Active control method and system for suspension unit and braking unit

Abstract

The present application belongs to the technical field of vehicle engineering, and specifically relates to an active control method and system for a suspension unit and a braking unit. The active control method comprises: a connected traffic infrastructure collects traffic light information and road camera information, and sends same to a cloud computing platform, and a control module of a vehicle collects vehicle speed information, acceleration information, GPS positioning information and navigation information of the vehicle, and sends same to the cloud computing platform; on the basis of the received traffic light information, the received road camera information, the received GPS positioning information and the received navigation information, the cloud computing platform performs detection, so as to obtain a distance to a nearest obstacle of the vehicle; on the basis of the obtained distance, the cloud computing platform determines whether to perform active control on a suspension unit and a braking unit of the vehicle; and if yes, on the basis of said distance, the vehicle speed information and the acceleration information, the cloud computing platform obtains suspension unit control information and braking unit control information corresponding to the vehicle, and sends same to the control module for control of the suspension unit and the braking unit of the vehicle.

Description

Active control method and system for suspension unit and brake unit Cross-reference to related applications

[0001] This application claims priority to Chinese Patent Application No. 202411029697.5, filed on July 30, 2024, the entire contents of which are incorporated herein by reference. TECHNICAL FIELD

[0002] The present application belongs to the technical field of vehicle engineering, and specifically relates to an active control method and system for a suspension unit and a brake unit. BACKGROUND

[0003] With the continuous improvement of vehicle automation level, the ride comfort of the vehicle in braking and acceleration conditions has become an important aspect of evaluating the driving performance of the vehicle, and the ride comfort of the vehicle in braking condition is a key focus. The ride comfort in braking condition refers to the discomfort of the driver and passenger caused by the change of the longitudinal dynamics of the vehicle during braking. From the control mechanism, the suspension unit and the brake unit of the vehicle are the key factors affecting the ride comfort of the vehicle in braking condition.

[0004] In order to improve the ride comfort of the vehicle in braking condition, the passive control method of the suspension unit and the brake unit is usually used in the prior art. A control module is set up to control the suspension unit and the brake unit of the vehicle according to the current speed and acceleration of the vehicle when the vehicle is in an emergency (emergency braking). However, since the passive control method is only triggered in emergency braking, it cannot actively pre-control the suspension unit and the brake unit of the vehicle in response to the driving obstacles in front of the vehicle (including traffic lights, stationary vehicles, electric vehicles, pedestrians and other obstacles to vehicle driving), which still has deficiencies in improving the ride comfort of the vehicle. SUMMARY

[0005] In order to solve the above-mentioned defects of the prior art, the present application provides an active control method and system for a suspension unit and a brake unit to solve the technical problem that in the prior art, in order to improve the ride comfort of the vehicle in braking condition, the passive control method of the suspension unit and the brake unit is usually used, but the passive control method of the suspension unit and the brake unit is only triggered in emergency braking, and cannot actively pre-control the suspension unit and the brake unit of the vehicle in response to the driving obstacles in front of the vehicle (including traffic lights, stationary vehicles, electric vehicles, pedestrians and other obstacles to vehicle driving), which still has deficiencies in improving the ride comfort of the vehicle in braking condition.

[0006] In order to achieve the above-mentioned purpose, the technical scheme of the present application is as follows:

[0007] An active control method of a suspension unit and a brake unit, comprising the following steps:

[0008] Step 1: The networking traffic infrastructure collects traffic signal information and road camera information, and sends the traffic signal information and the road camera information to a cloud computing platform; a control module of a vehicle collects vehicle speed information, acceleration information, GPS positioning information and navigation information of the vehicle, and sends the vehicle speed information, the acceleration information, the GPS positioning information and the navigation information to the cloud computing platform;

[0009] Step 2: The cloud computing platform detects according to the received traffic signal information, road camera information, GPS positioning information and navigation information, and obtains a nearest obstacle distance value of the vehicle;

[0010] Step 3: The cloud computing platform judges whether to actively control the suspension unit and the brake unit of the vehicle according to the obtained nearest obstacle distance value; if yes, go to step 4; if no, return to step 1;

[0011] Step 4: The cloud computing platform obtains suspension unit control information and brake unit control information corresponding to the vehicle according to the obtained nearest obstacle distance value, and the received vehicle speed information and acceleration information, and sends the obtained suspension unit control information and brake unit control information to the control module of the vehicle;

[0012] Step 5: The control module controls the suspension unit and the brake unit of the vehicle according to the received suspension unit control information and brake unit control information.

[0013] The cloud computing platform is used to obtain the closest obstacle distance value (i.e. the distance value between the vehicle and the closest obstacle in front of the vehicle; wherein the obstacle in front of the vehicle includes but is not limited to traffic lights, stationary vehicles, electric vehicles, pedestrians and other obstacles that hinder the driving of the vehicle), and the cloud computing platform is further used to determine whether to actively control the suspension unit and the braking unit of the vehicle according to the obtained closest obstacle distance value; and after determining to actively control the suspension unit and the braking unit of the vehicle, the cloud computing platform obtains the suspension unit control information and the braking unit control information corresponding to the vehicle according to the obtained closest obstacle distance value, the received vehicle speed information and the received acceleration information, and sends the obtained suspension unit control information and braking unit control information to the control module of the vehicle; finally, the control module controls the suspension unit and the braking unit of the vehicle according to the received suspension unit control information and braking unit control information. The active control method of the suspension unit and the braking unit provided by the present application can obtain the related information of the obstacle in front of the vehicle by using the networked transportation infrastructure, actively pre-control the suspension unit and the braking unit of the vehicle in view of the driving obstacles in front of the vehicle (including traffic lights, stationary vehicles, electric vehicles, pedestrians and other obstacles that hinder the driving of the vehicle), and effectively improve the ride comfort of the vehicle.

[0014] Further, the networked transportation infrastructure includes each traffic light in the transportation system and each road camera, each traffic light is used to collect the traffic light information, and each road camera is used to collect the road camera information.

[0015] The traffic light information includes the switching period signal and the first GPS signal of each traffic light in the transportation system, and the road camera information includes the image signal and the second GPS signal of each road camera in the transportation system.

[0016] By making the traffic light information include the switching period signal and the first GPS signal of each traffic light in the transportation system, the cloud computing platform can master the signal switching period and the GPS positioning of each traffic light in the transportation system; when the closest obstacle in front of the vehicle is a traffic light, the cloud computing platform can provide more accurate judgment basis for determining whether to actively control the suspension unit and the braking unit of the vehicle (the cloud computing platform can determine whether the vehicle can pass the traffic light within the duration of the nearest green light according to the received vehicle speed information and acceleration information, and if the vehicle can pass the traffic light within the duration of the nearest green light, there is no need to actively control the suspension unit and the braking unit of the vehicle).

[0017] By making the road camera information include image signals and second GPS signals of each road camera in the traffic system, the cloud computing platform can identify other obstacles except traffic signal lights from the received image signals, and obtain GPS positions of the other obstacles according to the second GPS signals sent by the road cameras that take pictures of any of the other obstacles, and further obtain GPS positions of each of the identified other obstacles, and further obtain a distance value between the vehicle and the nearest other obstacle.

[0018] The other obstacles include but are not limited to: stationary vehicles, electric vehicles, pedestrians and other obstacles that hinder the driving of vehicles.

[0019] Further, the step 2 includes the following sub-steps:

[0020] S201: The cloud computing platform obtains a first distance value between the vehicle and the nearest traffic signal light, and a second distance value between the vehicle and the nearest other obstacle, according to the received traffic signal light information, road camera information, GPS positioning information and navigation information.

[0021] S202: The cloud computing platform takes the smaller distance value between the first distance value and the second distance value as the nearest obstacle distance value.

[0022] Further, in the sub-step S201, the cloud computing platform obtains the first distance value according to the GPS positioning information, the navigation information and the first GPS signals of each traffic signal light.

[0023] The cloud computing platform obtains the second distance value according to the GPS positioning information, the navigation information and the image signals and second GPS signals of each road camera.

[0024] Further, the method for obtaining the second distance value includes:

[0025] The cloud computing platform identifies other obstacles taken pictures of by each road camera according to the image signals of each road camera.

[0026] The cloud computing platform obtains distance values between each road camera that takes pictures of the other obstacles and the vehicle according to the GPS positioning information, the navigation information and the second GPS signals of each traffic signal light.

[0027] The cloud computing platform takes the minimum value among the distance values between each road camera that takes pictures of the other obstacles and the vehicle as the second distance value.

[0028] Further, if the cloud computing platform takes the first distance value as the nearest obstacle distance value, the step 3 includes the following sub-steps:

[0029] S301: The cloud computing platform determines according to the received vehicle speed information, acceleration information and the switching period signal of the nearest traffic signal, if the vehicle can pass the nearest traffic signal within the nearest green light duration, returns to the step 1; otherwise, enters the sub-step S302.

[0030] S302: The cloud computing platform determines according to the obtained nearest obstacle distance value, if the nearest obstacle distance value is greater than the decision distance threshold, determines not to actively control the suspension unit and the braking unit of the vehicle, and returns to the step 1; if the nearest obstacle distance value is not greater than the decision distance threshold, determines to actively control the suspension unit and the braking unit of the vehicle, and enters the step 4.

[0031] By using the cloud computing platform to determine whether the vehicle can pass the nearest traffic signal within the nearest green light duration according to the received vehicle speed information, acceleration information and the switching period signal of the nearest traffic signal, it can avoid the false operation of actively controlling the suspension unit and the braking unit of the vehicle when the vehicle can pass the nearest traffic signal within the nearest green light duration, and only when it is determined that the vehicle cannot pass the nearest traffic signal within the nearest green light duration, the next step is entered.

[0032] Through the above method, when the cloud computing platform takes the first distance value as the nearest obstacle distance value, and determines that the vehicle cannot pass the nearest traffic signal within the nearest green light duration, and actively controls the suspension unit and the braking unit of the vehicle, the cloud computing platform can obtain the suspension unit control information and the braking unit control information corresponding to the vehicle according to the obtained nearest obstacle distance value, and the received vehicle speed information and acceleration information, to control the vehicle to stop before reaching the nearest traffic signal, and ensure the riding comfort.

[0033] The cloud computing platform can also obtain the suspension unit control information and the brake unit control information corresponding to the vehicle according to the obtained recent obstacle distance value, the received vehicle speed information and acceleration information, and the received switching cycle signal of the recent traffic signal light, so as to control the vehicle to slow down and pass through the recent traffic signal light within the next green light duration (the green light duration after the recent green light duration), thereby reducing the waiting time of the vehicle, saving the energy lost during starting and stopping of the vehicle, and improving the riding comfort of the passengers.

[0034] Further, in the step 3, if the cloud computing platform takes the second distance value as the recent obstacle distance value, the cloud computing platform judges according to the obtained recent obstacle distance value, if the recent obstacle distance value is greater than a decision distance threshold value, it is determined that the suspension unit and the brake unit of the vehicle are not actively controlled, and the step 1 is returned; if the recent obstacle distance value is not greater than the decision distance threshold value, it is determined that the suspension unit and the brake unit of the vehicle are actively controlled, and the step 4 is entered.

[0035] Further, in the step 5, the control module adjusts the height, stiffness and damping force of the front and rear suspensions of the suspension unit according to the received suspension unit control information.

[0036] Further, the brake unit control information includes a brake force-time curve.

[0037] In the step 5, the control module controls the brake unit of the vehicle according to the received brake unit control information.

[0038] According to the active control method of the suspension unit and the brake unit provided in the present application, the present application further provides an active control system of the suspension unit and the brake unit, which comprises a networked traffic infrastructure, a cloud computing platform, and a control module, a suspension unit and a brake unit of a vehicle.

[0039] The networked traffic infrastructure and the control module are in communication connection with the cloud computing platform, and the suspension unit and the brake unit are in communication connection with the control module.

[0040] The networked traffic infrastructure is used to collect traffic signal light information and road camera information, and send the traffic signal light information and the road camera information to the cloud computing platform; and the control module is used to collect vehicle speed information, acceleration information, GPS positioning information and navigation information of the vehicle, and send the vehicle speed information, the acceleration information, the GPS positioning information and the navigation information to the cloud computing platform.

[0041] The cloud computing platform is configured to determine whether to actively control the suspension unit and the brake unit according to the received vehicle speed information, acceleration information, traffic signal information, road camera information, GPS positioning information and navigation information, and obtain suspension unit control information and brake unit control information corresponding to the vehicle when determining to actively control the suspension unit and the brake unit.

[0042] The cloud computing platform is further configured to send the obtained suspension unit control information and brake unit control information to the control module.

[0043] The control module controls the suspension unit and the brake unit according to the received suspension unit control information and brake unit control information.

[0044] Further, the networked transportation infrastructure includes various traffic signals and various road cameras in the transportation system, each traffic signal being configured to collect the traffic signal information, and each road camera being configured to collect the road camera information.

[0045] The traffic signal information includes switching cycle signals and first GPS signals of each traffic signal in the transportation system, and the road camera information includes image signals and second GPS signals of each road camera in the transportation system.

[0046] Further, the suspension unit includes a front suspension and a rear suspension.

[0047] The front suspension includes a front suspension bracket body and two first multi-cavity air springs symmetrically arranged on the front suspension bracket body, and the rear suspension includes a rear suspension bracket body and two second multi-cavity air springs symmetrically arranged on the front suspension bracket body.

[0048] By arranging the four damping mechanisms of the suspension unit as two first multi-cavity air springs and two second multi-cavity air springs (i.e., four multi-cavity air springs), the functions of adjusting the height, stiffness and damping force of the front and rear suspensions of the multi-cavity air springs can be utilized, so that the control module can adjust the height, stiffness and damping force of the front and rear suspensions of the suspension unit according to the received suspension unit control information. BRIEF DESCRIPTION OF DRAWINGS

[0049] In order to more clearly illustrate the technical solutions of the present application, the following will briefly introduce the drawings needed in the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can also be obtained by those skilled in the art without creative labor.

[0050] Fig. 1 is a flow chart of the active control method of the suspension unit and the braking unit in embodiment 1. DETAILED DESCRIPTION

[0051] The technical solutions in the embodiments of the present application will be described clearly and completely below in combination with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments of the present application.

[0052] Embodiment 1:

[0053] As shown in Fig. 1, embodiment 1 provides an active control method of a suspension unit and a braking unit, comprising the following steps:

[0054] Step 1: The networked traffic infrastructure collects traffic signal information and road camera information, and sends the traffic signal information and the road camera information to a cloud computing platform; the control module of the vehicle collects vehicle speed information, acceleration information, GPS positioning information and navigation information, and sends the vehicle speed information, the acceleration information, the GPS positioning information and the navigation information to the cloud computing platform;

[0055] Step 2: The cloud computing platform detects according to the received traffic signal information, road camera information, GPS positioning information and navigation information, and obtains a nearest obstacle distance value of the vehicle;

[0056] Step 3: The cloud computing platform judges whether to actively control the suspension unit and the braking unit of the vehicle according to the obtained nearest obstacle distance value; if yes, it goes to step 4; if no, it returns to step 1;

[0057] Step 4: The cloud computing platform obtains the suspension unit control information and the braking unit control information corresponding to the vehicle according to the obtained nearest obstacle distance value, and the received vehicle speed information and acceleration information, and sends the obtained suspension unit control information and braking unit control information to the control module of the vehicle;

[0058] Step 5: The control module controls the suspension unit and the braking unit of the vehicle according to the received suspension unit control information and braking unit control information.

[0059] The cloud computing platform obtains a nearest obstacle distance value (i.e., a distance value between the vehicle and the nearest obstacle in front of the vehicle; wherein the obstacle in front of the vehicle includes but is not limited to traffic lights, stalled vehicles, electric vehicles, pedestrians, and other obstacles that hinder the driving of the vehicle), and then determines whether to actively control the suspension unit and the braking unit of the vehicle according to the obtained nearest obstacle distance value. After determining to actively control the suspension unit and the braking unit of the vehicle, the cloud computing platform obtains the suspension unit control information and the braking unit control information corresponding to the vehicle according to the obtained nearest obstacle distance value, the received vehicle speed information, and the received acceleration information, and sends the obtained suspension unit control information and braking unit control information to the control module of the vehicle. Finally, the control module controls the suspension unit and the braking unit of the vehicle according to the received suspension unit control information and braking unit control information. The active control method of the suspension unit and the braking unit provided by the present application can obtain the relevant information of the obstacle in front of the vehicle by using the connected transportation infrastructure, actively pre-control the suspension unit and the braking unit of the vehicle according to the driving obstacles in front of the vehicle (including traffic lights, stalled vehicles, electric vehicles, pedestrians, and other obstacles that hinder the driving of the vehicle), and effectively improve the ride comfort of the vehicle.

[0060] In the braking working condition of the vehicle, the specific method of controlling the suspension unit and the braking unit of the vehicle to improve the ride comfort of the driver and the passenger on the vehicle belongs to the conventional technology in the field, and can refer to the paper "Review of Automotive Braking Comfort Control", Science Technology and Engineering, 2022, 22(17): 6790-6801.

[0061] In one of the embodiments, the connected transportation infrastructure includes traffic lights and road cameras in the transportation system, the traffic lights are used to collect traffic light information, and the road cameras are used to collect road camera information.

[0062] The traffic light information includes switching cycle signals and first GPS signals of the traffic lights in the transportation system, and the road camera information includes image signals and second GPS signals of the road cameras in the transportation system.

[0063] The traffic signal lamp information includes the switching cycle signal of each traffic signal lamp in the traffic system and the first GPS signal, so that the cloud computing platform can master the signal switching cycle and GPS positioning of each traffic signal lamp in the traffic system; when the nearest obstacle in front of the vehicle is a traffic signal lamp, more accurate judgment basis is provided for whether to actively control the suspension unit and the braking unit of the vehicle (the cloud computing platform will judge whether the vehicle can pass the traffic signal lamp within the duration of the nearest green light according to the received vehicle speed information and acceleration information, and if the vehicle can pass the traffic signal lamp within the duration of the nearest green light, the suspension unit and the braking unit of the vehicle do not need to be actively controlled).

[0064] The road camera information includes the image signal of each road camera in the traffic system and the second GPS signal, so that the cloud computing platform can identify other obstacles in addition to traffic signal lamps from the received image signal, and obtain the GPS positioning of the other obstacles according to the second GPS signal sent by the road camera that captures any other obstacle, and further obtain the GPS positioning of each identified other obstacle, and further obtain the distance value between the vehicle and the nearest other obstacle.

[0065] Among them, the other obstacles include but are not limited to: stationary vehicles, electric vehicles, pedestrians and other obstacles that hinder the driving of vehicles.

[0066] Specifically, in embodiment 1, step 2 includes the following sub-steps:

[0067] S201: The cloud computing platform obtains the first distance value between the vehicle and the nearest traffic signal lamp, and the second distance value between the vehicle and the nearest other obstacle according to the received traffic signal lamp information, road camera information, GPS positioning information and navigation information;

[0068] S202: The cloud computing platform takes the smaller distance value between the first distance value and the second distance value as the nearest obstacle distance value.

[0069] Specifically, in embodiment 1, in sub-step S201, the cloud computing platform obtains the first distance value according to the GPS positioning information, the navigation information and the first GPS signal of each traffic signal lamp;

[0070] The cloud computing platform obtains the second distance value according to the GPS positioning information, the navigation information and the image signal and the second GPS signal of each road camera.

[0071] Specifically, in embodiment 1, the method for obtaining the second distance value includes:

[0072] The cloud computing platform identifies other obstacles captured by each road camera according to the image signal of each road camera;

[0073] The cloud computing platform obtains a distance value between each road camera that captures other obstacles and the vehicle according to the GPS positioning information, navigation information, and the second GPS signal of each traffic signal light;

[0074] The cloud computing platform takes the minimum value among the distance values between each road camera that captures other obstacles and the vehicle as a second distance value.

[0075] Specifically, in the first embodiment, if the cloud computing platform takes the first distance value as the nearest obstacle distance value, step 3 includes the following sub-steps:

[0076] S301: The cloud computing platform determines according to the received vehicle speed information, acceleration information, and switching period signal of the nearest traffic signal light. If it is determined that the vehicle can pass the nearest traffic signal light within the duration of the nearest green light, it returns to step 1; otherwise, it proceeds to sub-step S302;

[0077] S302: The cloud computing platform determines according to the obtained nearest obstacle distance value. If the nearest obstacle distance value is greater than the decision distance threshold, it determines not to actively control the suspension unit and the braking unit of the vehicle, and returns to step 1; if the nearest obstacle distance value is not greater than the decision distance threshold, it determines to actively control the suspension unit and the braking unit of the vehicle, and proceeds to step 4.

[0078] By using the cloud computing platform to determine whether the vehicle can pass the nearest traffic signal light within the duration of the nearest green light according to the received vehicle speed information, acceleration information, and switching period signal of the nearest traffic signal light, it can avoid the false operation of actively controlling the suspension unit and the braking unit of the vehicle when the vehicle can pass the nearest traffic signal light within the duration of the nearest green light, and only proceed to the next step of determination when it is determined that the vehicle cannot pass the nearest traffic signal light within the duration of the nearest green light.

[0079] Through the above method, when the cloud computing platform takes the first distance value as the nearest obstacle distance value, and determines that the vehicle cannot pass the nearest traffic signal light within the duration of the nearest green light, and actively controls the suspension unit and the braking unit of the vehicle, the cloud computing platform can obtain the suspension unit control information and the braking unit control information corresponding to the vehicle according to the obtained nearest obstacle distance value, and the received vehicle speed information and acceleration information, to control the vehicle to stop before reaching the nearest traffic signal light, and ensure the comfort of the ride;

[0080] The cloud computing platform can also obtain the recent obstacle distance value, the received vehicle speed information and acceleration information, and the received switching period signal of the nearest traffic light, obtain the suspension unit control information and the brake unit control information corresponding to the vehicle to control the vehicle to slow down, and pass through the nearest traffic light within the next green light duration of the nearest traffic light (the green light duration after the nearest green light duration). The waiting time of the vehicle can be reduced, the energy loss during starting and stopping of the vehicle can be saved, and the riding comfort of the passengers can be improved.

[0081] Specifically, in embodiment 1, in step 3, if the cloud computing platform takes the second distance value as the recent obstacle distance value, the cloud computing platform judges according to the obtained recent obstacle distance value. If the recent obstacle distance value is greater than the decision distance threshold, it is determined that the suspension unit and the brake unit of the vehicle are not actively controlled, and returns to step 1; if the recent obstacle distance value is not greater than the decision distance threshold, it is determined that the suspension unit and the brake unit of the vehicle are actively controlled, and enters step 4.

[0082] Specifically, in embodiment 1, in step 5, the control module adjusts the height, stiffness and damping force of the front and rear suspensions of the suspension unit according to the received suspension unit control information.

[0083] In the braking working condition of the vehicle, by adjusting the height, stiffness and damping force of the front and rear suspensions of the suspension unit, the riding comfort of the vehicle in the braking working condition is improved. It can be referred to the paper "Review of Automobile Braking Comfort Control" Science Technology and Engineering, 2022, 22(17): 6790-6801.

[0084] Specifically, in embodiment 1, the brake unit control information includes a brake force-time curve.

[0085] In step 5, the control module controls the brake unit of the vehicle according to the received brake unit control information.

[0086] Embodiment 2:

[0087] According to the active control method of the suspension unit and the brake unit provided in embodiment 1, embodiment 2 provides an active control system of the suspension unit and the brake unit, which includes a networked transportation infrastructure, a cloud computing platform, and a control module, a suspension unit and a brake unit of a vehicle.

[0088] The networked transportation infrastructure and the control module are in communication connection with the cloud computing platform, and the suspension unit and the brake unit are in communication connection with the control module.

[0089] The networking traffic infrastructure is configured to collect traffic signal information and road camera information, and send the traffic signal information and the road camera information to a cloud computing platform; the control module is configured to collect vehicle speed information, acceleration information, GPS positioning information and navigation information of the vehicle, and send the vehicle speed information, the acceleration information, the GPS positioning information and the navigation information to the cloud computing platform;

[0090] The cloud computing platform is configured to determine whether to actively control the suspension unit and the braking unit according to the received vehicle speed information, acceleration information, traffic signal information, road camera information, GPS positioning information and navigation information, and obtain suspension unit control information and braking unit control information corresponding to the vehicle when it is determined to actively control the suspension unit and the braking unit;

[0091] The cloud computing platform is further configured to send the obtained suspension unit control information and braking unit control information to the control module;

[0092] The control module controls the suspension unit and the braking unit according to the received suspension unit control information and braking unit control information.

[0093] Specifically, in the second embodiment, the networking traffic infrastructure includes each traffic signal lamp and each road camera in the traffic system, each traffic signal lamp is configured to collect traffic signal information, and each road camera is configured to collect road camera information.

[0094] The traffic signal information includes switching cycle signals and first GPS signals of each traffic signal lamp in the traffic system, and the road camera information includes image signals and second GPS signals of each road camera in the traffic system.

[0095] Specifically, in the second embodiment, the suspension unit includes a front suspension and a rear suspension.

[0096] The front suspension includes a front suspension bracket body and two first multi-cavity air springs symmetrically arranged on the front suspension bracket body, and the rear suspension includes a rear suspension bracket body and two second multi-cavity air springs symmetrically arranged on the rear suspension bracket body.

[0097] By arranging the four damping mechanisms of the suspension unit as two first multi-cavity air springs and two second multi-cavity air springs (i.e., four multi-cavity air springs), the functions of adjusting the height, stiffness and damping force of the front and rear suspensions of the multi-cavity air springs can be utilized, so that the control module can adjust the height, stiffness and damping force of the front and rear suspensions of the suspension unit according to the received suspension unit control information.

[0098] The active control method and system of the suspension unit and the braking unit provided by the present application have at least the following technical effects or advantages:

[0099] 1. The system utilizes a cloud computing platform to obtain the nearest obstacle distance value (i.e., the distance between the vehicle and the nearest obstacle in front of it; obstacles in front of the vehicle include, but are not limited to, traffic lights, stopped vehicles, electric vehicles, pedestrians, and other debris obstructing the vehicle's movement). Based on this nearest obstacle distance value, the cloud computing platform determines whether to actively control the vehicle's suspension and braking systems. After determining to actively control the suspension and braking systems, the cloud computing platform uses the nearest obstacle distance value, along with received vehicle speed and acceleration information, to obtain the corresponding suspension and braking system control information. This information is then sent to the vehicle's control module. Finally, the control module controls the vehicle's suspension and braking systems based on the received suspension and braking system control information. The active control method for the suspension and braking units provided in this application can utilize networked traffic infrastructure to obtain relevant information about obstacles in front of the vehicle, and actively pre-control the vehicle's suspension and braking units for obstacles in front of the vehicle (including traffic lights, stopped vehicles, electric vehicles, pedestrians and other debris that obstruct the vehicle's movement), which can effectively improve the vehicle's ride comfort.

[0100] 2. By including the switching cycle signals of each traffic light in the traffic system and the first GPS signal in the traffic signal information, the cloud computing platform can grasp the signal switching cycle and GPS positioning of each traffic light in the traffic system; when the nearest obstacle in front of the vehicle is a traffic light, it provides a more accurate basis for judging whether the vehicle's suspension unit and braking unit need to be actively controlled (the cloud computing platform, together with the received vehicle speed information and acceleration information, determines whether the vehicle can pass through the traffic light within the nearest green light duration; if the vehicle can pass through the traffic light within the nearest green light duration, then there is no need to actively control the vehicle's suspension unit and braking unit).

[0101] 3. By including the image signals and second GPS signals from each road camera in the traffic system in the road camera information, the cloud computing platform can identify obstacles other than traffic lights from the received image signals, and obtain the GPS location of the other obstacle based on the second GPS signal sent by the road camera that captured any other obstacle, thereby obtaining the GPS location of each identified other obstacle, and then obtaining the distance value between the vehicle and the nearest other obstacle.

[0102] 4. By using a cloud computing platform to determine whether a vehicle can pass through the nearest traffic light within the nearest green light duration based on the received vehicle speed information, acceleration information, and the switching cycle signal of the nearest traffic light, it is possible to avoid erroneous active control of the vehicle's suspension and braking units when the vehicle can pass through the nearest traffic light within the nearest green light duration. The next step of judgment will only be taken when it is determined that the vehicle cannot pass through the nearest traffic light within the nearest green light duration.

[0103] Using the above method, after the cloud computing platform uses the first distance value as the nearest obstacle distance value and determines that the vehicle cannot pass the nearest traffic light within the nearest green light duration, and actively controls the vehicle's suspension unit and braking unit, the cloud computing platform can obtain the corresponding suspension unit control information and braking unit control information of the vehicle based on the obtained nearest obstacle distance value, as well as the received vehicle speed information and acceleration information, so as to control the vehicle to stop before reaching the nearest traffic light and ensure ride comfort.

[0104] The cloud computing platform can also obtain the corresponding suspension unit control information and braking unit control information of the vehicle based on the obtained nearest obstacle distance value, as well as the received vehicle speed and acceleration information, and together with the received traffic light switching cycle signal, to control the vehicle to decelerate. It can pass through the nearest traffic light within the next green light duration (the green light duration after the nearest green light duration). This can reduce vehicle waiting time, save energy lost when starting and stopping the vehicle, and improve the ride comfort of the driver and passengers.

[0105] 5. By setting the four damping mechanisms of the suspension unit as two first multi-cavity air springs and two second multi-cavity air springs (that is, four multi-cavity air springs), the function of multi-cavity air springs to adjust the height, stiffness and damping force of the front and rear suspensions can be utilized, so that the control module can adjust the height, stiffness and damping force of the front and rear suspensions of the suspension unit according to the received suspension unit control information.

[0106] The above are merely specific application examples of this application and do not constitute any limitation on the scope of protection of this application. All technical solutions formed by equivalent transformation or equivalent substitution fall within the scope of protection of this application.

Claims

1. An active control method for a suspension unit and a braking unit, comprising the following steps: Step 1: The networked transportation infrastructure collects traffic light information and road camera information, and sends the traffic light information and road camera information to the cloud computing platform; the vehicle control module collects the vehicle speed information, acceleration information, GPS positioning information and navigation information, and sends the speed information, acceleration information, GPS positioning information and navigation information to the cloud computing platform; Step 2: The cloud computing platform performs detection based on the received traffic light information, road camera information, GPS positioning information, and navigation information to obtain the nearest obstacle distance value for the vehicle; Step 3: The cloud computing platform determines whether to actively control the vehicle's suspension unit and braking unit based on the obtained nearest obstacle distance value; if yes, proceed to step 4; if no, return to step 1. Step 4: The cloud computing platform obtains the suspension unit control information and braking unit control information corresponding to the vehicle based on the obtained nearest obstacle distance value, the received vehicle speed information and acceleration information, and sends the obtained suspension unit control information and braking unit control information to the vehicle's control module. Step 5: The control module controls the vehicle's suspension unit and braking unit according to the received suspension unit control information and braking unit control information.

2. The active control method for the suspension unit and braking unit according to claim 1, wherein, The networked transportation infrastructure includes traffic lights and road cameras in the transportation system. Each traffic light is used to collect traffic light information, and each road camera is used to collect road camera information. The traffic signal information includes the switching cycle signal of each traffic signal in the traffic system and the first GPS signal, and the road camera information includes the image signal of each road camera in the traffic system and the second GPS signal.

3. The active control method for the suspension unit and braking unit according to claim 2, wherein, Step 2 includes the following sub-steps: S201: The cloud computing platform obtains a first distance value between the vehicle and the nearest traffic light and a second distance value between the vehicle and the nearest other obstacle based on the received traffic light information, road camera information, GPS positioning information and navigation information. S202: The cloud computing platform uses the smaller of the first distance value and the second distance value as the nearest obstacle distance value.

4. The active control method for the suspension unit and braking unit according to claim 3, wherein, In sub-step S201, the cloud computing platform obtains the first distance value based on the GPS positioning information, the navigation information, and the first GPS signal of each traffic light; The cloud computing platform obtains the second distance value based on the GPS positioning information, the navigation information, the image signals from each road camera, and the second GPS signal.

5. The active control method for the suspension unit and braking unit according to claim 4, wherein, The methods for obtaining the second distance value include: The cloud computing platform identifies other obstacles captured by each road camera based on the image signals from each road camera. The cloud computing platform obtains the distance values ​​between the vehicle and each road camera that captured the other obstacles based on the GPS positioning information, the navigation information, and the second GPS signals of each traffic light. The cloud computing platform uses the minimum distance value among the distance values ​​between the road cameras that captured the other obstacles and the vehicle as the second distance value.

6. The active control method for the suspension unit and braking unit according to claim 3, wherein, If the cloud computing platform uses the first distance value as the nearest obstacle distance value, then step 3 includes the following sub-steps: S301: The cloud computing platform makes a judgment based on the received vehicle speed information, acceleration information, and the switching cycle signal of the nearest traffic light. If it determines that the vehicle can pass through the nearest traffic light within the nearest green light duration, it returns to step 1; otherwise, it proceeds to sub-step S302. S302: The cloud computing platform makes a judgment based on the obtained nearest obstacle distance value. If the nearest obstacle distance value is greater than the decision distance threshold, it determines that the suspension unit and braking unit of the vehicle will not be actively controlled, and returns to step 1; if the nearest obstacle distance value is not greater than the decision distance threshold, it determines that the suspension unit and braking unit of the vehicle will be actively controlled, and proceeds to step 4.

7. The active control method for the suspension unit and braking unit according to claim 3, wherein, In step 3, if the cloud computing platform uses the second distance value as the nearest obstacle distance value, the cloud computing platform makes a judgment based on the obtained nearest obstacle distance value. If the nearest obstacle distance value is greater than the decision distance threshold, it determines that the suspension unit and braking unit of the vehicle will not be actively controlled, and returns to step 1; if the nearest obstacle distance value is not greater than the decision distance threshold, it determines that the suspension unit and braking unit of the vehicle will be actively controlled, and proceeds to step 4.

8. The active control method for the suspension unit and braking unit according to claim 1, wherein, In step 5, the control module adjusts the height, stiffness, and damping force of the front and rear suspensions of the suspension unit according to the received suspension unit control information.

9. The active control method for the suspension unit and braking unit according to claim 1, wherein, The braking unit control information includes the braking force-time curve; In step 5, the control module controls the vehicle's braking unit according to the received braking unit control information.

10. An active control system for a suspension unit and a braking unit, comprising a networked traffic infrastructure, a cloud computing platform, and a vehicle control module, a suspension unit, and a braking unit; The networked transportation infrastructure and the control module are both communicatively connected to the cloud computing platform, and the suspension unit and the braking unit are both communicatively connected to the control module; The networked transportation infrastructure is used to collect traffic light information and road camera information, and send the traffic light information and road camera information to the cloud computing platform; the control module is used to collect vehicle speed information, acceleration information, GPS positioning information and navigation information, and send the vehicle speed information, acceleration information, GPS positioning information and navigation information to the cloud computing platform; The cloud computing platform is used to determine whether to actively control the suspension unit and the braking unit based on the received vehicle speed information, acceleration information, traffic light information, road camera information, GPS positioning information and navigation information, and when it is determined that the suspension unit and the braking unit should be actively controlled, it obtains the suspension unit control information and braking unit control information corresponding to the vehicle. The cloud computing platform is also used to send the obtained suspension unit control information and braking unit control information to the control module; The control module controls the suspension unit and the braking unit according to the received suspension unit control information and braking unit control information; The active control system of the suspension unit and braking unit is used to perform the steps in the active control method of the suspension unit and braking unit as described in any one of claims 1-9.

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