Power-assisted steering control method, device and equipment based on sensor data fusion

Abstract

The invention discloses a power-assisted steering control method, device and equipment based on sensor data fusion, and relates to the technical field of vehicle intelligent control, and the method comprises the steps: obtaining the measurement data of a suspension sensor and an axle sensor to calculate the total mass of a vehicle, and obtaining the measurement data of an acceleration sensor to calculate the height of the center of mass of the vehicle; determining a vehicle state mode by combining the calculated total mass of the vehicle and the height of the center of mass of the vehicle, and calculating a state transition matrix based on the determined vehicle state mode; based on the state transition matrix obtained through calculation, an input matrix in the current vehicle state mode is obtained in combination with a state equation used for describing vehicle dynamic system behaviors; based on the state vector of the vehicle and the obtained input matrix, a power-assisted steering value is obtained through calculation, and power-assisted steering control of the vehicle is achieved. The power-assisted steering value can be dynamically adjusted according to the driving condition, and the driving experience is improved.

Description

Technical Field

[0001] The present application relates to the field of vehicle intelligent control technology, and in particular to a steering assist control method, device and equipment based on sensor data fusion. Background Art

[0002] Power steering is used to assist the driver in adjusting the direction of the vehicle and reduce the force required to turn the steering wheel. Power steering plays a certain role in the safety and economy of car driving. The power steering system installed on the car can be roughly divided into three categories: mechanical hydraulic power steering system, electronic hydraulic power steering system and electric power steering system.

[0003] Currently, a fixed steering assist value is generally provided during the use of steering assist, and the steering assist value cannot be dynamically provided according to driving conditions and vehicle load, resulting in a poor driving experience during vehicle use. Summary of the invention

[0004] The present application provides a steering assist control method, device and equipment based on sensor data fusion, which can dynamically adjust the steering assist value according to driving conditions to improve the driving experience.

[0005] In a first aspect, an embodiment of the present application provides a steering assist control method based on sensor data fusion, the steering assist control method based on sensor data fusion comprising:

[0006] Obtaining the measurement data of the suspension sensor and the axle sensor to calculate the total mass of the vehicle, and obtaining the measurement data of the acceleration sensor to calculate the height of the center of mass of the vehicle;

[0007] Determine the vehicle state mode by combining the calculated vehicle gross mass and vehicle center of mass height, and calculate a state transfer matrix based on the determined vehicle state mode;

[0008] Based on the calculated state transfer matrix, combined with the state equation used to describe the behavior of the vehicle dynamic system, the input matrix under the current vehicle state mode is obtained;

[0009] Based on the state vector of the vehicle and the obtained input matrix, the steering assist value is calculated to achieve the steering assist control of the vehicle.

[0010] In combination with the first aspect, in one implementation, obtaining the measurement data of the suspension sensor and the axle sensor to calculate the total vehicle mass specifically includes:

[0011] Acquire the suspension force measured by the suspension sensor installed on the vehicle and the axle force measured by the axle sensor installed on the vehicle;

[0012] Based on the obtained suspension force and axle force, the total mass of the vehicle is calculated, specifically:

[0013] M=k 1 ·F susp +k 2 ·F axle

[0014] Where M represents the total mass of the vehicle, F susp Indicates the suspension force measured by the suspension sensor, F axle Represents the axle force measured by the axle sensor, k 1 represents the proportionality coefficient of the suspension force, k 2 Represents the proportionality factor of the axle force.

[0015] In combination with the first aspect, in one implementation, obtaining acceleration sensor measurement data to calculate the vehicle center of mass height specifically includes:

[0016] Acquiring acceleration data measured by an acceleration sensor installed on the vehicle, wherein the acceleration data includes the longitudinal acceleration of the vehicle and the vertical acceleration of the vehicle;

[0017] Based on the acquired acceleration data, the vehicle center of mass height is calculated, specifically:

[0018]

[0019] Among them, h c represents the height of the vehicle's center of mass, a x represents the longitudinal acceleration of the vehicle, a z is the vertical acceleration of the vehicle, h 0 Indicates the center of mass height of the vehicle in its initial state.

[0020] In combination with the first aspect, in one implementation, determining the vehicle state mode by combining the calculated total vehicle mass and vehicle center of mass height specifically includes:

[0021] When M<M 1 And h c <h c1 When , it is determined that the current vehicle state mode is a light load mode;

[0022] When M 1 ≤M<M 2 And h c1 ≤h c <h c2 When , it is determined that the current vehicle state mode is the medium load mode;

[0023] When M ≥ M 2 And h c ≥h c2When , it is determined that the current vehicle state mode is the heavy load mode;

[0024] Where M represents the total mass of the vehicle, h c Represents the vehicle's center of mass height, M 1 、M 2 represents the quality threshold, h c1 、h c2 Indicates the centroid height threshold.

[0025] In combination with the first aspect, in one implementation, the calculating and obtaining the state transfer matrix based on the determined vehicle state mode specifically includes:

[0026] For the state transfer matrix in light load mode, specifically:

[0027]

[0028] Among them, A 1 represents the state transition matrix in light load mode, h 1 Indicates the vehicle center of mass height in light load mode, b 1 Indicates the distance from the rear axle to the center of mass of the vehicle in light load mode, I z1 represents the moment of inertia of the vehicle around the vertical axis in light load mode, a y represents the lateral acceleration of the vehicle, L f1 Indicates the distance from the front axle to the center of mass of the vehicle in light load mode, K y1 Indicates the yaw stiffness coefficient of the vehicle in light load mode, m 1 represents the total mass of the vehicle in light load mode, and g represents the acceleration due to gravity;

[0029] For the state transfer matrix in medium load mode, specifically:

[0030]

[0031] Among them, A 2 represents the state transfer matrix in medium load mode, h 2 represents the vehicle center of mass height in medium load mode, b 2 Indicates the distance from the rear axle to the center of mass of the vehicle in medium load mode, I z2 represents the moment of inertia of the vehicle around the vertical axis in medium load mode, L f2 Indicates the distance from the front axle to the center of mass of the vehicle in medium load mode, K y2 represents the yaw stiffness coefficient of the vehicle in medium load mode, m 2 Indicates the total mass of the vehicle in medium load mode;

[0032] For the state transfer matrix in overload mode, specifically:

[0033]

[0034] Among them, A 3 represents the state transfer matrix in overload mode, h 3 Indicates the vehicle center of mass height in heavy load mode, b 3 Indicates the distance from the rear axle to the center of mass of the vehicle in heavy load mode, I z3 represents the moment of inertia of the vehicle around the vertical axis in heavy load mode, L f3 Indicates the distance from the front axle to the center of mass of the vehicle in heavy load mode, K y3 Indicates the yaw stiffness coefficient of the vehicle in heavy load mode, m 3 Indicates the total mass of the vehicle in heavy load mode.

[0035] In combination with the first aspect, in one implementation, the state equation is specifically:

[0036] x 1 =Ax+Bu

[0037] Among them, x 1 represents the derivative of the vehicle's state vector, A represents the state transfer matrix, x represents the vehicle's state vector, B represents the input matrix, and u represents the control input.

[0038] In combination with the first aspect, in one implementation,

[0039] The step of obtaining an input matrix in the current vehicle state mode based on the state transfer matrix obtained by calculation and combining it with a state equation used to describe the behavior of the vehicle dynamic system specifically includes: obtaining an input matrix in the current vehicle state mode based on the state transfer matrix obtained by calculation and combining it with a state equation used to describe the behavior of the vehicle dynamic system;

[0040] For the input matrix in the current vehicle state mode, specifically:

[0041] When the vehicle state mode is light load mode, the input matrix is:

[0042]

[0043] Among them, B 1 represents the input matrix in light load mode, b 1,1 、b 1,2 、b 1,3 、b 1,4 、b 1,5 、b 1,6 It represents the response coefficient of the vehicle to the input matrix in light load mode;

[0044] When the vehicle state mode is medium load mode, the input matrix is:

[0045]

[0046] Among them, B 2 represents the input matrix in medium load mode, b 2,1 、b 2,2 、b 2,3 、b 2,4 、b 2,5 、b 2,6 represents the response coefficient of the vehicle to the input matrix under medium load mode;

[0047] When the vehicle status mode is heavy load mode, the input matrix is:

[0048]

[0049] Among them, B 3 represents the input matrix in overload mode, b 3,1 、b 3,2 、b 3,3 、b 3,4 、b 3,5 、b 3,6 Represents the response coefficient of the vehicle to the input matrix in heavy load mode.

[0050] In combination with the first aspect, in one implementation, the calculation process of the steering assist value is:

[0051] F assist =B·x

[0052] Among them, F assist represents the steering assist value, B represents the input matrix, and x represents the state vector of the vehicle.

[0053] In a second aspect, an embodiment of the present application provides a steering assist control device based on sensor data fusion, the steering assist control device based on sensor data fusion comprising:

[0054] An acquisition module is used to acquire the measurement data of the suspension sensor and the axle sensor to calculate the total mass of the vehicle, and acquire the measurement data of the acceleration sensor to calculate the height of the center of mass of the vehicle;

[0055] A calculation module, which is used to determine the vehicle state mode in combination with the calculated vehicle total mass and vehicle center of mass height, and calculate a state transfer matrix based on the determined vehicle state mode;

[0056] A determination module, which is used to obtain an input matrix under a current vehicle state mode based on a state transfer matrix obtained by calculation and combined with a state equation used to describe the behavior of a vehicle dynamic system;

[0057] The execution module is used to calculate the steering assist value based on the state vector of the vehicle and the obtained input matrix, so as to realize the steering assist control of the vehicle.

[0058] In the third aspect, an embodiment of the present application provides a steering assist control device based on sensor data fusion, wherein the steering assist control device based on sensor data fusion comprises a processor, a memory, and a steering assist control program based on sensor data fusion stored in the memory and executable by the processor, wherein when the steering assist control program based on sensor data fusion is executed by the processor, the steps of the steering assist control method based on sensor data fusion described above are implemented.

[0059] The beneficial effects brought by the technical solution provided in the embodiments of the present application include:

[0060] By combining sensor data, it can provide feedback on changes in vehicle mass and center of mass height caused by cargo loading, and dynamically adjust the steering assist value according to driving conditions to enhance the driving experience; real-time processing of sensor data, update of status estimation, and calculation of steering assist value. There is no need to redetermine the steering assist value during loading or unloading, so that the driver feels the steering force unchanged under different loads, thereby optimizing the vehicle's handling. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1 This is a flow chart of a steering assist control method based on sensor data fusion in this application;

[0062] Figure 2 This is a schematic diagram of the functional modules of the steering assist control device based on sensor data fusion in this application;

[0063] Figure 3 This is a schematic diagram of the hardware structure of the steering assist control device based on sensor data fusion in this application. DETAILED DESCRIPTION

[0064] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0065] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0066] In a first aspect, an embodiment of the present application provides a steering assist control method based on sensor data fusion.

[0067] In one embodiment, referring to Figure 1 , Figure 1 This is a flow chart of the steering assistance control method based on sensor data fusion in this application. Figure 1 As shown, the steering assist control method based on sensor data fusion includes:

[0068] S1: Obtaining the measurement data of the suspension sensor and the axle sensor to calculate the total mass of the vehicle, and obtaining the measurement data of the acceleration sensor to calculate the height of the center of mass of the vehicle;

[0069] Furthermore, in one embodiment, obtaining the measurement data of the suspension sensor and the axle sensor to calculate the total mass of the vehicle specifically includes:

[0070] S101: obtaining a suspension force measured by a suspension sensor installed on the vehicle and an axle force measured by an axle sensor installed on the vehicle; that is, obtaining sensor data, measuring the suspension force by the suspension sensor and the axle force by the axle sensor;

[0071] S102: Based on the obtained suspension force and axle force, the total mass of the vehicle is calculated, specifically:

[0072] M=k 1 ·F susp +k 2 ·F axle

[0073] Where M represents the total mass of the vehicle, F susp Indicates the suspension force measured by the suspension sensor, F axle Represents the axle force measured by the axle sensor, k 1 represents the proportionality coefficient of the suspension force, k 2 Represents the proportionality coefficient of the axle force. After obtaining the suspension force and axle force measured by the sensor, the total mass of the vehicle can be calculated based on the suspension force and the axle force.

[0074] Furthermore, in one embodiment, obtaining the acceleration sensor measurement data to calculate the vehicle center of mass height specifically includes:

[0075] S111: Acquire acceleration data measured by an acceleration sensor installed on the vehicle, wherein the acceleration data includes the longitudinal acceleration and the vertical acceleration of the vehicle;

[0076] S112: Based on the acquired acceleration data, the height of the center of mass of the vehicle is calculated. Specifically:

[0077]

[0078] Among them, h c represents the height of the vehicle's center of mass, a x represents the longitudinal acceleration of the vehicle, a z is the vertical acceleration of the vehicle, h 0 It indicates the height of the center of mass of the vehicle in the initial state, that is, the height of the center of mass of the vehicle in a stationary state. That is, the acceleration sensor data is acquired to obtain the longitudinal acceleration and vertical acceleration of the vehicle, and then the real-time center of mass height of the vehicle can be calculated based on the longitudinal acceleration and vertical acceleration of the vehicle.

[0079] S2: Determine the vehicle state mode based on the calculated vehicle gross mass and vehicle center of mass height, and calculate a state transfer matrix based on the determined vehicle state mode;

[0080] Furthermore, the vehicle state mode is determined by combining the calculated vehicle gross mass and vehicle center of mass height, including:

[0081] When M<M 1 And h c <h c1 When , it is determined that the current vehicle state mode is a light load mode;

[0082] When M 1 ≤M<M 2 And h c1 ≤h c <h c2 When , it is determined that the current vehicle state mode is the medium load mode;

[0083] When M ≥ M 2 And h c ≥h c2 When , it is determined that the current vehicle state mode is the heavy load mode;

[0084] Where M represents the total mass of the vehicle, h c Represents the vehicle's center of mass height, M 1 、M 2 represents the quality threshold, and M 2 Greater than M 1 , M 1 、M 2 Take the value according to actual needs, h c1 、h c2 represents the centroid height threshold, and h c2 Greater than h c1 ,h c1 、h c2 Set the value according to actual needs.

[0085] Furthermore, a state transfer matrix is ​​calculated based on the determined vehicle state mode, specifically including:

[0086] For the state transfer matrix in light load mode, specifically:

[0087]

[0088] Among them, A 1 represents the state transition matrix in light load mode, h 1 Indicates the vehicle center of mass height in light load mode, b 1 Indicates the distance from the rear axle to the center of mass of the vehicle in light load mode, I z1 represents the moment of inertia of the vehicle around the vertical axis in light load mode, a y represents the lateral acceleration of the vehicle, L f1 Indicates the distance from the front axle to the center of mass of the vehicle in light load mode, K y1 Indicates the yaw stiffness coefficient of the vehicle in light load mode, m 1 represents the total mass of the vehicle in light load mode, and g represents the acceleration due to gravity;

[0089] For the state transfer matrix in medium load mode, specifically:

[0090]

[0091] Among them, A 2 represents the state transfer matrix in medium load mode, h 2 represents the vehicle center of mass height in medium load mode, b 2 Indicates the distance from the rear axle to the center of mass of the vehicle in medium load mode, I z2 represents the moment of inertia of the vehicle around the vertical axis in medium load mode, L f2 Indicates the distance from the front axle to the center of mass of the vehicle in medium load mode, K y2 represents the yaw stiffness coefficient of the vehicle in medium load mode, m 2 Indicates the total mass of the vehicle in medium load mode;

[0092] For the state transfer matrix in overload mode, specifically:

[0093]

[0094] Among them, A 3 represents the state transfer matrix in overload mode, h 3 Indicates the vehicle center of mass height in heavy load mode, b 3 Indicates the distance from the rear axle to the center of mass of the vehicle in heavy load mode, I z3 represents the moment of inertia of the vehicle around the vertical axis in heavy load mode, L f3 Indicates the distance from the front axle to the center of mass of the vehicle in heavy load mode, K y3 Indicates the yaw stiffness coefficient of the vehicle in heavy load mode, m3 Indicates the total mass of the vehicle in heavy load mode.

[0095] That is, according to the current vehicle state mode, the corresponding state transfer matrix is ​​solved.

[0096] S3: Based on the calculated state transfer matrix, combined with the state equation used to describe the behavior of the vehicle dynamic system, the input matrix under the current vehicle state mode is obtained;

[0097] In this application, the state equation is specifically:

[0098] x 1 =Ax+Bu

[0099] Among them, x 1 The derivative of the vehicle's state vector, that is, the system dynamics of the vehicle, A represents the state transfer matrix, x represents the vehicle's state vector, B represents the input matrix, and u represents the control input, such as steering angle or steering force. The vehicle's state vector can be calculated using data measured by the inclination sensor, lidar sensor, and ultrasonic sensor installed on the vehicle. For the input matrix, it is also the steering assist curve.

[0100] In the present application, based on the calculated state transfer matrix, combined with the state equation used to describe the behavior of the vehicle dynamic system, the input matrix under the current vehicle state mode is obtained, specifically including: based on the calculated state transfer matrix under the current vehicle state mode, combined with the state equation used to describe the behavior of the vehicle dynamic system, the input matrix under the current vehicle state mode is obtained.

[0101] For example, when the current vehicle state mode is light load mode, the input matrix under light load mode is calculated based on the state transfer matrix under light load mode through the state equation; when the current vehicle state mode is medium load mode, the input matrix under medium load mode is calculated based on the state transfer matrix under medium load mode through the state equation; when the current vehicle state mode is heavy load mode, the input matrix under heavy load mode is calculated based on the state transfer matrix under heavy load mode through the state equation.

[0102] In this application, when the vehicle state mode is light load mode, the input matrix is:

[0103]

[0104] Among them, B 1 represents the input matrix in light load mode, b 1,1 、b 1,2 、b 1,3 、b 1,4 、b 1,5 、b 1,6It represents the response coefficient of the vehicle to the input matrix in light load mode, and the value is determined according to the actual application;

[0105] When the vehicle state mode is medium load mode, the input matrix is:

[0106]

[0107] Among them, B 2 represents the input matrix in medium load mode, b 2,1 、b 2,2 、b 2,3 、b 2,4 、b 2,5 、b 2,6 represents the response coefficient of the vehicle to the input matrix under medium load mode;

[0108] When the vehicle status mode is heavy load mode, the input matrix is:

[0109]

[0110] Among them, B 3 represents the input matrix in overload mode, b 3,1 、b 3,2 、b 3,3 、b 3,4 、b 3,5 、b 3,6 Represents the response coefficient of the vehicle to the input matrix in heavy load mode.

[0111] S4: Based on the state vector of the vehicle and the obtained input matrix, the steering assist value is calculated to achieve the steering assist control of the vehicle.

[0112] In this application, the calculation process of the steering assist value is:

[0113] F assist =B·x

[0114] Among them, F assist represents the steering assist value, B represents the input matrix, and x represents the state vector of the vehicle.

[0115] Specifically, if the current vehicle state mode is light load mode, the steering assist value is calculated based on the input matrix in the light load mode and in combination with the state vector of the vehicle through the above formula; if the current vehicle state mode is medium load mode, the steering assist value is calculated based on the input matrix in the medium load mode and in combination with the state vector of the vehicle through the above formula; if the current vehicle state mode is heavy load mode, the steering assist value is calculated based on the input matrix in the heavy load mode and in combination with the state vector of the vehicle through the above formula.

[0116] For the real-time steering assist value calculated according to the vehicle's state vector and the input matrix under the current vehicle state mode, a corresponding control signal is sent to the power assist motor to adjust the output of the power assist motor; further, after adjusting the output of the power assist motor, the steering assist control method described in the present application can be repeated again to obtain the steering assist value again, and the steering assist can be controlled. This cycle is repeated to achieve real-time feedback and optimization, so that the steering assist can be adaptively adjusted according to the sensor data and the vehicle state to optimize the vehicle's handling.

[0117] It should be noted that when the steering assist control method based on sensor data fusion of the present application is applied in practice, it is necessary to select appropriate mass and center of mass height thresholds so as to accurately determine the vehicle state in actual situations; mode switching needs to be completed in real time to ensure response speed and accuracy; for the dynamic model, different state transfer matrices and input matrices are designed for each vehicle state mode (light load, medium load, heavy load) to ensure that the state transfer matrices in different modes can accurately reflect the dynamic behavior of the vehicle under different load conditions; for model parameters, matrix parameters (such as moment of inertia, damping coefficient, etc.) are determined through experiments or simulations; sensor data needs to be processed in real time, state estimates updated, and assist values ​​calculated; feedback is provided on mass changes of the cargo load and the center of mass height, and the assist value is dynamically adjusted according to driving conditions.

[0118] The steering assist control method based on sensor data fusion in the embodiment of the present application can provide feedback on changes in vehicle mass and center of mass height caused by cargo loading by combining sensor data, and dynamically adjust the steering assist value according to driving conditions to improve driving experience; it processes sensor data, updates state estimation, and calculates the steering assist value in real time, and there is no need to redetermine the steering assist value during mid-way loading or unloading, so that the driver's steering force feeling remains unchanged under different loads, thereby optimizing the vehicle's handling.

[0119] In a second aspect, an embodiment of the present application also provides a steering assist control device based on sensor data fusion.

[0120] In one embodiment, referring to Figure 2 , Figure 2 This is a functional module diagram of the steering assist control device based on sensor data fusion in this application. Figure 2 As shown, the steering assist control device based on sensor data fusion includes: an acquisition module, a calculation module, a determination module, and an execution module.

[0121] The acquisition module is used to obtain the measurement data of the suspension sensor and the axle sensor to calculate the total mass of the vehicle, and to obtain the measurement data of the acceleration sensor to calculate the height of the center of mass of the vehicle; the calculation module is used to determine the vehicle state mode in combination with the calculated total mass of the vehicle and the height of the center of mass of the vehicle, and calculate the state transfer matrix based on the determined vehicle state mode; the determination module is used to obtain the input matrix under the current vehicle state mode based on the calculated state transfer matrix and the state equation used to describe the behavior of the vehicle dynamic system; the execution module is used to calculate the steering assist value based on the vehicle state vector and the obtained input matrix, so as to realize the steering assist control of the vehicle.

[0122] Among them, the functional implementation of each module in the above-mentioned steering assist control device based on sensor data fusion corresponds to the various steps in the above-mentioned steering assist control method embodiment based on sensor data fusion, and its functions and implementation processes will not be repeated here one by one.

[0123] On the third aspect, an embodiment of the present application provides a steering assist control device based on sensor data fusion. The steering assist control device based on sensor data fusion may be a personal computer (PC), a laptop computer, a server, or other device with data processing capabilities.

[0124] Reference Figure 3 , Figure 3 The schematic diagram of the hardware structure of the steering assistance control device based on sensor data fusion involved in the embodiment of the present application is shown in FIG. In the embodiment of the present application, the steering assistance control device based on sensor data fusion may include a processor, a memory, a communication interface and a communication bus.

[0125] The communication bus may be of any type and is used to interconnect the processor, the memory, and the communication interface.

[0126] The communication interface includes an input / output (I / O) interface, a physical interface, and a logical interface, etc., which are used to realize the interconnection of devices inside the steering power control device based on sensor data fusion, and an interface used to realize the interconnection between the steering power control device based on sensor data fusion and other devices (such as other computing devices or user devices). The physical interface can be an Ethernet interface, an optical fiber interface, an ATM interface, etc.; the user device can be a display, a keyboard, etc.

[0127] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0128] The processor may be a general-purpose processor, which may call the steering assistance control program based on sensor data fusion stored in the memory and execute the steering assistance control method based on sensor data fusion provided in the embodiment of the present application. For example, the general-purpose processor may be a central processing unit (CPU). The method executed when the steering assistance control program based on sensor data fusion is called may refer to the various embodiments of the steering assistance control method based on sensor data fusion of the present application, which will not be described in detail here.

[0129] Those skilled in the art will understand that Figure 3 The hardware structure shown in the figure does not constitute a limitation on the present application, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0130] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit "first", "second" and "third" to different types.

[0131] In the description of the embodiments of the present application, "exemplary", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "for example" or "for example" is intended to present related concepts in a specific way.

[0132] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; the “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0133] In some processes described in the embodiments of the present application, multiple operations or steps that appear in a specific order are included, but it should be understood that these operations or steps may not be executed in the order in which they appear in the embodiments of the present application or in parallel, and the sequence number of the operation is only used to distinguish the different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed in sequence or in parallel, and these operations or steps may be combined.

[0134] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, disk, CD) as described above, and includes a number of instructions for a terminal device to execute the methods described in each embodiment of the present application.

[0135] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A steering assist control method based on sensor data fusion, characterized in that: The steering assist control method based on sensor data fusion includes: Obtaining the measurement data of the suspension sensor and the axle sensor to calculate the total mass of the vehicle, and obtaining the measurement data of the acceleration sensor to calculate the height of the center of mass of the vehicle; Determine the vehicle state mode by combining the calculated vehicle gross mass and vehicle center of mass height, and calculate a state transfer matrix based on the determined vehicle state mode; Based on the calculated state transfer matrix, combined with the state equation used to describe the behavior of the vehicle dynamic system, the input matrix under the current vehicle state mode is obtained; Based on the state vector of the vehicle and the obtained input matrix, the steering assist value is calculated to achieve the steering assist control of the vehicle.

2. A steering assist control method based on sensor data fusion as claimed in claim 1, characterized in that: The obtaining of the measurement data of the suspension sensor and the axle sensor to calculate the total mass of the vehicle specifically includes: Acquire the suspension force measured by the suspension sensor installed on the vehicle and the axle force measured by the axle sensor installed on the vehicle; Based on the obtained suspension force and axle force, the total mass of the vehicle is calculated, specifically: M=k1·F susp +k2·F axle Where M represents the total mass of the vehicle, F susp Indicates the suspension force measured by the suspension sensor, F axle It represents the axle force measured by the axle sensor, k1 represents the proportional coefficient of the suspension force, and k2 represents the proportional coefficient of the axle force.

3. A steering assist control method based on sensor data fusion as claimed in claim 1, characterized in that: The step of obtaining the acceleration sensor measurement data to calculate the vehicle center of mass height specifically includes: Acquiring acceleration data measured by an acceleration sensor installed on the vehicle, wherein the acceleration data includes the longitudinal acceleration of the vehicle and the vertical acceleration of the vehicle; Based on the acquired acceleration data, the vehicle center of mass height is calculated, specifically: Among them, h c represents the height of the vehicle's center of mass, a x represents the longitudinal acceleration of the vehicle, a z represents the vertical acceleration of the vehicle, and h0 represents the height of the center of mass of the vehicle in the initial state.

4. A steering assist control method based on sensor data fusion as claimed in claim 1, characterized in that: The step of determining the vehicle state mode by combining the calculated vehicle gross mass and vehicle center of mass height specifically includes: When M<M1 and h c <h c1 When , it is determined that the current vehicle state mode is a light load mode; When M1≤M<M2 and h c1 ≤h c <h c2 When , it is determined that the current vehicle state mode is the medium load mode; When M ≥ M2 and h c ≥h c2 When , it is determined that the current vehicle state mode is the heavy load mode; Where M represents the total mass of the vehicle, h c represents the height of the vehicle's center of mass, M1 and M2 represent mass thresholds, and h c1 、h c2 Indicates the centroid height threshold.

5. A steering assist control method based on sensor data fusion as claimed in claim 4, characterized in that: The state transfer matrix is ​​calculated based on the determined vehicle state mode, specifically including: For the state transfer matrix in light load mode, specifically: Among them, A1 represents the state transfer matrix in light load mode, h1 represents the height of the vehicle center of mass in light load mode, b1 represents the distance from the rear axle to the center of mass of the vehicle in light load mode, I z1 represents the moment of inertia of the vehicle around the vertical axis in light load mode, a y represents the lateral acceleration of the vehicle, L f1 Indicates the distance from the front axle to the center of mass of the vehicle in light load mode, K y1 represents the yaw stiffness coefficient of the vehicle in light load mode, m1 represents the total mass of the vehicle in light load mode, and g represents the acceleration of gravity; For the state transfer matrix in medium load mode, specifically: Among them, A2 represents the state transfer matrix in the medium load mode, h2 represents the height of the vehicle center of mass in the medium load mode, b2 represents the distance from the rear axle to the center of mass of the vehicle in the medium load mode, I z2 represents the moment of inertia of the vehicle around the vertical axis in medium load mode, L f2 Indicates the distance from the front axle to the center of mass of the vehicle in medium load mode, K y2 represents the yaw stiffness coefficient of the vehicle in medium load mode, and m2 represents the total mass of the vehicle in medium load mode; For the state transfer matrix in overload mode, specifically: Among them, A3 represents the state transfer matrix in heavy load mode, h3 represents the height of the vehicle center of mass in heavy load mode, b3 represents the distance from the rear axle to the center of mass of the vehicle in heavy load mode, I z3 represents the moment of inertia of the vehicle around the vertical axis in heavy load mode, L f3 Indicates the distance from the front axle to the center of mass of the vehicle in heavy load mode, K y3 represents the yaw stiffness coefficient of the vehicle in heavy load mode, and m3 represents the total mass of the vehicle in heavy load mode.

6. A steering assist control method based on sensor data fusion as claimed in claim 5, characterized in that: The state equation is specifically: x1=Ax+Bu Among them, x1 represents the derivative of the vehicle's state vector, A represents the state transfer matrix, x represents the vehicle's state vector, B represents the input matrix, and u represents the control input.

7. A steering assist control method based on sensor data fusion as claimed in claim 6, characterized in that: The step of obtaining an input matrix in the current vehicle state mode based on the state transfer matrix obtained by calculation and combining it with a state equation used to describe the behavior of the vehicle dynamic system specifically includes: obtaining an input matrix in the current vehicle state mode based on the state transfer matrix obtained by calculation and combining it with a state equation used to describe the behavior of the vehicle dynamic system; For the input matrix in the current vehicle state mode, specifically: When the vehicle state mode is light load mode, the input matrix is: Where B1 represents the input matrix in light load mode, b 1,1 , b 1,2 , b 1,3 , b 1,4 , b 1,5 , b 1,6 It represents the response coefficient of the vehicle to the input matrix in light load mode; When the vehicle state mode is medium load mode, the input matrix is: Where B2 represents the input matrix under medium load mode, b 2,1 , b 2,2 , b 2,3 , b 2,4 , b 2,5 , b 2,6 represents the response coefficient of the vehicle to the input matrix under medium load mode; When the vehicle status mode is heavy load mode, the input matrix is: Among them, B3 represents the input matrix in overload mode, b 3,1 , b 3,2 , b 3,3 , b 3,4 , b 3,5 , b 3,6 Represents the response coefficient of the vehicle to the input matrix in heavy load mode.

8. The steering assist control method based on sensor data fusion as claimed in claim 1, characterized in that: The calculation process of the steering assist value is: F assist =B·x Among them, F assist represents the steering assist value, B represents the input matrix, and x represents the state vector of the vehicle.

9. A steering assist control device based on sensor data fusion, characterized in that: The steering assist control device based on sensor data fusion comprises: An acquisition module is used to acquire the measurement data of the suspension sensor and the axle sensor to calculate the total mass of the vehicle, and acquire the measurement data of the acceleration sensor to calculate the height of the center of mass of the vehicle; A calculation module, which is used to determine the vehicle state mode in combination with the calculated vehicle total mass and vehicle center of mass height, and calculate a state transfer matrix based on the determined vehicle state mode; A determination module, which is used to obtain an input matrix under a current vehicle state mode based on a state transfer matrix obtained by calculation and combined with a state equation used to describe the behavior of a vehicle dynamic system; The execution module is used to calculate the steering assist value based on the state vector of the vehicle and the obtained input matrix, so as to realize the steering assist control of the vehicle.

10. A steering assist control device based on sensor data fusion, characterized in that: The steering assist control device based on sensor data fusion includes a processor, a memory, and a steering assist control program based on sensor data fusion stored in the memory and executable by the processor, wherein when the steering assist control program based on sensor data fusion is executed by the processor, the steps of the steering assist control method based on sensor data fusion as described in any one of claims 1 to 8 are implemented.

Images