Vehicle cooperative control method for mountainous road based on thermal load dynamic prediction

Abstract

This invention discloses a vehicle cooperative control method for mountain roads based on dynamic thermal load prediction, belonging to the field of vehicle active safety technology. The method includes real-time acquisition of vehicle driving environment data and braking system status data to construct a two-dimensional road condition model based on slope and curves; thermal load prediction based on the two-dimensional road condition model and vehicle status to calculate the predicted thermal load value for a predetermined road segment in the future; and multi-level cooperative vehicle control based on the predicted thermal load value and brake disc temperature. The control unit drives the execution of cooling operations, while simultaneously recording driver operation behavior and system response data during the control process to optimize thermal load prediction. This invention improves the forward-looking identification capability of braking thermal risks under complex working conditions on mountain roads, reduces long-term prediction deviations, and extends brake life; it ensures driving safety while also considering passenger experience and system economy.

Description

Technical Field

[0001] This invention relates to the field of active vehicle safety technology, and in particular to a collaborative control method for vehicles on mountain roads based on dynamic prediction of thermal load. Background Technology

[0002] In recent years, with the development of the automotive industry and intelligent driving technology, vehicle safety in complex road environments has become a research hotspot. Especially in mountainous and hilly roads with steep slopes and numerous curves, vehicles are prone to frequent braking and continuous brake pad temperature increases on long downhill sections and continuous curves, leading to decreased braking efficiency or even brake fade, posing significant safety risks. To address this issue, existing technologies mainly focus on two aspects: firstly, improving the heat dissipation capacity of the braking system, such as using large-size ventilated discs, ceramic composite brake pads, and air-cooled or water-cooled auxiliary cooling devices to improve the system's heat resistance; secondly, utilizing electronic control systems such as Electronic Stability Program (ESP), Anti-lock Braking System (ABS), and Hill Start Assist Control (HAC) to coordinate the operation of the engine, transmission, and brakes on downhill sections or continuous curves, distributing some of the braking load and reducing the rate of heat buildup on the brake discs. Meanwhile, some high-end models have also begun to try to introduce feedforward control and road preview technology. By reading high-precision maps, camera or slope sensor data, the longitudinal slope and curve information of the road ahead of the vehicle can be predicted, thereby adjusting the shift strategy and engine braking in advance to reduce the instantaneous thermal shock of the braking system.

[0003] However, existing technologies still have significant shortcomings in practical applications. First, traditional brake thermal management relies heavily on passive cooling and reactive response, meaning that fans or liquid cooling devices are only activated when the brake disc temperature has already reached a high level. This results in delayed cooling action, failing to effectively suppress temperature peaks and increasing the risk of thermal fatigue in the braking system. Second, existing road-predictive control strategies typically adjust transmission gears based solely on road geometry parameters, without comprehensively considering factors such as actual vehicle weight, current speed, and braking frequency. This leads to insufficient prediction accuracy and a tendency for gear shifts to occur too early or too late, affecting driving smoothness. Furthermore, most existing control strategies are single-stage controls, such as adjusting engine speed or activating air cooling alone. They lack multi-level coordinated control of engine braking, friction braking, and the cooling system, resulting in a mismatch between braking energy distribution and cooling capacity, potentially causing localized overheating. Finally, existing systems generally lack self-learning and model optimization capabilities, failing to dynamically correct prediction parameters based on historical driving behavior and actual temperature response. Over prolonged use, prediction biases tend to accumulate, reducing control effectiveness. Summary of the Invention

[0004] The purpose of this invention is to provide a vehicle cooperative control method for mountain roads based on dynamic heat load prediction. This method uses high spatiotemporal resolution characterization of road geometry and vehicle status for physically quantified heat load prediction, and combines the prediction results with real-time temperature change rate as trigger logic for multi-level control, thereby achieving progressive linkage and closed-loop optimization of engine braking, air cooling, and water cooling. This invention provides the following technical solution:

[0005] In a first aspect, the present invention provides a vehicle cooperative control method for mountain roads based on dynamic prediction of heat load, which includes real-time acquisition of vehicle driving environment data and braking system status data, and construction of a two-dimensional road condition model of slope and curve.

[0006] Heat load prediction is performed based on a two-dimensional road condition model and vehicle status, and the predicted heat load value within a predetermined road segment in the future is calculated.

[0007] Based on the predicted heat load value and brake disc temperature, the vehicle is controlled in a multi-level coordinated manner. The control unit drives the heat dissipation operation and records the driver's operation behavior and system response data during the control process to optimize the heat load prediction.

[0008] As a preferred embodiment of the vehicle cooperative control method for mountain roads based on dynamic prediction of thermal load described in this invention, the vehicle driving environment data includes the current road section gradient and the radius of the curve ahead; the braking system status data includes brake disc temperature, vehicle mass, current vehicle speed and engine speed.

[0009] As a preferred embodiment of the vehicle cooperative control method for mountain roads based on dynamic prediction of heat load described in this invention, the construction of the two-dimensional road condition model of slope and curve includes:

[0010] Preprocessing of sensor-acquired data includes filtering, noise reduction, and anomaly detection;

[0011] The preprocessed sensor data is used to construct a two-dimensional road condition model based on slope and curve. Any point on the path ahead of the vehicle in this two-dimensional road condition model is represented by a pair of tuples:

[0012] ;

[0013] in: It is a two-dimensional road condition model. For slope, The radius of the curve is 1. This represents the distance the vehicle is ahead along its current heading.

[0014] As a preferred embodiment of the vehicle cooperative control method for mountain roads based on dynamic heat load prediction described in this invention, the calculation of the predicted heat load value within a predetermined road segment in the future includes:

[0015] The planned road segment will be divided into multiple segments of fixed length.

[0016] The heat load is predicted for each calculated segment, and the total predicted heat load for the future predetermined length of road segment is obtained by summing them up.

[0017] As a preferred embodiment of the vehicle cooperative control method for mountain roads based on dynamic heat load prediction described in this invention, the expression for the total predicted heat load is:

[0018] ;

[0019] ;

[0020] in: To predict heat load, This is the curve density coefficient. For vehicle quality, It is the acceleration due to gravity. The slope angle, For the length of the road segment, The air drag coefficient, air density, This refers to the projected area of ​​the vehicle's front. Current vehicle speed; For the total predicted heat load, For road section Predicted heat load, This refers to the number of road segments.

[0021] As a preferred embodiment of the vehicle cooperative control method for mountain roads based on dynamic heat load prediction described in this invention, the curve density coefficient includes:

[0022] Define the foundation curve density coefficient and dynamically adjust it, expressed as:

[0023] ;

[0024] in: Based on the basic curve density coefficient, Sensitivity coefficient; Curvature density index These are reference values.

[0025] As a preferred embodiment of the vehicle cooperative control method for mountain roads based on dynamic prediction of heat load described in this invention, the multi-level cooperative control of vehicles based on predicted heat load values ​​and brake disc temperatures includes:

[0026] The total predicted heat load output by the heat load prediction unit is compared with the predetermined heat load threshold:

[0027] When the total predicted heat load exceeds the heat load threshold, the vehicle is considered to be at high risk. The control unit issues a shift command to switch the transmission to the target gear. The target gear is pre-calibrated using the vehicle dynamics model. Simultaneously, the brake disc temperature is acquired, and the rate of temperature change is calculated, expressed as:

[0028] ;

[0029] in: For the rate of temperature change, Sampling time Brake disc temperature, Sampling time Brake disc temperature, The sampling period;

[0030] When the brake disc temperature exceeds the predetermined first temperature and the temperature change rate exceeds the predetermined first change rate, active cooling measures are immediately activated, and the control unit starts the axial turbine air cooling device.

[0031] When the brake disc temperature exceeds the predetermined second temperature or the temperature change rate continues to exceed the predetermined first change rate for a predetermined time, the control unit immediately activates the external micro-water cooling circulation system to cool the brake disc.

[0032] When the brake disc temperature drops below the predetermined first temperature, the control unit gradually restores the transmission to its original gear. During the heat dissipation control process, the driver's operating behavior, system response data, and the deviation between the predicted heat load value and the actual heat release are recorded simultaneously.

[0033] Based on the deviation between the predicted heat load and the actual heat release, the bend density coefficient is iteratively corrected using the least squares method.

[0034] In a second aspect, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of a vehicle cooperative control method for mountain roads based on dynamic prediction of heat load.

[0035] Thirdly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements the steps of a vehicle cooperative control method for mountain roads based on dynamic prediction of heat load.

[0036] The beneficial effects of this invention are as follows: This invention significantly improves the ability to proactively identify braking thermal risks under complex working conditions on mountain roads, thereby enabling early and graded intervention to suppress temperature peaks; through closed-loop learning of behavioral and system response data, it reduces long-term prediction bias and extends brake life; and it avoids simplistic and aggressive cooling or frequent gear shifting, thereby ensuring driving safety while also taking into account passenger experience and system economy. Attached Figure Description

[0037] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0038] Figure 1 This is a flowchart of a vehicle cooperative control method for mountain roads based on dynamic prediction of heat load. Detailed Implementation

[0039] To make the above-mentioned objects, features, and advantages of the present invention more readily understood, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0040] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0041] Secondly, the term "one embodiment" or "example" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the invention. An embodiment appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment that selectively excludes other embodiments.

[0042] Reference Figure 1 This is the first embodiment of the present invention, which provides a vehicle cooperative control method for mountain roads based on dynamic prediction of heat load, including:

[0043] S1: Real-time acquisition of vehicle driving environment data and braking system status data to construct a two-dimensional road condition model of slope and curve;

[0044] S2: Based on the two-dimensional road condition model and vehicle status, predict the heat load and calculate the predicted heat load value within the future predetermined length of the road segment.

[0045] S3: Based on the predicted heat load value and brake disc temperature, the vehicle performs multi-level coordinated control. The control unit drives the heat dissipation operation and records the driver's operation behavior and system response data during the control process to optimize the heat load prediction.

[0046] Slope sensor: outputs slope gradient; GPS + map: used to obtain the radius of the curve ahead; infrared temperature sensor: obtains the brake disc temperature; vehicle CAN bus: provides vehicle mass, current vehicle speed, engine speed, etc.; preprocesses the data acquired by the sensors, including filtering, noise reduction and anomaly detection.

[0047] The preprocessed sensor data is fused to construct a two-dimensional road condition model based on slope and curve. Any point on the path ahead of the vehicle in this two-dimensional road condition model is represented by a pair of tuples:

[0048] ;

[0049] in: It is a two-dimensional road condition model. For slope, The radius of the curve is 1. For visibility, This represents the distance the vehicle is ahead along its current heading.

[0050] The predetermined road segment is divided into multiple segments of fixed length. The predicted heat load is calculated for each segment, and the total predicted heat load for the predetermined road segment is obtained by summing the results. This is expressed as:

[0051] ;

[0052] ;

[0053] in: To predict heat load, This is the curve density coefficient. For vehicle quality, It is the acceleration due to gravity. The slope angle, For the length of the road segment, The air drag coefficient, air density, This refers to the projected area of ​​the vehicle's front. Current vehicle speed; For the total predicted heat load, For road section Predicted heat load, Number of road segments;

[0054] Define the foundation curve density coefficient and dynamically adjust it, expressed as:

[0055] ;

[0056] in: Based on the basic curve density coefficient, The sensitivity coefficient is obtained through regression learning; The curvature density index is obtained by statistically analyzing the total number of curve segments that meet the curvature requirements within a future predetermined road length, and then normalizing the result. For reference only;

[0057] The total predicted heat load output by the heat load prediction unit is compared with the predetermined heat load threshold:

[0058] When the total predicted heat load is greater than the heat load threshold, it indicates that there will be a large amount of braking energy consumption in the future predetermined road section, which is likely to cause the brake pads and brake discs to overheat. The control unit issues a shift command to switch the transmission to the target gear, which is pre-calibrated by the vehicle dynamics model.

[0059] Simultaneously, the brake disc temperature is acquired, and the rate of temperature change is calculated, expressed as:

[0060] ;

[0061] in: For the rate of temperature change, Sampling time Brake disc temperature, Sampling time Brake disc temperature, The sampling period.

[0062] When the brake disc temperature is greater than the predetermined first temperature and the temperature change rate is greater than the predetermined first change rate, it indicates that the brake disc temperature rise trend is obvious and active cooling measures need to be intervened immediately. The control unit starts the axial turbine air cooling device.

[0063] When the brake disc temperature exceeds the predetermined second temperature or the temperature change rate continues to exceed the predetermined first change rate for a predetermined time, it indicates a risk of brake failure. The control unit immediately activates the external micro-cooling circulation system to cool the brake disc.

[0064] After the control unit issues a heat dissipation command, it sequentially drives the axial turbine fan and the external water cooling system: the air cooling device forms an airflow to force convection heat dissipation on the surface of the brake disc, and the water cooling pipeline starts the micro-distance water cooling circulation system, with the coolant flowing along the spiral tube close to the surface of the brake disc to achieve close-range heat conduction and heat dissipation.

[0065] If the predicted heat load remains in the high-risk range during the cooling process, the transmission will remain in the target gear and the friction braking load will continue to be shared through engine braking.

[0066] When the brake disc temperature drops below the predetermined first temperature, the control unit gradually restores the transmission to its original gear. During the heat dissipation control process, the driver's operating behavior, system response data, and the deviation between the predicted heat load value and the actual heat release are recorded simultaneously.

[0067] Based on the deviation between the predicted heat load and the actual heat release, the bend density coefficient is iteratively corrected using the least squares method.

[0068] This embodiment also provides a computer device applicable to the vehicle cooperative control method for mountain roads based on dynamic prediction of heat load, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement all or part of the steps of the method described in the above embodiments of the present invention.

[0069] This embodiment also provides a storage medium storing a computer program thereon. When the computer program is executed by a processor, it performs the method in any optional implementation of the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read-Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0070] The storage medium proposed in this embodiment and the data storage method proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0071] In summary, this invention significantly improves the ability to proactively identify braking thermal risks under complex working conditions on mountain roads, thereby enabling early and graded intervention to suppress temperature peaks; through closed-loop learning of behavioral and system response data, it reduces long-term prediction bias and extends brake life; and it avoids simplistic and aggressive cooling or frequent gear shifting, thus ensuring driving safety while also considering passenger experience and system economy.

[0072] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A vehicle cooperative control method for mountain roads based on dynamic heat load prediction, characterized in that: include, Real-time data collection of vehicle driving environment and braking system status is used to construct a two-dimensional road condition model of slope and curve. The vehicle driving environment data includes the current road gradient and the radius of the curve ahead; The braking system status data includes brake disc temperature, vehicle weight, current vehicle speed, and engine speed; The construction of the slope-curve two-dimensional road condition model includes: Preprocessing of sensor-acquired data includes filtering, noise reduction, and anomaly detection; The preprocessed sensor data is used to construct a two-dimensional road condition model based on slope and curve. Any point on the path ahead of the vehicle in this two-dimensional road condition model is represented by a pair of tuples: in: It is a two-dimensional road condition model. For slope, The radius of the curve is 1. This represents the distance the vehicle is ahead along its current heading. Heat load prediction is performed based on a two-dimensional road condition model and vehicle status, and the predicted heat load value within a predetermined road segment in the future is calculated. Based on the predicted heat load value and brake disc temperature, the vehicle is controlled in a multi-level coordinated manner. The control unit drives the heat dissipation operation and records the driver's operation behavior and system response data during the control process to optimize the heat load prediction. The multi-level coordinated vehicle control based on predicted heat load and brake disc temperature includes: The total predicted heat load output by the heat load prediction unit is compared with the predetermined heat load threshold: When the total predicted heat load exceeds the heat load threshold, the vehicle is considered to be at high risk. The control unit issues a shift command to switch the transmission to the target gear. The target gear is pre-calibrated using the vehicle dynamics model. Simultaneously, the brake disc temperature is acquired, and the rate of temperature change is calculated, expressed as: in: For the rate of temperature change, Sampling time Brake disc temperature, Sampling time Brake disc temperature, The sampling period; When the brake disc temperature exceeds the predetermined first temperature and the temperature change rate exceeds the predetermined first change rate, active cooling measures are immediately activated, and the control unit starts the axial turbine air cooling device. When the brake disc temperature exceeds the predetermined second temperature or the temperature change rate continues to exceed the predetermined first change rate for a predetermined time, the control unit immediately activates the external micro-water cooling circulation system to cool the brake disc. When the brake disc temperature drops below the predetermined first temperature, the control unit gradually restores the transmission to its original gear. During the heat dissipation control process, the driver's operating behavior, system response data, and the deviation between the predicted heat load value and the actual heat release are recorded simultaneously. Based on the deviation between the predicted heat load and the actual heat release, the bend density coefficient is iteratively corrected using the least squares method.

2. The method for coordinated vehicle control on mountain roads based on dynamic heat load prediction as described in claim 1, characterized in that: The calculation of the predicted heat load value within the future predetermined length of the road segment includes: The planned road segment will be divided into multiple segments of fixed length. The heat load is predicted for each calculated segment, and the total predicted heat load for the future predetermined length of road segment is obtained by summing them up.

3. The method for coordinated vehicle control on mountain roads based on dynamic heat load prediction as described in claim 2, characterized in that: The expression for the total predicted heat load is: in: To predict heat load, For curve density coefficient, For vehicle quality, It is the acceleration due to gravity. The slope angle, For the length of the road segment, The air drag coefficient, air density, This refers to the projected area of ​​the vehicle's front. Current vehicle speed; For the total predicted heat load, For road section Predicted heat load, This refers to the number of road segments.

4. The method for coordinated vehicle control on mountain roads based on dynamic heat load prediction as described in claim 3, characterized in that: The curve density coefficient includes: Define the foundation curve density coefficient, and dynamically adjust the foundation curve density coefficient as follows: in: Based on the basic curve density coefficient, Sensitivity coefficient; Curvature density index These are reference values.

5. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the vehicle cooperative control method for mountain roads based on dynamic prediction of heat load as described in any one of claims 1 to 4.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, it implements the steps of the vehicle cooperative control method for mountain roads based on dynamic prediction of heat load as described in any one of claims 1 to 4.

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