Control method, device and system for vehicle suspension system and vehicle

Abstract

The invention relates to the technical field of vehicle control, and discloses a control method, device and system for a vehicle suspension system and a vehicle. The control method comprises the steps that risk environment data influencing vehicle driving safety are obtained; obtaining vehicle operation data related to vehicle driving safety; determining a current risk level of the vehicle according to the risk environment data and the vehicle operation data; a target suspension adjusting instruction is generated according to the current risk level, and the vehicle suspension system is adjusted according to the target suspension adjusting instruction. The risk environment data and the vehicle operation data are used for fusion analysis, the current environment and the current operation information of the vehicle can be comprehensively considered, the comprehensiveness during data analysis is improved, and therefore the more accurate current risk level is obtained, the target suspension adjusting instruction is generated according to the current risk level, and the adjustment accuracy is improved. Intelligent adjustment of the suspension system can be achieved, the comprehensive performance of the vehicle is improved, and then the safety and stability of the vehicle in a complex environment are improved.

Description

Technical Field

[0001] The present application relates to the technical field of vehicle control, and for example, relates to a control method, device, system and vehicle for a vehicle suspension system. Background Art

[0002] With the increasingly perfect layout of vehicle sensors and the increasing diversification of vehicle actuators, the level of vehicle intelligence and electrification has been improved, and the vehicle functions have become more perfect and powerful. At present, the suspension system of vehicles has evolved from the original passive suspension to an active suspension, which can actively adjust the suspension height and ride comfort according to user needs and vehicle conditions. However, most of the suspension functions are internal functions of the suspension system, and the functional correlation with other systems of the vehicle needs to be improved.

[0003] In the related art, a control method for an air suspension is proposed, including: collecting the air spring height signal of the wheel according to the height sensor of the air suspension, and combining the current state of the vehicle to judge whether the vehicle is in a wading state; when it is judged that the vehicle is in a wading state, adjusting the air suspension height.

[0004] In the process of implementing the embodiments of the present disclosure, it is found that at least the following problems exist in the related art:

[0005] In the related art, only wading conditions are considered, and other conditions that may affect the safety state of the vehicle are not comprehensively considered, so the safety and stability of the vehicle in a complex environment are relatively low.

[0006] It should be noted that the information disclosed in the above background art section is only used to enhance the understanding of the background of the present application, and thus may include information that does not constitute the prior art known to those of ordinary skill in the art. Summary of the Invention

[0007] To have a basic understanding of some aspects of the disclosed embodiments, a simple summary is given below. This summary is not a general review, nor is it intended to identify key / important elements or delineate the protection scope of these embodiments, but is presented as a preface to the subsequent detailed description.

[0008] The embodiments of the present disclosure provide a control method, device, system and vehicle for a vehicle suspension system, which improve the safety and stability of the vehicle in a complex environment.

[0009] In some embodiments, the control method for the vehicle suspension system includes: obtaining risk environment data affecting vehicle driving safety; obtaining vehicle operation data related to vehicle driving safety; determining the current risk level of the vehicle according to the risk environment data and the vehicle operation data; generating a target suspension adjustment instruction according to the current risk level to adjust the vehicle suspension system according to the target suspension adjustment instruction.

[0010] Optionally, when the risk environment data includes vehicle wading data, determine the current risk level of the vehicle according to the risk environment data and the vehicle operation data, including: determining the current water depth data in the vehicle wading data, and determining the longitudinal and lateral accelerations and the angular rate in the vehicle operation data; performing eigenvalue quantization on the current water depth data, the longitudinal and lateral accelerations, and the angular rate, and calculating the current wading risk level of the vehicle according to the quantization data.

[0011] Optionally, when the risk environment data includes vehicle surrounding wind speed data, determine the current risk level of the vehicle according to the risk environment data and the vehicle operation data, including: determining the current wind speed data in the vehicle surrounding wind speed data, and determining the longitudinal and lateral accelerations and the angular rate in the vehicle operation data; performing eigenvalue quantization on the current wind speed data, the longitudinal and lateral accelerations, and the angular rate, and calculating the current high wind risk level of the vehicle according to the quantization data.

[0012] Optionally, when the risk environment data includes vehicle wading data and vehicle surrounding wind speed data, determine the current risk level of the vehicle according to the risk environment data and the vehicle operation data, including: determining the current water depth data in the vehicle wading data, the current wind speed data in the vehicle surrounding wind speed data, and determining the longitudinal and lateral accelerations and the angular rate in the vehicle operation data; performing eigenvalue quantization and comprehensive risk assessment on the current water depth data and the current wind speed data to obtain comprehensive risk data; performing eigenvalue quantization on the longitudinal and lateral accelerations and the angular rate, and calculating the current comprehensive risk level of the vehicle according to the quantization data and the comprehensive risk data.

[0013] Optionally, performing eigenvalue quantization and comprehensive risk assessment on the current water depth data and the current wind speed data to obtain comprehensive risk data, including: assigning initial weights to the current water depth data and the current wind speed data according to the vehicle design and the actual use scenario; adjusting the initial weights according to the real-time operation state of the vehicle to obtain target weights; performing eigenvalue quantization and comprehensive risk assessment on the current water depth data and the current wind speed data according to the target weights to obtain comprehensive risk data.

[0014] Optionally, generate a target suspension adjustment instruction according to the current risk level, including: determining a suspension adjustment strategy according to the current risk level; generating a target suspension adjustment instruction according to the suspension adjustment strategy; the target suspension adjustment instruction includes an adjustment height and an adjustment direction.

[0015] Optionally, the control method further includes: after generating the target suspension adjustment instruction, sending the target suspension adjustment instruction to the user for confirmation; determining whether to execute the target suspension adjustment instruction according to the confirmation result of the user.

[0016] In some embodiments, a control device for a vehicle suspension system includes a processor and a memory storing program instructions. The processor is configured to execute the control method for the vehicle suspension system as described above when running the program instructions.

[0017] In some embodiments, a control system for a vehicle suspension system includes: an environmental sensor module configured to acquire risk environment data affecting vehicle driving safety; a vehicle sensor module configured to acquire vehicle operation data related to vehicle driving safety; a suspension height adjustment controller configured to determine the current risk level of the vehicle based on the risk environment data and the vehicle operation data, and generate a target suspension adjustment instruction according to the current risk level; and a suspension adjustment actuator configured to adjust the vehicle suspension system according to the target suspension adjustment instruction.

[0018] In some embodiments, a vehicle includes: a vehicle body; a vehicle suspension system disposed on the vehicle body; and the control system for the vehicle suspension system as described above, disposed on the vehicle body and connected to the vehicle suspension system.

[0019] The control method, device, system, and vehicle for a vehicle suspension system provided by the embodiments of the present disclosure can achieve the following technical effects:

[0020] In the embodiments of the present disclosure, according to the risk environment data around the vehicle, factors that affect vehicle driving safety in the current environment can be identified; according to the vehicle operation data related to vehicle driving safety, the current driving state of the vehicle can be confirmed. By using the risk environment data and the vehicle operation data for fusion analysis, the current environment and the current operation information of the vehicle can be comprehensively considered, the comprehensiveness in data analysis can be improved, and thus a more accurate current risk level can be obtained. The target suspension adjustment instruction generated according to the current risk level can realize the intelligent adjustment of the suspension system, improve the comprehensive performance of the vehicle, and further improve the safety and stability of the vehicle in complex environments.

[0021] The above general description and the following description are only exemplary and explanatory, and are not used to limit the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] One or more embodiments are exemplarily illustrated by corresponding drawings. These exemplary illustrations and the drawings do not constitute a limitation on the embodiments. Elements with the same reference numerals in the drawings are shown as similar elements. The drawings do not constitute a scale limitation, and in which:

[0023] Figure 1 is a schematic diagram of a control method for a vehicle suspension system provided by an embodiment of the present disclosure;

[0024] Figure 2It is a schematic diagram of a vehicle entering a wading area provided by an embodiment of the present disclosure;

[0025] Figure 3 It is a schematic diagram of risk prompt through an interaction terminal in a wading scenario provided by an embodiment of the present disclosure;

[0026] Figure 4 It is a schematic diagram of vehicle adjustment state display through an interaction terminal in a wading scenario provided by an embodiment of the present disclosure;

[0027] Figure 5 It is a schematic diagram of risk prompt through an interaction terminal in a strong wind scenario provided by an embodiment of the present disclosure;

[0028] Figure 6 It is a schematic diagram of vehicle adjustment state display through an interaction terminal in a strong wind scenario provided by an embodiment of the present disclosure;

[0029] Figure 7 It is a schematic diagram of a control device for a vehicle suspension system provided by an embodiment of the present disclosure;

[0030] Figure 8 It is a schematic diagram of a control system for a vehicle suspension system provided by an embodiment of the present disclosure;

[0031] Figure 9 It is a signal topology sketch in a control system for a vehicle suspension system provided by an embodiment of the present disclosure. Detailed implementation manners

[0032] In order to be able to understand the features and technical content of the embodiments of the present disclosure in more detail, the implementation of the embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. The accompanying drawings are only for reference and illustration purposes and are not used to limit the embodiments of the present disclosure. In the following technical description, for the sake of explanation, multiple details are provided to give a full understanding of the disclosed embodiments. However, one or more embodiments can still be implemented without these details. In other cases, well-known structures and devices can be shown in a simplified manner to simplify the drawings.

[0033] The terms "first", "second", etc. in the technical solutions described in this application are used to distinguish similar objects and do not have to be used to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so as to implement the embodiments of the present disclosure described here. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion.

[0034] Unless otherwise specified, the term "plurality" means two or more.

[0035] In the embodiments of the present disclosure, the character " / " indicates an "or" relationship between the front and rear objects. For example, A / B means: A or B.

[0036] The term "and / or" is an associative relationship describing an object, indicating that three relationships can exist. For example, A and / or B means: A or B, or, the three relationships of A and B.

[0037] The term "corresponding" can refer to an associative relationship or a binding relationship. A corresponding to B means that there is an associative relationship or a binding relationship between A and B.

[0038] Combined with Figure 1 As shown, the embodiments of the present disclosure provide a control method for a vehicle suspension system. The execution subject of the control method can be a processor, and the control method includes:

[0039] S101, the processor obtains risk environment data that affects vehicle driving safety.

[0040] S102, the processor obtains vehicle operation data related to vehicle driving safety.

[0041] S103, the processor determines the current risk level of the vehicle according to the risk environment data and the vehicle operation data.

[0042] S104, the processor generates a target suspension adjustment instruction according to the current risk level to adjust the vehicle suspension system according to the target suspension adjustment instruction.

[0043] In the embodiments of the present disclosure, according to the risk environment data around the vehicle, factors that affect vehicle driving safety in the current environment can be identified; according to the vehicle operation data related to vehicle driving safety, the current driving state of the vehicle can be confirmed. Using the risk environment data and the vehicle operation data for fusion analysis can comprehensively consider the current environment and the current operation information of the vehicle, improve the comprehensiveness during data analysis, and thus obtain a more accurate current risk level. The target suspension adjustment instruction generated according to the current risk level can realize the intelligent adjustment of the suspension system, improve the comprehensive performance of the vehicle, and further improve the safety and stability of the vehicle in a complex environment.

[0044] Optionally, the risk environment data includes vehicle wading data and / or vehicle surrounding wind speed data.

[0045] In this embodiment, in order to achieve height adjustment of the vehicle suspension system in wading scenarios and strong wind scenarios, wading data around the vehicle can be obtained through a wading sensor, and wind speed data of the environment where the vehicle is located can be obtained through a wind speed sensor. By continuously monitoring and comprehensively analyzing the wading data and wind speed data, the risk level of the vehicle can be accurately evaluated, and corresponding target suspension adjustment instructions can be generated, thereby improving the safety and stability of the vehicle in complex environments.

[0046] Optionally, obtaining vehicle wading data includes: obtaining water depth data through ultrasonic sensors, lidar, or cameras installed at the front, side, or bottom of the vehicle; calculating the water level change rate by continuously monitoring the change rate of the water depth data; and determining the wading area range by scanning the wading area around the vehicle with a camera or lidar.

[0047] In this embodiment, by monitoring various wading data, it can be determined whether the vehicle is about to enter a wading area or is currently in a wading state, so as to evaluate whether the vehicle can safely pass through the wading area or whether it needs to take a detour.

[0048] Optionally, obtaining wind speed data around the vehicle includes: measuring the horizontal wind speed through a wind speed sensor installed on the top or side of the vehicle; measuring the vertical wind speed through a wind speed sensor, such as gusts or eddies; and obtaining the wind direction information through a wind direction sensor.

[0049] In this embodiment, through the horizontal wind speed, the lateral wind force impact that the vehicle may receive during driving can be evaluated, especially when driving at high speed. And through the vertical wind speed, the wind force impact that the vehicle may receive in the vertical direction can be evaluated, especially on bridges or elevated roads. Combining the horizontal wind speed and vertical wind speed data can more comprehensively evaluate the impact of the wind on the vehicle. For example, crosswinds may have a greater impact on the stability of the vehicle, while the impact of headwinds or tailwinds is relatively small.

[0050] Optionally, the vehicle operation data related to vehicle driving safety includes: the longitudinal and lateral accelerations and yaw rate of the vehicle. In addition, in different embodiments, the vehicle operation data may also include one or more of the following: vehicle speed, wheel speed signal, steering rate, power status, yaw angular velocity, left front body height signal, right front body height signal, left rear body height signal, and right rear body height signal.

[0051] In this embodiment, the vehicle operation data provides comprehensive information about the vehicle operation state. For example: the driving stability of the vehicle can be judged according to the vehicle speed; slip detection and road condition judgment can be carried out according to the wheel speed signal; system function guarantee can be achieved according to the power status; the balance and stability of the vehicle can be judged according to the longitudinal and lateral accelerations; and suspension state monitoring can be achieved according to the body height signal.

[0052] Optionally, when the risk environment data includes vehicle wading data, determine the current risk level of the vehicle according to the risk environment data and the vehicle operation data, including: determining the current water depth data in the vehicle wading data, and determining the lateral and longitudinal accelerations and the angular rate in the vehicle operation data; quantifying the eigenvalues of the current water depth data, the lateral and longitudinal accelerations, and the angular rate, and calculating the current wading risk level of the vehicle according to the quantified data.

[0053] In this embodiment, by quantifying the eigenvalues such as water depth, acceleration, and angular rate, and then combining algorithms such as weighted summation, the risk level of the vehicle in the wading situation can be accurately evaluated. It not only considers the influence of a single factor, but also comprehensively considers the interaction of multiple factors, improving the accuracy and reliability of the risk assessment. Figure 2 As shown, when the vehicle enters the wading area, calculate the predicted water depth h2 of the vehicle after traveling a distance l according to the wading depth h1 of the front wheels in the driving direction, the road slope α displayed by the navigation, and the current vehicle real-time inclination signal, etc., so as to determine whether the vehicle is about to enter the deep water area. Combine the current vehicle operation state signals, such as lateral and longitudinal accelerations, angular rate, etc., to determine the current wading risk level in the wading state. For example, assume that the currently collected data is: water depth 25 cm, lateral and longitudinal acceleration 0.6 g, angular rate 9° / s. Quantify the eigenvalues of the above data. If the consideration range of the water depth data is 0 to 50 cm, the quantified data of the water depth data is 5. If the consideration range of the lateral and longitudinal acceleration is 0 to 1.5 g, the quantified data of the lateral and longitudinal acceleration is 4. If the consideration range of the angular rate is 0 to 15° / s, the quantified data of the angular rate is 6. Then assign weights to each eigenvalue and perform weighted calculation. For example, the water depth weight is 0.6, the lateral and longitudinal acceleration weight is 0.2, and the angular rate weight is 0.2. Calculate the current risk level as 5×0.6 + 4×0.2 + 6×0.2 = 5. Assume that the risk level is divided into 1 to 3 levels as low risk levels, 4 to 6 levels as medium risk levels, and 7 to 10 levels as high risk levels. Then it can be determined that the current wading risk level 5 is a medium risk level.

[0054] Optionally, when the risk environment data includes the vehicle surrounding wind speed data, determine the current risk level of the vehicle according to the risk environment data and the vehicle operation data, including: determining the current wind speed data in the vehicle surrounding wind speed data, and determining the lateral and longitudinal accelerations and the angular rate in the vehicle operation data; quantifying the eigenvalues of the current wind speed data, the lateral and longitudinal accelerations, and the angular rate, and calculating the current high wind risk level of the vehicle according to the quantified data.

[0055] In this embodiment, by quantifying eigenvalues such as wind speed, acceleration, and angular rate, and then combining algorithms such as weighted summation, the risk level of the vehicle in strong wind conditions can be accurately evaluated. It not only considers the influence of single factors but also synthesizes the interaction of multiple factors, improving the accuracy and reliability of risk assessment. When the vehicle is traveling at a high speed and a large wind speed is detected, based on the current wind speed data and signals such as the longitudinal and lateral accelerations and angular rate during the current operation of the vehicle, the current high wind risk level is determined. For example, assume the currently collected data is: wind speed 21 m / s, longitudinal and lateral acceleration 0.9 g, and angular rate 3° / s. Quantify the eigenvalues of the above data. If the considered range of wind speed data is 0 to 30 m / s, the quantified data of the wind speed data is 7. If the considered range of longitudinal and lateral acceleration is 0 to 1.5 g, the quantified data of the longitudinal and lateral acceleration is 6. If the considered range of angular rate is 0 to 15° / s, the quantified data of the angular rate is 2. Then assign weights to each eigenvalue and perform weighted calculation. For example, the wind speed weight is 0.6, the longitudinal and lateral acceleration weight is 0.2, and the angular rate weight is 0.2. Calculate the current risk level as 7×0.6 + 6×0.2 + 2×0.2 = 5.8. Assume the risk level is divided into 1 to 3 as low risk level, 4 to 6 as medium risk level, and 7 to 10 as high risk level. Then it can be determined that the current high wind risk level 5.8 is a medium risk level.

[0056] Optionally, when the risk environment data includes vehicle wading data and vehicle surrounding wind speed data, determine the current risk level of the vehicle according to the risk environment data and vehicle operation data, including: determining the current water depth data in the vehicle wading data, the current wind speed data in the vehicle surrounding wind speed data, and determining the longitudinal and lateral accelerations and angular rate in the vehicle operation data; performing eigenvalue quantization and comprehensive risk assessment on the current water depth data and the current wind speed data to obtain comprehensive risk data; performing eigenvalue quantization on the longitudinal and lateral accelerations and angular rate, and calculating the current comprehensive risk level of the vehicle according to the quantified data and the comprehensive risk data.

[0057] In this embodiment, by comprehensively considering the wading data, wind speed data, and the operating state of the vehicle, the risk level of the vehicle in complex environments can be comprehensively evaluated.

[0058] Optionally, performing eigenvalue quantization and comprehensive risk assessment on the current water depth data and the current wind speed data to obtain comprehensive risk data includes: assigning initial weights to the current water depth data and the current wind speed data according to vehicle design and actual use scenarios; adjusting the initial weights according to the real-time operating state of the vehicle to obtain target weights; performing eigenvalue quantization and comprehensive risk assessment on the current water depth data and the current wind speed data according to the target weights to obtain comprehensive risk data.

[0059] In this embodiment, according to the vehicle design and actual usage scenarios, initial weights can be assigned to the current water depth data and the current wind speed data. For example, considering the vehicle's wading depth design standard and wind resistance design standard, as well as the environment where the vehicle mainly travels, such as urban roads, mountain roads, coastal areas, etc., the safety priorities of wading risk and strong wind risk can also be determined according to the vehicle's safety design. Moreover, the initial weights can be reassigned according to the actual usage scenarios. For example, when traveling on a rainy day, the wading weight can be temporarily increased. Suppose the vehicle has a relatively high wading risk and a strong wind resistance ability, the initial weights can be assigned as follows: the initial weight of the current water depth data is 0.7, and the initial weight of the current wind speed data is 0.3. Then, the initial weights are adjusted according to the vehicle's real-time operating state to obtain the target weights. For example: when driving at a high speed, the influence of the wind speed may be greater; when driving at a low speed, the influence of wading may be greater; high acceleration may increase the instability of the vehicle in strong winds; high angular rate may increase the risk of rollover of the vehicle during wading or in strong winds. Therefore, the rule for adjusting the weights can be preset as follows: if the vehicle speed is relatively high, increase the weight of the wind speed data and decrease the weight of the water depth data; if the longitudinal and lateral accelerations are relatively high, increase the weight of the wind speed data; if the angular rate is relatively high, increase the weight of the water depth data. Finally, a comprehensive risk assessment is performed on the current water depth data and the current wind speed data according to the target weights to obtain the comprehensive risk data. Suppose the currently collected data are: water depth 25 cm, wind speed 21 m / s, vehicle speed 70 km / h, longitudinal and lateral acceleration 0.6 g, and angular rate 9° / s. According to the vehicle design and actual usage scenarios, the initial weight of the water depth data is determined to be 0.7, and the initial weight of the current wind speed data is 0.3. Since the current vehicle speed is relatively high, the weight of the wind speed data needs to be increased to 0.4, and the weight of the water depth data needs to be decreased to 0.6. The eigenvalue quantization is performed on the water depth data and the wind speed data. If the considered range of the water depth data is from 0 to 50 cm, the quantization data of the water depth data is 5. If the considered range of the wind speed data is from 0 to 30 m / s, the quantization data of the wind speed data is 7. Thus, the comprehensive risk data can be calculated as 5×0.6 + 7×0.4 = 5.8. Then, the eigenvalue quantization is performed on the longitudinal and lateral accelerations and the angular rate. If the considered range of the longitudinal and lateral accelerations is from 0 to 1.5 g, the quantization data of the longitudinal and lateral accelerations is 4. If the considered range of the angular rate is from 0 to 15° / s, the quantization data of the angular rate is 6. Then, weights are assigned to each eigenvalue for weighted calculation. For example, the weight of the comprehensive risk data is 0.8, the weight of the longitudinal and lateral acceleration is 0.1, and the weight of the angular rate is 0.1. Based on this, the current comprehensive risk level is calculated as 5.8×0.8 + 4×0.1 + 6×0.1 = 5.64.

[0060] Optionally, eigenvalue quantization and comprehensive risk assessment are performed on the current water depth data and the current wind speed data according to the target weights, including: obtaining a wading risk index based on the quantization data of the current water depth data and its corresponding target weight; obtaining a strong wind risk index based on the quantization data of the current wind speed data and its corresponding target weight; comparing the wading risk index and the strong wind risk index to obtain a comprehensive risk assessment result.

[0061] In this embodiment, the wading risk index is the product of the quantization data of the current water depth data and its corresponding target weight, and the strong wind risk index is the product of the quantization data of the current wind speed data and its corresponding target weight. By comparing the magnitudes of the wading risk index and the strong wind risk index, it is possible to determine which risk has a greater impact on the vehicle. Specifically, it includes: if the wading risk index is greater than the strong wind risk index, then the wading risk is the main risk; if the strong wind risk index is greater than the wading risk index, then the strong wind risk is the main risk; if the wading risk index and the strong wind risk index are equal, then the two risks have an equivalent impact on the vehicle. According to the above comparison results, a comprehensive risk assessment result can be obtained, thereby determining the adjustment strategy for the suspension height. Specifically, it includes: if the wading risk is the main risk, then generate an instruction to raise the suspension height; if the strong wind risk is the main risk, then generate an instruction to lower the suspension height; if the two risks have an equivalent impact on the vehicle, then make a further judgment based on the risk level, select the suspension adjustment strategy corresponding to the higher risk level, or prompt the user to make a selection. For example, the quantization data of the current water depth data is 5, and the target weight of the water depth data is 0.6, then the wading risk index is 3; the quantization data of the current wind speed data is 7, and the target weight of the wind speed data is 0.4, then the strong wind risk index is 2.8. Therefore, the wading risk is the main risk of this comprehensive risk assessment.

[0062] Optionally, a target suspension adjustment instruction is generated according to the current risk level, including: determining a suspension adjustment strategy according to the current risk level; generating a target suspension adjustment instruction according to the suspension adjustment strategy; the target suspension adjustment instruction includes an adjustment height and an adjustment direction.

[0063] In this embodiment, different risk levels correspond to differentiated suspension adjustment strategies, such as the height adjustment range and the adjustment speed, which can reduce unnecessary suspension actions while ensuring safety, and optimize energy consumption and comfort. For example, the wading risk level is associated with the suspension lift amplitude. When the wading risk level is 2, the suspension lift amplitude is 20 mm; when the wading risk level is 8, the suspension lift amplitude is 80 mm. In this way, the situation of insufficient height or excessive lift caused by a fixed lift value can be avoided, the wading safety can be ensured, and water ingress into the air intake can be prevented. The high wind risk level is associated with the suspension lowering amplitude. For example, when the high wind risk level is 1, the suspension lowering amplitude is 5 mm; when the high wind risk level is 7, the suspension lowering height is 35 mm. In this way, the wind resistance coefficient of the vehicle can be reduced when encountering strong winds, the roll probability can be reduced by lowering the center of gravity, and the stability during high-speed driving can be improved. For the comprehensive risk level, the conflict problem between the wading scenario and the high wind scenario needs to be considered to prevent repeated lifting and lowering triggered by a single risk. For example, when the vehicle encounters gusts and fluctuating water depths at the same time, the action with a higher safety level is preferably selected. According to the main risk in the comprehensive risk assessment, a specific suspension adjustment strategy can be determined. For example, when the main risk is the wading risk, the suspension needs to be lifted; when the main risk is the high wind risk, the suspension needs to be lowered.

[0064] Optionally, the control method further includes: after generating a suspension adjustment instruction, sending the suspension adjustment instruction to the user for confirmation; and determining whether to execute the suspension adjustment instruction according to the user's confirmation result.

[0065] In this embodiment, in combination with Figure 3 and Figure 4 as shown, according to different wading risk levels, risk warnings are given to the user through the interaction terminal in different colors, and the user is prompted whether to adjust the vehicle body height. Then the user can choose whether to adjust according to the need. When the user selects "Yes", the suspension will be lifted to adjust the vehicle body height, and the maximum adjustment range of the vehicle body is subject to the vehicle design. At the same time, the adjustment state of the vehicle is displayed to the user, and the wading depth level and color are displayed in real time according to the actual state of the vehicle body. When the vehicle is stationary and the wading-related sensors detect that the vehicle has a wading risk, signals such as the wading risk level, color, and whether to adjust the vehicle body height request are transmitted to the user's mobile phone APP and displayed. The user can choose whether to turn on the vehicle body height adjustment through the mobile phone APP, and the adjustment state and the current wading level and color are also displayed to the user APP. In combination with Figure 5 and Figure 6As shown, according to different high wind risk levels, signals such as the high wind risk level and adjustment requests can also be sent to the user through the interaction terminal for risk warnings. The user can then choose whether to adjust according to their needs. When the user selects "Yes", the rear suspension will adjust in real time and the vehicle body will be lowered. The maximum adjustment range of the vehicle body is subject to the vehicle design. At the same time, the adjustment state of the vehicle is displayed to the user. When the vehicle is stationary, if it encounters environmental conditions such as hurricanes, after a large wind speed warning signal is generated, a suspension system adjustment request signal is actively sent to the user APP. After the user confirms, the suspension makes an active adjustment to lower the vehicle body height.

[0066] Optionally, the control method further includes: after adjusting the height of the suspension system according to the suspension adjustment instruction, obtaining the feedback status of the stability and safety of the vehicle; and adjusting the height of the suspension system again according to the feedback status.

[0067] In this embodiment, through the real-time feedback and secondary adjustment mechanism, dynamic optimization and fault tolerance enhancement of suspension control can be achieved to cope with the dynamic changes in complex environments, such as sudden waterlogging or gust intensification, and identify and correct the deficiencies or failures of the first adjustment. After the first adjustment, the stability and safety of the vehicle are monitored, such as the IMU yaw angular velocity, suspension displacement sensor, continuous water depth reading of the wading sensor, wind speed change, etc., to verify the adjustment effect and make fine adjustments. For example: after the suspension is raised for the first time, if it is detected that the lateral swing of the vehicle body still exceeds the threshold, the height is raised by 5% for the second time; after the suspension is lowered to resist the wind, if the wind speed sensor shows a sudden decrease in wind force, the height is automatically adjusted back to the comfortable position.

[0068] Combined with Figure 7 As shown, an embodiment of the present disclosure provides a control device 600 for a vehicle suspension system, including a processor 700 and a memory 701, and may further include a communication interface 702 and a bus 703. Among them, the processor 700, the communication interface 702, and the memory 701 can communicate with each other through the bus 703. The communication interface 702 can be used for information transmission. The processor 700 can call the logical instructions in the memory 701 to execute the control method for the vehicle suspension system in the above embodiment.

[0069] In addition, when the logical instructions in the above-mentioned memory 701 are implemented in the form of a software functional unit and sold or used as an independent product, they can be stored in a computer-readable storage medium.

[0070] The memory 701, being a computer-readable storage medium, can be used to store software programs and computer-executable programs, such as the program instructions / modules corresponding to the methods in the embodiments of the present disclosure. The processor 700 executes functional applications and data processing by running the program instructions / modules stored in the memory 701, that is, implements the control method for the vehicle suspension system in the above method embodiments.

[0071] The memory 701 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the terminal device, etc. In addition, the memory 701 may include high-speed random access memory and may also include non-volatile memory.

[0072] Combined with Figure 8 As shown, the embodiments of the present disclosure provide a control system 800 for a vehicle suspension system, including: an environmental sensor module 801, a vehicle sensor module 802, a suspension height adjustment controller 803, and a suspension adjustment actuator 804. The environmental sensor module 801 is configured to obtain risk environment data that affects vehicle driving safety. The vehicle sensor module 802 is configured to obtain vehicle operation data related to vehicle driving safety. The suspension height adjustment controller 803 is configured to determine the current risk level of the vehicle according to the risk environment data and the vehicle operation data, and generate a target suspension adjustment instruction according to the current risk level. The suspension adjustment actuator 804 is configured to adjust the vehicle suspension system according to the target suspension adjustment instruction. The environmental sensor module 801 and the vehicle sensor module 802 are connected to the suspension height adjustment controller 803 through a gateway to realize signal interaction. The suspension height adjustment controller 803 generates a suspension adjustment instruction, and realizes the height adjustment of the suspension system through the suspension adjustment actuator 804, including the left front suspension height adjustment, the right front suspension height adjustment, the left rear suspension height adjustment, and the right rear suspension height adjustment. The suspension height adjustment controller 803 can also obtain the suspension adjustment status feedback returned by the suspension adjustment actuator 804.

[0073] Optionally, the environmental sensor module 801 includes a wading sensor 811 and a wind speed sensor 821. The wading sensor 811 is configured to obtain the wading data of the vehicle. The wind speed sensor 821 is configured to obtain the wind speed data of the vehicle. When the vehicle is powered off, the wading sensor 811, the wind speed sensor 821, and related controllers are still in the wake-up state, ensuring that the vehicle can also collect data around the vehicle after being powered off, and realizing the height adjustment of the suspension system.

[0074] Optionally, the control system 800 further includes a human-machine interaction module 805, which is connected to the suspension height adjustment controller 803 through a gateway. The human-machine interaction module 805 is configured to send suspension adjustment instructions to the user for confirmation. In combination with Figure 9 As shown, the suspension height adjustment controller 803 receives vehicle signal data such as vehicle speed, wheel speed signal, steering angle, steering rate, power status, longitudinal acceleration, lateral acceleration, and yaw rate, as well as water depth level signal and wind speed level signal through CAN signals, and receives left front body height signal, right front body height signal, left rear body height signal, and right rear body height signal and other body height states through sensor signals. Then, according to the APP authorization control signal or the in-vehicle computer authorization control signal, the suspension height is adjusted through the suspension adjustment actuator 804. Then, the suspension height adjustment controller 803 feeds back the left front body height adjustment state, right front body height adjustment state, left rear body height adjustment state, right rear body height adjustment state, vehicle body wading state, and out-of-vehicle wind speed state to the human-machine interaction module 805 for display on the instrument panel and interaction through the APP. In addition, in the event of a failure in the suspension system, the suspension height adjustment controller 803 will also feed back a suspension failure signal to the human-machine interaction module 805.

[0075] Optionally, the human-machine interaction module 805 includes an in-vehicle computer system 815 and a mobile phone APP 825.

[0076] An embodiment of the present disclosure provides a vehicle, including: a vehicle body; a vehicle suspension system disposed on the vehicle body; and a control system for the vehicle suspension system as described above, disposed on the vehicle body and connected to the vehicle suspension system. The described setting relationship not only includes being placed inside the vehicle, but also includes installation and connection with other components of the vehicle, including but not limited to physical connection, electrical connection, or signal transmission connection, etc.

[0077] An embodiment of the present disclosure provides a computer-readable storage medium storing computer-executable instructions, and the computer-executable instructions are configured to execute the above-mentioned control method for the vehicle suspension system.

[0078] An embodiment of the present disclosure provides a computer program product, the computer program product includes a computer program stored on a computer-readable storage medium, the computer program includes program instructions, and when the program instructions are executed by a computer, the computer is caused to execute the above-mentioned control method for the vehicle suspension system.

[0079] The above-mentioned computer-readable storage medium may be a transient computer-readable storage medium or a non-transient computer-readable storage medium.

[0080] The technical solution of the embodiments of the present disclosure can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes one or more instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in the embodiments of the present disclosure. The aforementioned storage medium may be a non-transitory storage medium, including: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical discs, or may also be a transient storage medium.

[0081] The above description and the drawings fully illustrate the embodiments of the present disclosure, enabling those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, process, and other changes. Embodiments merely represent possible variations. Unless explicitly required, individual components and functions are optional, and the order of operations may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the terms used in this application are only for describing embodiments and do not limit the technical solutions described in this application. As used in the technical solutions described in this application, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to also include the plural forms. Similarly, as used in this application, the term "and / or" refers to any and all possible combinations including one or more of the associated listed items. Additionally, when used in this application, the term "comprise" and its variants "comprises" and / or "comprising", etc., refer to the presence of the stated features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or groupings of these. Without further limitation, an element defined by the statement "comprising one..." does not exclude the presence of additional identical elements in the process, method, or device including the element. In this article, each embodiment may focus on the differences from other embodiments, and the same or similar parts between the embodiments may be referred to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method part disclosed in the embodiments, the relevant parts may refer to the description of the method part.

[0082] Those skilled in the art will realize that the units and algorithm steps of each example described in connection with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software can depend on the specific application and design constraints of the technical solution. The skilled person can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of the embodiments of the present disclosure. The skilled person can clearly understand that for the convenience and conciseness of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0083] In the embodiments disclosed herein, the disclosed methods, products (including but not limited to devices, equipment, etc.) can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units can be merely a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Additionally, the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces, and the indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms. The units described as separate components can be or can not be physically separated, and the components displayed as units can be or can not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to implement this embodiment. Additionally, in the embodiments of the present disclosure, the various functional units can be integrated in one processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0084] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a portion of code, which contains one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions noted in the blocks may occur in a different order than noted in the accompanying drawings. For example, two consecutive blocks may in fact be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may in fact be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented by a dedicated hardware-based system that performs the specified functions or actions, or may be implemented by a combination of dedicated hardware and computer instructions.

Claims

1. A control method for a vehicle suspension system, characterized in that, Including: Obtain risk environment data affecting vehicle driving safety; Obtain vehicle operation data related to vehicle driving safety; Determine the current risk level of the vehicle according to the risk environment data and the vehicle operation data; Generate a target suspension adjustment instruction according to the current risk level to adjust the vehicle suspension system according to the target suspension adjustment instruction.

2. The control method according to claim 1, wherein When the risk environment data includes vehicle wading data, determine the current risk level of the vehicle according to the risk environment data and the vehicle operation data, including: Determine the current water depth data in the vehicle wading data, and determine the longitudinal and lateral accelerations and the angular rate in the vehicle operation data; Perform eigenvalue quantization on the current water depth data, the longitudinal and lateral accelerations, and the angular rate, and calculate the current wading risk level of the vehicle according to the quantization data.

3. The control method according to claim 1, wherein When the risk environment data includes vehicle surrounding wind speed data, determine the current risk level of the vehicle according to the risk environment data and the vehicle operation data, including: Determine the current wind speed data in the vehicle surrounding wind speed data, and determine the longitudinal and lateral accelerations and the angular rate in the vehicle operation data; Perform eigenvalue quantization on the current wind speed data, the longitudinal and lateral accelerations, and the angular rate, and calculate the current high wind risk level of the vehicle according to the quantization data.

4. The control method according to claim 1, wherein When the risk environment data includes vehicle wading data and vehicle surrounding wind speed data, determine the current risk level of the vehicle according to the risk environment data and the vehicle operation data, including: Determine the current water depth data in the vehicle wading data, the current wind speed data in the vehicle surrounding wind speed data, and determine the longitudinal and lateral accelerations and the angular rate in the vehicle operation data; Perform eigenvalue quantization and comprehensive risk assessment on the current water depth data and the current wind speed data to obtain comprehensive risk data; Perform eigenvalue quantization on the longitudinal and lateral accelerations and the angular rate, and calculate the current comprehensive risk level of the vehicle according to the quantization data and the comprehensive risk data.

5. The control method according to claim 4, wherein Perform eigenvalue quantization and comprehensive risk assessment on the current water depth data and the current wind speed data to obtain comprehensive risk data, including: Assign initial weights to the current water depth data and the current wind speed data according to the vehicle design and the actual use scenario; Adjust the initial weights according to the real-time operation state of the vehicle to obtain target weights; Perform eigenvalue quantization and comprehensive risk assessment on the current water depth data and the current wind speed data according to the target weights to obtain comprehensive risk data.

6. The control method according to claim 1, wherein Generate a target suspension adjustment instruction according to the current risk level, including: Determine a suspension adjustment strategy according to the current risk level; Generate a target suspension adjustment instruction according to the suspension adjustment strategy; the target suspension adjustment instruction includes an adjustment height and an adjustment direction.

7. The control method according to any one of claims 1 to 6, characterized in that Also including: After generating the target suspension adjustment instruction, send the target suspension adjustment instruction to the user for confirmation; Judge whether to execute the target suspension adjustment instruction according to the user's confirmation result.

8. A control device for a vehicle suspension system, comprising a processor and a memory storing program instructions, characterized in that, The processor is configured to execute the control method for the vehicle suspension system according to any one of claims 1 to 7 when running the program instructions.

9. A control system for a vehicle suspension system, characterized in that, Including: An environment sensor module configured to obtain risk environment data affecting vehicle driving safety; A vehicle sensor module configured to obtain vehicle operation data related to vehicle driving safety; A suspension height adjustment controller, configured to determine the current risk level of the vehicle according to risk environment data and vehicle operation data, and generate a target suspension adjustment instruction according to the current risk level; A suspension adjustment actuator, configured to adjust the vehicle suspension system according to the target suspension adjustment instruction.

10. A vehicle, characterized in that, Comprising: A vehicle body; A vehicle suspension system, disposed on the vehicle body; The control system for a vehicle suspension system according to claim 9, disposed on the vehicle body and connected to the vehicle suspension system.

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