current vehicle speed, target vehicle speed, average deceleration, and vehicle weight correction coefficient related to the actual vehicle weight of the target new energy vehicle are obtained. The vehicle weight correction coefficient related to the actual vehicle weight is determined by the braking energy distribution weight of mechanical braking.

[0034] A second difference between the current vehicle speed and the target vehicle speed is calculated and determined, and a second ratio between the second difference and the average deceleration of the target new energy vehicle is calculated and determined, so as to determine the braking speed change rate of the target new energy vehicle in the corresponding braking event;

[0035] The second product between the first calibration coefficient and the current vehicle speed is calculated and determined, and the third product between the second calibration coefficient and the square of the current vehicle speed is calculated and determined. Based on the second sum of the calibration constant term, the second product, and the third product, the basic emission factor of the target new energy vehicle in the corresponding braking event is determined.

[0036] The fourth product between the vehicle weight correction factor, the braking speed change rate, and the basic emission factor is calculated to determine the predicted braking particulate matter emissions of the target new energy vehicle in the corresponding braking event.

[0037] Optionally, the step of calculating and determining the brake wear depth of the target new energy vehicle in the corresponding braking event based on the mechanical braking energy, brake contact surface state, brake contact surface temperature, and braking dynamic parameters, and determining the actual emission amount of brake particulate matter in the corresponding braking event based on the brake wear depth, includes:

[0038] In each actual braking event, the mechanical braking energy, braking contact surface state, braking contact surface temperature, and braking dynamic parameters of the target new energy vehicle are acquired.

[0039] Based on the mechanical braking energy, determine the braking contact load and relative braking slip speed between the brake pads and the brake disc during the braking event;

[0040] Based on the state of the braking contact surface, the temperature of the braking contact surface, and the braking dynamics parameters, determine the material property parameters and contact stiffness parameters of the braking contact surface;

[0041] The braking wear depth of the target new energy vehicle in the corresponding braking event is calculated and determined based on the contact load, the relative braking speed, the material property parameters, and the contact stiffness parameters.

[0042] Based on the brake wear depth, the actual amount of brake particulate matter emitted by the target new energy vehicle during the corresponding braking event is determined.

[0043] A new energy vehicle braking particulate emission control device provided for another purpose of this application includes:

[0044] The braking event prediction module is configured to acquire vehicle-road cooperative data and vehicle status data in the target route for the target new energy vehicle, and predict each braking event of the target new energy vehicle in the target route and its corresponding braking data based on the vehicle-road cooperative data.

[0045] The total braking energy distribution module is configured to calculate and determine the actual total braking energy of the target new energy vehicle in each actual braking event; calculate and determine the actual vehicle weight of the target new energy vehicle based on the instantaneous longitudinal deceleration, instantaneous total braking force at the wheel ends, and current vehicle speed in the vehicle status data; determine the braking energy distribution weight of the target new energy vehicle in the corresponding braking event based on the actual vehicle weight, the current remaining battery charge, and the current motor status; and determine the recyclable electric braking energy and mechanical braking energy of the target new energy vehicle according to the actual total braking energy and the braking energy distribution weight.

[0046] The predicted emission determination module is configured to calculate and determine the predicted emission of braking particulate matter for each predicted braking event based on the vehicle speed, the target vehicle speed in the braking data, the average deceleration, and the vehicle weight correction coefficient related to the actual vehicle weight, combined with the braking energy distribution weight of the mechanical braking.

[0047] The actual emission determination module is configured to calculate and determine the brake wear depth of the target new energy vehicle in the corresponding braking event based on the mechanical braking energy, brake contact surface state, brake contact surface temperature and braking dynamic parameters, and determine the actual emission of brake particulate matter in the corresponding braking event based on the brake wear depth.

[0048] The emission reduction effect feedback module is configured to determine the total predicted emission and total actual emission of braking particulate matter along the target route based on the predicted and actual emission of braking particulate matter corresponding to each braking event, and upload the total predicted emission and total actual emission to the cloud server to provide feedback to the driver on the emission reduction effect of this driving, thereby completing the prediction of braking particulate matter emissions from new energy vehicles.

[0049] An electronic device provided for another purpose of this application includes a central processing unit and a memory, wherein the central processing unit is used to invoke and run a computer program stored in the memory to perform the steps of the new energy vehicle braking particulate matter emission control method of this application.

[0050] A computer-readable storage medium is provided for another purpose of this application, which stores, in the form of computer-readable instructions, a computer program implemented according to the new energy vehicle braking particulate matter emission control method, which, when called by a computer, executes the steps included in the corresponding method.

[0051] Compared to existing technologies, this application addresses several issues in existing technologies. Firstly, while improving brake pad and disc materials or structures reduces wear rates, it significantly increases braking system costs. Secondly, existing energy recovery strategies focus solely on energy recovery efficiency and braking safety, failing to proactively optimize based on the mechanism of brake particulate matter generation, thus failing to achieve emission prediction and source reduction at the vehicle intelligent control level. This application offers, but is not limited to, the following beneficial effects:

[0052] Firstly, existing technologies mostly employ post-treatment methods such as improving braking materials, adding collection devices, and passively adsorbing particulate matter. These methods can only collect particulate matter after it is generated and cannot suppress emissions at the source. This application, however, uses vehicle-road cooperative data, navigation information, and ADAS perception to predict all braking events and braking intensity within the target route in advance. It completes emission prediction, energy allocation planning, and braking strategy optimization before braking occurs, upgrading the traditional "passive response braking" to an intelligent management and control mode of "active prediction, active allocation, and active control," truly achieving a reduction in particulate matter generation at the source.

[0053] Secondly, this application does not require replacement of the brake friction pair, nor does it require the addition of any dust collection, filtration, or suction devices. It does not alter the hardware structure, increase costs, or affect the overall vehicle layout. It can be directly installed in existing new energy vehicles and assisted driving vehicles, and has strong versatility and scalability.

[0054] Third, this application utilizes real-time vehicle conditions such as instantaneous longitudinal deceleration, total braking force at the wheel end, and current vehicle speed, and deducts the influence of wind resistance and rolling resistance to accurately calculate the actual vehicle weight. This provides a real load basis for braking energy distribution, braking wear calculation, and particulate matter emission calculation, significantly improving the consistency between the predicted and actual emissions of braking particulate matter, and making the braking particulate matter emission control strategy more in line with real driving conditions.

[0055] Fourth, this application uses actual vehicle weight, remaining battery charge, and maximum regenerative braking power of the motor as constraints to dynamically determine the allocation weight of motor braking and mechanical braking. While ensuring safety, it aims to maximize the proportion of motor braking and minimize the intervention of mechanical friction braking, fundamentally reducing friction and wear between brake pads and brake discs. This improves energy recovery rate and significantly reduces... , Reduce particulate matter emissions and achieve synergistic optimization of energy conservation and environmental protection.

[0056] Fifth, this application uses mechanical braking energy, braking contact surface state, contact surface temperature, and braking dynamic parameters as inputs to calculate braking wear depth, and directly maps the wear depth to obtain the actual particulate matter emission amount, which is highly consistent with the braking friction and wear mechanism and can more realistically and accurately reflect the generation law of particulate matter under different working conditions.

[0057] Furthermore, this application, while controlling the mechanical braking intervention ratio, dynamically adjusts the normal force according to the temperature of the braking contact surface to avoid friction coefficient decay, increased wear, and a surge in particulate matter caused by continuous high temperature in the braking system. Under the premise of ensuring braking safety, braking smoothness, and suppressing thermal fade, it minimizes braking particulate matter emissions, solving the problem that existing technologies cannot balance safety, performance, and environmental protection. Attached Figure Description

[0058] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0059] Figure 1 This is a flowchart illustrating the method for controlling particulate matter emissions from the braking system of new energy vehicles in this application.

[0060] Figure 2 This is an exemplary framework diagram of the new energy vehicle braking particulate matter emission control method in the embodiments of this application;

[0061] Figure 3 This is a schematic block diagram of the new energy vehicle braking particulate matter emission control device in the embodiments of this application;

[0062] Figure 4 This is a schematic diagram of the structure of the computer device in the embodiments of this application. Detailed Implementation

[0063] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0064] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this application means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof. It should be understood that when we say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or wireless coupling. The term “and / or” as used herein includes all or any units and all combinations of one or more associated listed items.

[0065] Those skilled in the art will understand that, unless otherwise defined, all terms used herein (including technical and scientific terms) have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains. It should also be understood that terms such as those defined in general dictionaries should be understood to have the same meaning as in the context of the prior art, and should not be interpreted in an idealized or overly formal sense unless specifically defined as herein.

[0066] Those skilled in the art will understand that the terms "client," "terminal," and "terminal device" as used herein include both devices that receive wireless signals, devices that only possess wireless signal receiver capabilities without transmission capabilities, and devices with receiving and transmitting hardware, devices that have receiving and transmitting hardware capable of bidirectional communication over a bidirectional communication link. Such devices may include: cellular or other communication devices such as personal computers or tablets, having single-line displays, multi-line displays, or cellular or other communication devices without multi-line displays; PCS (Personal Communications Service) that can combine voice, data processing, fax, and / or data communication capabilities; PDAs (Personal Digital Assistants) that may include radio frequency receivers, pagers, internet / intranet access, web browsers, notebooks, calendars, and / or GPS (Global Positioning System) receivers; and conventional laptops and / or handheld computers or other devices that have and / or include radio frequency receivers. As used herein, "client," "terminal," and "terminal device" can be portable, transportable, installed in a means of transportation (air, sea, and / or land), or suitable and / or configured to operate locally and / or in a distributed manner, operating in any other location on Earth and / or in space. "Client," "terminal," and "terminal device" as used herein can also be a communication terminal, an internet access terminal, or a music / video playback terminal, such as a PDA, a MID (Mobile Internet Device), and / or a mobile phone with music / video playback capabilities, or a smart TV, set-top box, etc.

[0067] The hardware referred to by the names "server," "client," and "service node" in this application is essentially an electronic device with the equivalent capabilities of a personal computer. It is a hardware device with the necessary components revealed by the von Neumann architecture, such as a central processing unit (including an arithmetic logic unit and a control unit), memory, input devices, and output devices. The computer program is stored in its memory, and the central processing unit loads the program stored in the secondary storage into the main memory to run it, execute the instructions in the program, and interact with the input and output devices to complete specific functions.

[0068] It should be noted that the concept of "server" used in this application can also be extended to the case of server clusters. Based on the network deployment principles understood by those skilled in the art, the servers should be logically divided. Physically, these servers can be independent of each other but accessible through interfaces, or they can be integrated into a single physical computer or a computer cluster. Those skilled in the art should understand this flexibility and should not use it to constrain the implementation of the network deployment method in this application.

[0069] One or more of the technical features of this application, unless explicitly specified herein, can be deployed on a server and accessed by a client remotely calling the online service interface provided by the server, or can be directly deployed and run on a client for access.

[0070] Unless otherwise specified, the neural network models referenced or potentially referenced in this application may be deployed on a remote server and invoked remotely on the client, or deployed on a client with the capability to invoke directly. In some embodiments, when running on the client, the corresponding intelligence may be acquired through transfer learning in order to reduce the requirements on the client's hardware resources and avoid excessive consumption of the client's hardware resources.

[0071] Unless otherwise specified, all data involved in this application may be stored remotely on a server or on a local terminal device, as long as it is suitable for use by the technical solution of this application.

[0072] Those skilled in the art will understand that although the various methods in this application are described based on the same concept and thus present commonality among them, they can be performed independently unless otherwise specified. Similarly, the various embodiments disclosed in this application are all based on the same inventive concept; therefore, concepts expressed in the same way, as well as concepts that are appropriately changed for convenience but are expressed differently, should be understood equivalently.

[0073] Unless otherwise expressly stated, the various embodiments disclosed in this application can be combined in a cross-cutting manner to flexibly construct new embodiments, as long as such combination does not depart from the inventive spirit of this application and can meet the needs of the prior art or solve a certain deficiency in the prior art. Those skilled in the art should be aware of such modifications.

[0074] Please see Figure 1 In one embodiment of the new energy vehicle braking particulate matter emission control method of this application, the method includes:

[0075] Step S10: The target new energy vehicle acquires vehicle-road cooperative data and vehicle status data in the target route, and predicts each braking event of the target new energy vehicle in the target route and its corresponding braking data based on the vehicle-road cooperative data.

[0076] The terminal equipment in the target new energy vehicle can acquire vehicle-road cooperative data and vehicle status data along the target route, and predict each braking event of the target new energy vehicle along the target route and its corresponding braking data based on the vehicle-road cooperative data; wherein, the vehicle status data includes instantaneous longitudinal deceleration, instantaneous total braking force at the wheel ends, current vehicle speed, current remaining battery charge (SOC), and current motor status; the braking data includes the target vehicle speed and average deceleration for each braking event; the vehicle-road cooperative data includes road traffic signals, traffic flow data, and roadside perception information; the braking particulate matter includes , Particulate matter.

[0077] Specifically, when the driver gets into the vehicle and powers it on, the vehicle's power system is activated, and the initial collection of vehicle status data (current vehicle speed, current battery charge (SOC), current motor status, etc.) is completed.

[0078] By activating navigation, Advanced Driver Assistance Systems (ADAS), or trip memory functions, vehicle-to-infrastructure (V2I) data for the target route is acquired, including environmental data such as road traffic signals, real-time road conditions, road gradient, and speed limits. Combining V2I data with vehicle status data, the system predicts the entire route's travel dynamics parameters (vehicle speed, deceleration) and identifies all braking events: After setting the destination, based on the road traffic conditions along the entire route, the system predicts the vehicle speed and deceleration for each segment and identifies braking events along the entire route; based on historical travel data, it predicts the vehicle's travel dynamics for future travel intervals (e.g., 2 to 5 minutes) and identifies braking events within those intervals; and it dynamically calculates the vehicle's travel dynamics parameters in real time based on the road traffic environment, identifying current and upcoming braking events in real time.

[0079] For each predicted braking event, the corresponding braking data is output, including the target vehicle speed (final braking speed) and average deceleration, providing input for subsequent calculations of actual vehicle weight and predicted emissions.

[0080] Step S20: In each actual braking event, calculate and determine the actual total braking energy corresponding to the target new energy vehicle; calculate and determine the actual vehicle weight of the target new energy vehicle based on the instantaneous longitudinal deceleration, instantaneous total braking force at the wheel ends, and current vehicle speed in the vehicle state data; determine the braking energy allocation weight of the target new energy vehicle in the corresponding braking event based on the actual vehicle weight, the current remaining battery charge, and the current motor state; determine the recyclable electric braking energy and mechanical braking energy of the target new energy vehicle according to the actual total braking energy and the braking energy allocation weight.

[0081] The target new energy vehicle acquires vehicle-road cooperative data and vehicle status data along the target route. Based on the vehicle-road cooperative data, it predicts each braking event and its corresponding braking data along the target route. In each actual braking event, it calculates and determines the actual total braking energy of the target new energy vehicle. Based on the instantaneous longitudinal deceleration, instantaneous total braking force at the wheel ends, and current vehicle speed in the vehicle status data, it calculates and determines the actual vehicle weight of the target new energy vehicle. Based on the actual vehicle weight, the current remaining battery charge, and the current motor status, it determines the braking energy allocation weight for the target new energy vehicle in the corresponding braking event. Based on the actual total braking energy and according to the braking energy allocation weight, it determines the recoverable electric braking energy and mechanical braking energy of the target new energy vehicle.

[0082] In some embodiments, the step of calculating and determining the actual total braking energy corresponding to the target new energy vehicle includes:

[0083] Step S31: In each actual braking event, obtain the actual vehicle weight, current vehicle speed, and target vehicle speed of the target new energy vehicle in the corresponding braking event;

[0084] Step S32: Calculate and determine the third difference between the first squared value of the current vehicle speed and the second squared value of the target vehicle speed;

[0085] Step S33: Calculate the fifth product between half of the determined value, the actual vehicle weight, and the third difference, to determine the actual total braking energy of the target new energy vehicle in the corresponding braking event.

[0086] Specifically, the formula for calculating the actual total braking energy of the target new energy vehicle in the corresponding braking event is expressed as follows:

[0087]

[0088] in, This represents the actual total braking energy of the target new energy vehicle during the corresponding braking event; This indicates the actual weight of the target new energy vehicle at the corresponding braking event; This indicates the current vehicle speed (initial braking speed) of the target new energy vehicle. This indicates the target vehicle speed (final braking speed) of the target new energy vehicle at the corresponding braking event.

[0089] In some embodiments, the step of calculating and determining the actual weight of the target new energy vehicle based on the instantaneous longitudinal deceleration, the instantaneous total braking force at the wheel ends, and the current vehicle speed in the vehicle state data includes:

[0090] Step S301: In each actual braking event, obtain the instantaneous total braking force at the wheel end of the target new energy vehicle, air density, drag coefficient, vehicle frontal area, current vehicle speed, and instantaneous longitudinal deceleration.

[0091] Step S302: Calculate and determine the air resistance of the target new energy vehicle in the corresponding braking event based on the air density, the drag coefficient, the vehicle frontal area, and the current vehicle speed.

[0092] Step S303: Calculate and determine the first difference between the instantaneous total braking force at the wheel end and the air resistance, so as to determine the effective braking force of the target new energy vehicle in the corresponding braking event;

[0093] Step S304: Calculate and determine the first product between the gravitational acceleration and the rolling resistance coefficient to determine the equivalent deceleration corresponding to the rolling resistance; calculate the first sum between the instantaneous longitudinal deceleration and the equivalent deceleration to determine the total equivalent deceleration of the target new energy vehicle in the corresponding braking event.

[0094] Step S305: Calculate and determine the first ratio between the effective braking force of the target new energy vehicle and the total equivalent deceleration, so as to determine the actual vehicle weight of the target new energy vehicle in the corresponding braking event.

[0095] Specifically, the formula for calculating the actual vehicle weight of the target new energy vehicle during the corresponding braking event is as follows:

[0096]

[0097] in, This indicates the actual weight of the target new energy vehicle at the corresponding braking event; This indicates the instantaneous total braking force at the wheel ends of the target new energy vehicle; Indicates air density; This represents the drag coefficient of the target new energy vehicle; This indicates the frontal area of ​​the target new energy vehicle. This indicates the current speed of the target new energy vehicle, which is also the instantaneous speed of the vehicle at the moment of braking; This represents the instantaneous longitudinal deceleration of the target new energy vehicle; Represents gravitational acceleration; This represents the rolling resistance coefficient, which is the resistance coefficient generated by the friction between the tire and the road surface. This represents the total equivalent deceleration of the target new energy vehicle during the corresponding braking event.

[0098] In a further embodiment, the step of determining the braking energy allocation weight of the target new energy vehicle in the corresponding braking event based on the actual vehicle weight, the current remaining battery charge, and the current motor status, and determining the recoverable electric braking energy and mechanical braking energy of the target new energy vehicle according to the actual total braking energy and the braking energy allocation weight, includes:

[0099] Step S3001: Obtain the actual vehicle weight, current remaining battery power, and current motor status of the target new energy vehicle at the corresponding braking event;

[0100] Step S3002: Determine the braking load level of the target new energy vehicle based on the actual vehicle weight, determine the battery rechargeable capacity threshold of the target new energy vehicle based on the current remaining battery power, and determine the maximum regenerative braking power of the target new energy vehicle based on the current motor status.

[0101] The greater the actual vehicle weight of the target new energy vehicle in the corresponding braking event, the higher the total braking energy and the higher the braking load level (for example, divided into three levels: light load, medium load, and heavy load). The load is dynamically divided based on the real-time vehicle weight, replacing the traditional fixed load assumption, so that the distribution ratio is more in line with the actual working conditions of the vehicle, avoiding the problems of insufficient motor braking under heavy load and waste of mechanical braking under light load.

[0102] The higher the current remaining battery charge (SOC) of the target new energy vehicle, the smaller the remaining charging space and the lower the rechargeable capacity threshold; the lower the current remaining battery charge (SOC) of the target new energy vehicle, the higher the rechargeable capacity threshold. Limiting the maximum proportion of motor braking from the battery side ensures battery safety while maximizing the use of charging space and achieving maximum recycling efficiency.

[0103] When the motor temperature is too high, the speed is out of range, or there is a fault, the maximum regenerative braking power of the motor will be automatically reduced; under normal operating conditions, the maximum regenerative braking power of the motor will be used; the motor braking safety will be protected from the motor hardware side to avoid overload damage, while ensuring the regenerative braking efficiency under normal operating conditions.

[0104] Step S3003: Determine the upper limit of motor braking capability based on the battery rechargeable capacity threshold and the maximum regenerative braking power of the motor, and determine the braking energy distribution weights of motor braking and mechanical braking respectively in conjunction with the braking load level;

[0105] Step S3004: According to the braking energy allocation weight, the actual total braking energy of the target new energy vehicle in the corresponding braking event is divided into recoverable motor braking energy and mechanical braking energy that needs to be dissipated.

[0106] The minimum value between the battery rechargeable capacity threshold and the maximum regenerative braking power of the motor can be used as the absolute upper limit of motor braking, simultaneously satisfying both battery safety and motor hardware safety. This dual constraint provides a safety net, avoiding safety risks caused by the failure of a single constraint and defining a safe boundary for the allocation ratio. Within the upper limit of motor braking, the weight is dynamically adjusted according to the braking load level. When the corresponding braking event is at a light load level, the braking energy allocation weight of motor braking is maximized (100%), with no mechanical braking. When the corresponding braking event is at a medium load level, the braking energy allocation weight of motor braking is 80%, and the braking energy allocation weight of mechanical braking is 20%. When the corresponding braking event is at a heavy load level, the braking energy allocation weight of motor braking is 60%, and the braking energy allocation weight of mechanical braking is 40% (ensuring braking safety). Under the premise of safety, maximizing the proportion of motor braking and minimizing the proportion of mechanical braking reduces braking friction and wear at the source, directly reducing the actual emission of braking particulate matter.

[0107] Step S30: In each predicted braking event, the predicted emission of braking particulate matter for the braking event is calculated and determined based on the vehicle speed, the target vehicle speed in the braking data, the average deceleration, and the vehicle weight correction coefficient related to the actual vehicle weight, combined with the braking energy distribution weight of the mechanical braking.

[0108] In each actual braking event, the actual total braking energy corresponding to the target new energy vehicle is calculated and determined; based on the instantaneous longitudinal deceleration, wheel-end instantaneous total braking force, and current vehicle speed in the vehicle state data, the actual vehicle weight of the target new energy vehicle is calculated and determined; based on the actual vehicle weight, current remaining battery charge, and current motor status, the braking energy allocation weight of the target new energy vehicle in the corresponding braking event is determined; after determining the recyclable electric braking energy and mechanical braking energy of the target new energy vehicle according to the actual total braking energy and the braking energy allocation weight, in each predicted braking event, based on the vehicle speed, the target vehicle speed in the braking data, the average deceleration, and the vehicle weight correction coefficient related to the actual vehicle weight, combined with the braking energy allocation weight of mechanical braking, the predicted emission of braking particulate matter in the braking event is calculated and determined.

[0109] In some embodiments, the step of calculating and determining the predicted emissions of braking particulate matter for each predicted braking event, based on the vehicle speed, the target vehicle speed in the braking data, the average deceleration, and the vehicle weight correction factor related to the actual vehicle weight, combined with the braking energy distribution weight of the mechanical braking, includes:

[0110] Step S301: In each predicted braking event, obtain the current vehicle speed, target vehicle speed, average deceleration, and vehicle weight correction coefficient related to the actual vehicle weight of the target new energy vehicle, wherein the vehicle weight correction coefficient related to the actual vehicle weight is determined by the braking energy distribution weight of mechanical braking.

[0111] Step S302: Calculate and determine a second difference between the current vehicle speed and the target vehicle speed, and calculate and determine a second ratio between the second difference and the average deceleration of the target new energy vehicle, so as to determine the braking speed change rate of the target new energy vehicle in the corresponding braking event;

[0112] Step S303: Calculate and determine the second product between the first calibration coefficient and the current vehicle speed, calculate and determine the third product between the second calibration coefficient and the square of the current vehicle speed, and determine the basic emission factor of the target new energy vehicle in the corresponding braking event based on the second sum of the calibration constant term, the second product and the third product.

[0113] Step S304: Calculate and determine the fourth product between the vehicle weight correction coefficient, the braking speed change rate, and the basic emission factor to determine the predicted braking particulate matter emissions of the target new energy vehicle in the corresponding braking event.

[0114] Specifically, the formula for calculating the predicted braking particulate matter emissions of the target new energy vehicle during the corresponding braking event is expressed as follows:

[0115]

[0116] in, This indicates the predicted emissions of braking particulate matter from the target new energy vehicle during the corresponding braking event.

[0117] The vehicle weight correction coefficient is related to the actual weight of the target new energy vehicle. The vehicle weight correction coefficient related to the actual vehicle weight is determined by the braking energy distribution weight of the mechanical brake. It can be determined by a preset mapping relationship or a linear fitting method based on the correspondence between the actual total mass of the vehicle and the braking energy distribution weight of the mechanical brake. This indicates the current vehicle speed (initial braking speed) of the target new energy vehicle. This indicates the target vehicle speed (final braking speed) of the target new energy vehicle at the corresponding braking event. This represents the average deceleration of the target new energy vehicle during the corresponding braking event; Indicates the calibration constant term; Indicates the first calibration coefficient; This represents the second calibration coefficient.

[0118] Step S40: Calculate and determine the brake wear depth of the target new energy vehicle in the corresponding braking event based on the mechanical braking energy, brake contact surface state, brake contact surface temperature and braking dynamic parameters, and determine the actual emission amount of brake particulate matter in the corresponding braking event based on the brake wear depth.

[0119] In each predicted braking event, based on the vehicle speed, the target vehicle speed in the braking data, the average deceleration, and the vehicle weight correction coefficient related to the actual vehicle weight, combined with the braking energy distribution weight of the mechanical braking, the predicted emission amount of braking particulate matter for the braking event is calculated and determined. Then, based on the mechanical braking energy, the braking contact surface state, the braking contact surface temperature, and the braking dynamics parameters, the braking wear depth of the target new energy vehicle in the corresponding braking event is calculated and determined. Based on the braking wear depth, the actual emission amount of braking particulate matter for the corresponding braking event is determined.

[0120] In some embodiments, the step of calculating and determining the brake wear depth of the target new energy vehicle in a corresponding braking event based on the mechanical braking energy, brake contact surface state, brake contact surface temperature, and braking dynamic parameters, and determining the actual emission amount of brake particulate matter in the corresponding braking event based on the brake wear depth, includes:

[0121] Step S401: In each actual braking event, acquire the mechanical braking energy, braking contact surface state, braking contact surface temperature, and braking dynamic parameters of the target new energy vehicle.

[0122] Step S402: Based on the mechanical braking energy, determine the braking contact load and relative braking sliding speed between the brake pads and the brake disc during the braking event;

[0123] Step S403: Determine the material property parameters and contact stiffness parameters of the brake contact surface based on the brake contact surface state, the brake contact surface temperature, and the brake dynamics parameters;

[0124] Step S404: Calculate and determine the braking wear depth of the target new energy vehicle in the corresponding braking event based on the contact load, the relative braking speed, the material property parameters, and the contact stiffness parameters.

[0125] Step S405: Based on the brake wear depth, determine the actual amount of brake particulate matter emitted by the target new energy vehicle during the corresponding braking event.

[0126] Specifically, the formula for calculating the brake wear depth of the target new energy vehicle in the corresponding braking event is expressed as follows:

[0127]

[0128] in, The brake wear depth of the target new energy vehicle in the corresponding braking event represents the wear thickness of the brake pads and brake disc in a single braking event, which directly determines the amount of brake particles generated. The yield strength of brake pads and brake discs for new energy vehicles represents the yield limit of the materials used in brake pads and brake discs, characterizing the material's ability to resist plastic deformation. The shear strength of brake pads and brake discs for new energy vehicles is defined as the material shear limit of brake pads and brake discs, which characterizes the material's ability to resist shear wear. This represents the friction coefficient of the brake pads and brake discs, and the dynamic friction coefficient between the brake pads and brake discs, which is dynamically corrected by the condition of the brake contact surface and temperature. The elastic modulus of the brake pads and brake discs represents the elastic modulus of the brake pads and brake discs, characterizes the stiffness properties of the materials, and affects the distribution of contact stress. This represents the contact area correction factor, used to correct the deviation between the actual contact area and the nominal contact area of ​​the brake contact surface, adapting to different wear stages; is the elastic contact wear coefficient, which represents the wear coefficient of a material under elastic contact conditions, corresponding to low load and light wear conditions; is the plastic contact wear coefficient, which represents the wear coefficient of a material under plastic contact conditions, corresponding to high load and heavy wear conditions; The braking contact load represents the normal clamping force of the lining on the disc during braking. It represents the contact stiffness coefficient, which is dynamically corrected by the temperature and surface condition of the braking contact surface, and characterizes the effect of contact stiffness on wear inhibition. The fractal dimension of the contact surface characterizes the microscopic roughness of the braking contact surface. The larger the size, the rougher the surface, and the more severe the wear. is the fractal dimension of contact stiffness, which characterizes the fractal properties of the contact stiffness of the contact surface and is used to correct the influence of contact load on wear; The braking relative slip velocity represents the braking relative slip velocity between the pad and the disc during braking. It is a fractal roughness characteristic scale, representing the height scale of micro-protrusions on the contact surface, and together with the fractal dimension of the contact surface, it describes the surface morphology. Indicates the duration of braking.

[0129] Brake wear depth characterizes the degree of material loss between the brake pads and brake disc due to friction during braking, and the amount of material loss directly determines the amount of brake particulate matter generated. Therefore, the actual amount of brake particulate matter emitted during a braking event can be directly mapped through the brake wear depth, achieving precise quantification of brake particulate matter emissions.

[0130] Step S50: Based on the predicted and actual emissions of braking particulate matter corresponding to each braking event, determine the total predicted and actual emissions of braking particulate matter along the target route, upload the total predicted and actual emissions to the cloud server, and provide feedback to the driver on the emission reduction effect of this driving experience, thereby completing the prediction of braking particulate matter emissions from new energy vehicles.

[0131] Based on the mechanical braking energy, braking contact surface state, braking contact surface temperature, and braking dynamics parameters, the braking wear depth of the target new energy vehicle in the corresponding braking event is calculated and determined. After determining the actual emission of braking particulate matter for the corresponding braking event based on the braking wear depth, the total predicted emission and total actual emission of braking particulate matter for the target route are determined based on the predicted emission and actual emission of braking particulate matter for each braking event. The total predicted emission and the total actual emission are then uploaded to a cloud server to provide feedback to the driver on the emission reduction effect of this drive, thereby completing the prediction of braking particulate matter emissions from new energy vehicles.

[0132] Specifically, at the end of this driving cycle, the total predicted emissions and the total actual emissions of braking particulate matter generated during this cycle are compared. The difference between the actual and predicted emissions is displayed on the instrument panel to remind the driver. If the actual emissions are better than the predicted emissions, the driver is encouraged; otherwise, the driver is advised to control the brakes gently.

[0133] As can be seen from the above embodiments, compared with the prior art, this application addresses the problems of existing technologies in controlling brake particulate matter emissions by improving brake pads, brake disc materials or structures to reduce wear rates, but this significantly increases the cost of the braking system, and existing energy recovery strategies only focus on energy recovery efficiency and braking safety without actively optimizing in conjunction with the mechanism of brake particulate matter generation, thus failing to achieve emission prediction and source reduction from the perspective of vehicle intelligent control. This application includes, but is not limited to, the following beneficial effects:

[0134] Firstly, existing technologies mostly employ post-treatment methods such as improving braking materials, adding collection devices, and passively adsorbing particulate matter. These methods can only collect particulate matter after it is generated and cannot suppress emissions at the source. This application, however, uses vehicle-road cooperative data, navigation information, and ADAS perception to predict all braking events and braking intensity within the target route in advance. It completes emission prediction, energy allocation planning, and braking strategy optimization before braking occurs, upgrading the traditional "passive response braking" to an intelligent management and control mode of "active prediction, active allocation, and active control," truly achieving a reduction in particulate matter generation at the source.

[0135] Secondly, this application does not require replacement of the brake friction pair, nor does it require the addition of any dust collection, filtration, or suction devices. It does not alter the hardware structure, increase costs, or affect the overall vehicle layout. It can be directly installed in existing new energy vehicles and assisted driving vehicles, and has strong versatility and scalability.

[0136] Third, this application utilizes real-time vehicle conditions such as instantaneous longitudinal deceleration, total braking force at the wheel end, and current vehicle speed, and deducts the influence of wind resistance and rolling resistance to accurately calculate the actual vehicle weight. This provides a real load basis for braking energy distribution, braking wear calculation, and particulate matter emission calculation, significantly improving the consistency between the predicted and actual emissions of braking particulate matter, and making the braking particulate matter emission control strategy more in line with real driving conditions.

[0137] Fourth, this application uses actual vehicle weight, remaining battery charge, and maximum regenerative braking power of the motor as constraints to dynamically determine the allocation weight of motor braking and mechanical braking. While ensuring safety, it aims to maximize the proportion of motor braking and minimize the intervention of mechanical friction braking, fundamentally reducing friction and wear between brake pads and brake discs. This improves energy recovery rate and significantly reduces... , To reduce particulate matter emissions and achieve synergistic optimization of energy conservation and environmental protection.

[0138] Fifth, this application uses mechanical braking energy, braking contact surface state, contact surface temperature, and braking dynamic parameters as inputs to calculate braking wear depth, and directly maps the wear depth to obtain the actual particulate matter emission amount, which is highly consistent with the braking friction and wear mechanism and can more realistically and accurately reflect the generation law of particulate matter under different working conditions.

[0139] Furthermore, this application, while controlling the mechanical braking intervention ratio, dynamically adjusts the normal force according to the temperature of the braking contact surface to avoid friction coefficient decay, increased wear, and a surge in particulate matter caused by continuous high temperature in the braking system. Under the premise of ensuring braking safety, braking smoothness, and suppressing thermal fade, it minimizes braking particulate matter emissions, solving the problem that existing technologies cannot balance safety, performance, and environmental protection.

[0140] Please see Figure 3A new energy vehicle braking particulate matter emission control device provided for one of the purposes of this application includes a braking event prediction module 1100, a total braking energy distribution module 1200, a predicted emission determination module 1300, an actual emission determination module 1400, and an emission reduction effect feedback module 1500. The braking event prediction module 1100 is configured to acquire vehicle-road cooperative data and vehicle status data in the target route for the target new energy vehicle, and predict each braking event and its corresponding braking data of the target new energy vehicle in the target route based on the vehicle-road cooperative data; the total braking energy allocation module 1200 is configured to calculate and determine the actual total braking energy of the target new energy vehicle in each actual braking event; calculate and determine the actual vehicle weight of the target new energy vehicle based on the instantaneous longitudinal deceleration, instantaneous total braking force at the wheel ends and the current vehicle speed in the vehicle status data; determine the braking energy allocation weight of the target new energy vehicle in the corresponding braking event based on the actual vehicle weight, the current remaining battery power and the current motor status; and determine the recyclable electric braking energy and mechanical braking energy of the target new energy vehicle according to the braking energy allocation weight based on the actual total braking energy; the emission prediction module 1300 is configured to determine the emission amount in each predicted braking event. In this system, based on vehicle speed, target vehicle speed in the braking data, average deceleration, and vehicle weight correction coefficient related to the actual vehicle weight, combined with the braking energy distribution weight of mechanical braking, the predicted emission of braking particulate matter for the braking event is calculated and determined. The actual emission determination module 1400 is configured to calculate and determine the brake wear depth of the target new energy vehicle in the corresponding braking event based on the mechanical braking energy, brake contact surface state, brake contact surface temperature, and braking dynamic parameters, and determine the actual emission of braking particulate matter for the corresponding braking event based on the brake wear depth. The emission reduction effect feedback module 1500 is configured to determine the total predicted emission and total actual emission of braking particulate matter for the target route based on the predicted and actual emission of braking particulate matter for each braking event, upload the total predicted emission and the total actual emission to the cloud server, and provide feedback to the driver on the emission reduction effect of this driving, thereby completing the prediction of braking particulate matter emissions from new energy vehicles.

[0141] Based on any embodiment of this application, please refer to Figure 4 Another embodiment of this application also provides an electronic device, which can be implemented by a computer device, such as... Figure 4The diagram shows the internal structure of a computer device. The computer device includes a processor, a computer-readable storage medium, a memory, and a network interface connected via a system bus. The computer-readable storage medium stores an operating system, a database, and computer-readable instructions. The database may store a sequence of control information. When the computer-readable instructions are executed by the processor, the processor can implement a method for controlling particulate matter emissions from braking in new energy vehicles. The processor of the computer device provides computing and control capabilities, supporting the operation of the entire computer device. The memory of the computer device may store computer-readable instructions. When the computer-readable instructions are executed by the processor, the processor can execute the method for controlling particulate matter emissions from braking in new energy vehicles according to this application. The network interface of the computer device is used for communication with a terminal. Those skilled in the art will understand that… Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0142] In this embodiment, the processor is used to execute... Figure 3 The memory stores the specific functions of each module, and stores the program code and various data required to execute the above modules. The network interface is used for data transmission between the user terminal and the server. In this embodiment, the memory stores the program code and data required to execute all modules in the new energy vehicle braking particulate emission control device of this application, and the server can call the server's program code and data to execute the functions of all modules.

[0143] This application also provides a storage medium storing computer-readable instructions, which, when executed by one or more processors, cause the one or more processors to perform the steps of the new energy vehicle braking particulate emission control method described in any embodiment of this application.

[0144] This application also provides a computer program product, including a computer program / instructions, which, when executed by one or more processors, implement the steps of the new energy vehicle braking particulate matter emission control method described in any embodiment of this application.

[0145] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. This computer program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. The aforementioned storage medium can be a magnetic disk, optical disk, read-only memory (ROM), or random access memory (RAM), etc.

[0146] The above description is only a partial embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A method for controlling particulate matter emissions from braking in new energy vehicles, characterized in that, include: The target new energy vehicle acquires vehicle-road cooperative data and vehicle status data in the target route, and predicts each braking event of the target new energy vehicle in the target route and its corresponding braking data based on the vehicle-road cooperative data. In each actual braking event, the actual total braking energy corresponding to the target new energy vehicle is calculated and determined; based on the instantaneous longitudinal deceleration, the instantaneous total braking force at the wheel ends, and the current vehicle speed in the vehicle state data, the actual vehicle weight of the target new energy vehicle is calculated and determined. The braking energy allocation weight of the target new energy vehicle in the corresponding braking event is determined based on the actual vehicle weight, the current remaining battery power, and the current motor status. The recyclable electric braking energy and mechanical braking energy of the target new energy vehicle are determined according to the actual total braking energy and the braking energy allocation weight. In each predicted braking event, the predicted emission of braking particulate matter for the braking event is calculated and determined based on the vehicle speed, the target vehicle speed in the braking data, the average deceleration, and the vehicle weight correction coefficient related to the actual vehicle weight, combined with the braking energy distribution weight of the mechanical braking. Based on the mechanical braking energy, braking contact surface state, braking contact surface temperature, and braking dynamics parameters, the braking wear depth of the target new energy vehicle in the corresponding braking event is calculated and determined, and the actual emission amount of braking particulate matter in the corresponding braking event is determined based on the braking wear depth. Based on the predicted and actual emissions of braking particulate matter corresponding to each braking event, the total predicted and actual emissions of braking particulate matter along the target route are determined. The total predicted and actual emissions are then uploaded to a cloud server to provide feedback to the driver on the emission reduction effect of this driving experience, thereby completing the prediction of braking particulate matter emissions from new energy vehicles.

2. The method for controlling particulate matter emissions from braking in new energy vehicles according to claim 1, characterized in that, The vehicle status data includes instantaneous longitudinal deceleration, instantaneous total braking force at the wheel ends, current vehicle speed, current remaining battery power, and current motor status; The braking data includes the target vehicle speed and average deceleration for each braking event; The vehicle-road cooperative data includes road traffic signals, traffic flow data, and roadside perception information.

3. The method for controlling particulate matter emissions from braking in new energy vehicles according to claim 1, characterized in that, The steps for calculating and determining the actual weight of the target new energy vehicle based on the instantaneous longitudinal deceleration, instantaneous total braking force at the wheel ends, and current vehicle speed from the vehicle status data include: In each actual braking event, the instantaneous total braking force at the wheel ends, air density, drag coefficient, vehicle frontal area, current vehicle speed, and instantaneous longitudinal deceleration of the target new energy vehicle are obtained. The air resistance of the target new energy vehicle during the corresponding braking event is calculated and determined based on the air density, the drag coefficient, the vehicle's frontal area, and the current vehicle speed. The first difference between the instantaneous total braking force at the wheel end and the air resistance is calculated and determined to determine the effective braking force of the target new energy vehicle in the corresponding braking event. Calculate the first product between the gravitational acceleration and the rolling resistance coefficient to determine the equivalent deceleration corresponding to the rolling resistance, and calculate the first sum between the instantaneous longitudinal deceleration and the equivalent deceleration to determine the total equivalent deceleration of the target new energy vehicle in the corresponding braking event. A first ratio between the effective braking force of the target new energy vehicle and the total equivalent deceleration is calculated to determine the actual vehicle weight of the target new energy vehicle in the corresponding braking event.

4. The method for controlling particulate matter emissions from braking in new energy vehicles according to claim 1, characterized in that, The steps for calculating and determining the actual total braking energy corresponding to the target new energy vehicle include: In each actual braking event, the actual vehicle weight, current vehicle speed, and target vehicle speed of the target new energy vehicle at the corresponding braking event are obtained; Calculate and determine a third difference between the first squared value of the current vehicle speed and the second squared value of the target vehicle speed; The fifth product of half the determined value, the actual vehicle weight, and the third difference is calculated to determine the actual total braking energy of the target new energy vehicle in the corresponding braking event.

5. The method for controlling particulate matter emissions from braking in new energy vehicles according to claim 1, characterized in that, The steps of determining the braking energy allocation weight of the target new energy vehicle in the corresponding braking event based on the actual vehicle weight, current remaining battery charge, and current motor status, and determining the recoverable electric braking energy and mechanical braking energy of the target new energy vehicle according to the actual total braking energy and the braking energy allocation weight, include: Obtain the actual vehicle weight, current remaining battery power, and current motor status of the target new energy vehicle at the corresponding braking event; The braking load level of the target new energy vehicle is determined based on the actual vehicle weight, the battery rechargeable capacity threshold of the target new energy vehicle is determined based on the current remaining battery power, and the maximum regenerative braking power of the target new energy vehicle is determined based on the current motor status. The upper limit of the motor braking capacity is determined based on the battery rechargeable capacity threshold and the maximum regenerative braking power of the motor, and the braking energy distribution weights of motor braking and mechanical braking are determined based on the braking load level. Based on the braking energy allocation weight, the actual total braking energy of the target new energy vehicle in the corresponding braking event is divided into recoverable motor braking energy and mechanical braking energy that needs to be dissipated.

6. The method for controlling particulate matter emissions from braking in new energy vehicles according to claim 1, characterized in that, In each predicted braking event, the step of calculating and determining the predicted emissions of braking particulate matter for that braking event, based on the vehicle speed, the target vehicle speed in the braking data, the average deceleration, and the vehicle weight correction factor related to the actual vehicle weight, combined with the braking energy distribution weight of the mechanical braking, includes: In each predicted braking event, the current vehicle speed, target vehicle speed, average deceleration, and vehicle weight correction coefficient related to the actual vehicle weight of the target new energy vehicle are obtained. The vehicle weight correction coefficient related to the actual vehicle weight is determined by the braking energy distribution weight of mechanical braking. A second difference between the current vehicle speed and the target vehicle speed is calculated and determined, and a second ratio between the second difference and the average deceleration of the target new energy vehicle is calculated and determined, so as to determine the braking speed change rate of the target new energy vehicle in the corresponding braking event; The second product between the first calibration coefficient and the current vehicle speed is calculated and determined, and the third product between the second calibration coefficient and the square of the current vehicle speed is calculated and determined. Based on the second sum of the calibration constant term, the second product, and the third product, the basic emission factor of the target new energy vehicle in the corresponding braking event is determined. The fourth product between the vehicle weight correction factor, the braking speed change rate, and the basic emission factor is calculated to determine the predicted braking particulate matter emissions of the target new energy vehicle in the corresponding braking event.

7. The method for controlling particulate matter emissions from braking in new energy vehicles according to claim 1, characterized in that, The steps of calculating and determining the brake wear depth of the target new energy vehicle in a corresponding braking event based on the mechanical braking energy, brake contact surface state, brake contact surface temperature, and braking dynamic parameters, and determining the actual emission amount of brake particulate matter in the corresponding braking event based on the brake wear depth, include: In each actual braking event, the mechanical braking energy, braking contact surface state, braking contact surface temperature, and braking dynamic parameters of the target new energy vehicle are acquired. Based on the mechanical braking energy, determine the braking contact load and relative braking slip speed between the brake pads and the brake disc during the braking event; Based on the state of the braking contact surface, the temperature of the braking contact surface, and the braking dynamics parameters, determine the material property parameters and contact stiffness parameters of the braking contact surface; The braking wear depth of the target new energy vehicle in the corresponding braking event is calculated and determined based on the contact load, the relative braking speed, the material property parameters, and the contact stiffness parameters. Based on the brake wear depth, the actual amount of brake particulate matter emitted by the target new energy vehicle during the corresponding braking event is determined.

8. A particulate matter emission control device for braking in new energy vehicles, characterized in that, include: The braking event prediction module is configured to acquire vehicle-road cooperative data and vehicle status data in the target route for the target new energy vehicle, and predict each braking event of the target new energy vehicle in the target route and its corresponding braking data based on the vehicle-road cooperative data. The total braking energy distribution module is configured to calculate and determine the actual total braking energy corresponding to the target new energy vehicle in each actual braking event; and to calculate and determine the actual vehicle weight of the target new energy vehicle based on the instantaneous longitudinal deceleration, wheel-end instantaneous total braking force and current vehicle speed in the vehicle status data. The braking energy allocation weight of the target new energy vehicle in the corresponding braking event is determined based on the actual vehicle weight, the current remaining battery power, and the current motor status. The recyclable electric braking energy and mechanical braking energy of the target new energy vehicle are determined according to the actual total braking energy and the braking energy allocation weight. The predicted emission determination module is configured to calculate and determine the predicted emission of braking particulate matter for each predicted braking event based on the vehicle speed, the target vehicle speed in the braking data, the average deceleration, and the vehicle weight correction coefficient related to the actual vehicle weight, combined with the braking energy distribution weight of the mechanical braking. The actual emission determination module is configured to calculate and determine the brake wear depth of the target new energy vehicle in the corresponding braking event based on the mechanical braking energy, brake contact surface state, brake contact surface temperature and braking dynamic parameters, and determine the actual emission of brake particulate matter in the corresponding braking event based on the brake wear depth. The emission reduction effect feedback module is configured to determine the total predicted emission and total actual emission of braking particulate matter along the target route based on the predicted and actual emission of braking particulate matter corresponding to each braking event, and upload the total predicted emission and total actual emission to the cloud server to provide feedback to the driver on the emission reduction effect of this driving, thereby completing the prediction of braking particulate matter emissions from new energy vehicles.

9. An electronic device comprising a central processing unit and a memory, characterized in that, The central processing unit is used to invoke and run a computer program stored in the memory to perform the steps of the method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, It stores, in the form of computer-readable instructions, a computer program implemented according to any one of claims 1 to 7, which, when invoked by a computer, executes the steps included in the corresponding method.

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