Vehicle and power-assisted steering control method thereof

Abstract

The invention is suitable for the technical field of vehicle control, and particularly relates to a vehicle and a power-assisted steering control method thereof. According to the method, the hand torque data of vehicle steering control by a driver is obtained, anomaly detection is carried out on the hand torque data to obtain a data detection result, and when the data detection result is abnormal, the target hand torque is determined according to the anomaly type in the data detection result. The power-assisted steering torque is determined according to the safety curve and the target hand torque when the vehicle enters the safety state, and the vehicle is controlled to steer according to the power-assisted steering torque, so that when the torque sensor is abnormal, the vehicle enters the safety state, certain power-assisted steering can be provided, the situation that the vehicle is difficult to control due to the failure of the torque sensor is avoided, and the safety of the vehicle is improved. And the safety of the vehicle can be improved.

Description

Technical Field

[0001] This application is applicable to the field of vehicle control technology, and particularly relates to a vehicle and a steering assist control method thereof. Background Art

[0002] Currently, in order to make it easier for the driver to control the steering wheel, most vehicles are equipped with an electric power steering system to assist the steering system. Since the electric power steering system needs to sense the hand force torque input by the driver in the steering system, torque signals detected by a torque sensor in the steering system are required. However, when the torque sensor fails, the safety mechanism of the electric power steering system is to enter a safe state within a set time after determining the failure. Among them, the safe state is to directly cut off the assist to avoid unexpected steering assist in the steering system. However, after cutting off the assist, the rotation of the steering wheel needs to rely on the driver's strength to control the steering wheel. Since a relatively large amount of force is required, it is difficult for the driver to control the direction and drive the vehicle to a safe position. Therefore, how to change the safe state to provide partial assistance when the torque sensor fails to avoid difficult vehicle control caused by sensor failure has become an urgent problem to be solved. Summary of the Invention

[0003] In view of this, the embodiments of the present application provide a vehicle and a steering assist control method thereof to solve the problem of how to control the steering system to enter a safe state according to the failure degree and provide partial assistance to the steering system when the torque sensor fails.

[0004] In a first aspect, the embodiments of the present application provide a steering assist control method, and the steering assist control method includes:

[0005] Obtain the hand force torque data of the driver controlling the vehicle to steer;

[0006] Perform anomaly detection on the hand force torque data to obtain a data detection result;

[0007] When the data detection result is abnormal, determine the target hand force torque according to the abnormal type in the data detection result;

[0008] Determine the steering assist torque according to the safety curve of the vehicle in the safe state and the target hand force torque, and provide steering assist to the vehicle according to the steering assist torque.

[0009] In a second aspect, the embodiments of the present application provide a vehicle, and the vehicle includes the steering assist control method as described in the first aspect.

[0010] The beneficial effects of the embodiments of the present application compared with the prior art are as follows: By obtaining the hand force torque data of the driver's vehicle steering, performing anomaly detection on the hand force torque data to obtain a data detection result, when the data detection result is abnormal, determining a target hand force torque according to the type of anomaly in the data detection result, determining a steering assist torque according to the safety curve of the vehicle in the safe state and the target hand force torque, and controlling the vehicle steering according to the steering assist torque, it is realized that when the torque sensor is abnormal, the vehicle enters a safe state and can provide a certain amount of steering assist, thus avoiding the situation that the vehicle is difficult to control due to the failure of the torque sensor, which helps to improve the safety of the vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for use in the embodiments or the prior art description. Obviously, the following drawings are only some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0012] Figure 1 It is a flowchart of a steering assist control method provided in Embodiment 1 of the present application;

[0013] Figure 2 It is a flowchart of a steering assist control method provided in Embodiment 2 of the present application;

[0014] Figure 3 It is a flowchart of a steering assist control method provided in Embodiment 3 of the present application;

[0015] Figure 4 It is a flowchart of a steering assist control method provided in Embodiment 4 of the present application;

[0016] Figure 5 It is a flowchart of a steering assist control method provided in Embodiment 5 of the present application;

[0017] Figure 6 It is a flowchart of a steering assist control method provided in Embodiment 6 of the present application;

[0018] Figure 7 It is a flowchart of a steering assist control method provided in Embodiment 7 of the present application;

[0019] Figure 8 It is a structural diagram of an electric power steering system provided in Embodiment 8 of the present application;

[0020] In the figure, 1 is an electric power steering system, 2 is a torque sensor, 3 is a motor, 4 is a braking system, 11 is a torque calculation and diagnosis module, 12 is a normal feel module, 13 is an arbitration module, 14 is a safety monitoring status judgment module, 15 is a torque self-learning module, and 16 is a safety feel module. Detailed implementation manners

[0021] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures and technologies are presented in order to provide a thorough understanding of the embodiments of the present application. However, those skilled in the art should clearly understand that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present application.

[0022] It should be understood that when used in the specification of the present application and the appended claims, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0023] In addition, in the description of the specification of the present application and the appended claims, the terms "first", "second", "third", etc. are only used for differentiating descriptions and cannot be understood as indicating or implying relative importance.

[0024] The reference to "one embodiment" or "some embodiments" etc. described in the specification of the present application means that a specific feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the present application. Thus, the statements "in one embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments", etc. that appear in different places in this specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in another way. The terms "comprising", "including", "having", and their variants all mean "including but not limited to", unless otherwise specifically emphasized in another way.

[0025] It should be understood that the magnitudes of the sequence numbers of the steps in the following embodiments do not mean the order of execution is prior or subsequent. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0026] To illustrate the technical solution of the present application, the following specific embodiments are used for illustration.

[0027] See Figure 1, which is a schematic flow chart of a steering assist control method provided in the first embodiment of the present application. This steering assist control method can run in the control device of the vehicle's power steering system. Among them, the power steering system is used to provide assistance to the vehicle's steering system, specifically including power assistance methods such as electric assistance and mechanical assistance. The power steering system using the electric assistance method is an Electric Power Steering System (EPS).

[0028] As Figure 1 shown, this steering assist control method may include the following steps:

[0029] Step S101, obtain the hand force torque data of the driver controlling the vehicle to steer.

[0030] In the embodiment of the present application, in the power steering system that provides steering assistance to the vehicle, corresponding measuring devices such as torque sensors are designed to measure the driver's force when the driver controls the steering wheel to steer the vehicle. The corresponding measurement result is expressed as torque, which is the torque data. The result measured by the corresponding torque sensor each time is the hand force torque data.

[0031] The hand force torque data may include at least one torque perception data. If the hand force torque data is multiple torque perception data, the multiple torque perception data may be two independent data collected by the same torque sensor at the same time and transmitted to the power steering system through different transmission paths.

[0032] In addition, the torque perception data in the hand force torque data may be a torque value or a torque signal value. Among them, if the hand force torque data is a torque signal value, signal processing is also required according to the sensor specification table, etc. to obtain the corresponding torque value.

[0033] Step S102, perform anomaly detection on the hand force torque data to obtain a data detection result.

[0034] In the embodiment of the present application, for the hand force torque data, it will enter the power steering system only through the processes of measurement, transmission, and data transmission and reception of the torque sensor. Therefore, abnormal situations such as measurement anomalies, transmission anomalies, transmission anomalies, and reception anomalies may exist in the above processes. For this, corresponding detection means are used to detect each of the above anomalies, so as to obtain the corresponding data detection result.

[0035] For example, when performing anomaly detection on transmission, corresponding communication protocols can be used for diagnosis to determine whether the requirements of the communication protocol are met. Those that do not meet the requirements of the communication protocol will be detected as transmission anomalies. Another example is that when performing anomaly detection on the measured data, methods such as comparing with upper and lower threshold values can be used for diagnosis. When the measured data exceeds the range included in the upper and lower threshold values, it can be detected as a measurement anomaly.

[0036] In addition, the anomaly type can also be included in the data detection result. The anomaly type represents different anomaly situations. For example, transmission anomaly and measurement anomaly are two different types of anomaly situations. Transmission anomaly represents an anomaly situation such as a transmission path or line being abnormal, which reflects a fault in the line. Measurement anomaly represents an anomaly situation of the result measured by the torque sensor, which reflects a fault in the torque sensor.

[0037] Step S103, when there is an anomaly in the data detection result, determine the target hand force torque according to the anomaly type in the data detection result.

[0038] In the embodiment of the present application, the data detection result contains at least one result of anomaly detection. If there is one result of anomaly detection that is abnormal, it is determined that there is an anomaly in the data detection result. If there are multiple results of anomaly detection and all results are not abnormal, it is determined that there is no anomaly in the data detection result.

[0039] As can be seen from the analysis of the data detection result in the above step S102, the anomaly type can be reflected in the data detection result. In this embodiment, different anomaly types can be analyzed to obtain corresponding steering assist torques.

[0040] For example, if there is an anomaly in the data detection result and the corresponding anomaly type is measurement anomaly, that is, the torque sensor fails. At this time, since accurate hand force torque data cannot be obtained, the hand force torque data cannot be used to obtain the steering assist torque. Instead, the running data of the vehicle can be used to predict a driver's hand force. By analyzing the running data, parameters such as the vehicle's attitude can be obtained. Combining with the corresponding prediction model, a driver's hand force can be obtained, and this driver's hand force can be used as the target hand force torque for calculating the steering assist torque.

[0041] Of course, in the process of determining the driver's hand force according to the anomaly type in the data detection result, some preset parameters, models, etc. can be configured according to requirements to achieve the output of the corresponding hand force torque. Among them, the parameters and models can be obtained through training, experiments or experience to ensure that a relatively accurate hand force torque can be output for different anomaly types.

[0042] Step S104: Determine the steering assist torque based on the safety curve and the target hand force torque when the vehicle is in a safe state, and provide steering assist to the vehicle according to the steering assist torque.

[0043] In the embodiment of the present application, when the hand force torque data collected by the torque sensor is abnormal, the vehicle enters the corresponding safe state, and the steering assist torque is obtained based on the safety curve and the target hand force torque in the safe state, so that there is assistance when the vehicle is in the safe state.

[0044] The steering assist torque can be a parameter that enables the power steering system to work, enabling the power steering system to generate a corresponding assist torque, and this assist torque acts on the steering system to provide steering assist to the vehicle.

[0045] The above steps can analyze the abnormality and give corresponding solutions to prevent the sudden cut-off of the steering assist caused by the abnormality, and can ensure the safety of the vehicle to a certain extent.

[0046] In the embodiment of the present application, by obtaining the hand force torque data of the driver controlling the vehicle steering, performing abnormal detection on the hand force torque data to obtain the data detection result, when the data detection result is abnormal, determining the target hand force torque according to the abnormal type in the data detection result, determining the steering assist torque according to the safety curve and the target hand force torque when the vehicle enters the safe state, and controlling the vehicle steering according to the steering assist torque, it is realized that when the torque sensor is abnormal, the vehicle enters the safe state and can provide a certain amount of steering assist, thus avoiding the situation that the vehicle is difficult to control due to the failure of the torque sensor, which helps to improve the safety of the vehicle.

[0047] See Figure 2 , which is a schematic flow chart of a steering assist control method provided by the second embodiment of the present application. Among them, the hand force torque data includes two torque sensing data, and these two torque sensing data can be two data measured by one sensor, or data measured by two sensors respectively, and this is not limited herein.

[0048] As Figure 2 shown, in the above step S103, determining the steering assist torque according to the abnormal type in the data detection result may specifically include the following steps:

[0049] Step S201: If the abnormal type in the data detection result is that one torque sensing data is normal and the other torque sensing data is abnormal, then determine the target hand force torque according to the normal torque sensing data.

[0050] In the embodiments of the present application, an abnormal type is defined to characterize the abnormal conditions of two torque sensing data. Among them, only one torque sensing data is abnormal, both two torque sensing data are normal, and both two torque sensing data are abnormal are three different abnormal types. Among them, for the abnormal type corresponding to only one torque sensing data being abnormal, the other torque sensing data is normal. Therefore, the normal torque sensing data can be used to determine the target hand force torque.

[0051] The torque value corresponding to the normal torque sensing data is the hand force torque provided by the driver. Through this hand force torque, the steering requirement can be determined, and then the steering assist torque can be determined. For example, the steering assist torque is 90% of the steering requirement, and the remaining 10% is provided by the driver.

[0052] Step S202, if the abnormal type in the data detection result is that both two torque sensing data are abnormal, then determine the target hand force torque according to the current vehicle driving data.

[0053] Among them, for the abnormal type where both two torque sensing data are abnormal, the torque sensing data cannot be used, that is, the hand force torque provided by the driver cannot be sensed. Therefore, the target hand force torque is obtained through the current vehicle driving data.

[0054] The current vehicle driving data may refer to the driving data of the vehicle at the current moment, including data such as vehicle speed, yaw angle, longitudinal acceleration, lateral acceleration, steering wheel angle, and steering wheel angular velocity. This driving data can be provided by the braking system of the vehicle. Among them, the braking system, power steering system, etc. of the vehicle can communicate through the Controller Area Network (CAN) bus. Therefore, the power steering system can directly obtain the driving data on the CAN bus.

[0055] In the embodiments of the present application, in this power steering system, a mapping relationship between the driving data of the vehicle and the target hand force torque is pre-configured. Thus, after obtaining the current vehicle driving data, the target hand force torque required at present can be determined, so as to realize power steering in the case of abnormal torque sensing.

[0056] See Figure 3 which is a schematic flow chart of a power steering control method provided in Embodiment 3 of the present application. As Figure 3 shown, in the above step S202, to determine the target hand force torque according to the current vehicle driving data, it may specifically include the following steps:

[0057] Step S301, detect whether the current vehicle driving data is valid data.

[0058] Among them, the validity of the current vehicle driving data is detected. Only valid data can be used to determine the target hand force torque. Invalid data will result in inaccurate determination of the target hand force torque, thus affecting driving safety. When the braking system sends the driving data, it will attach a tag indicating whether the data is valid, so that other devices can determine whether the driving data is valid after obtaining the driving data.

[0059] Step S302, if it is detected that the current vehicle driving data is valid data, use the torque self-learning module to calculate the torque of the current vehicle driving data to obtain the target hand force torque.

[0060] In the embodiment of the present application, a torque self-learning model is provided. Using this torque self-learning model, when the current vehicle driving data is valid data, the current vehicle driving data can be calculated, so as to predict the target hand force torque, and the target hand force torque is equivalent to the torque measured by the torque sensor.

[0061] This torque self-learning model is used to analyze the driving habits of the driver. That is, when the torque sensor, power steering system, steering system, braking system, etc. of the vehicle are all normal, record the hand force torque data, driving data, etc. during the vehicle steering process, and realize the learning of the mapping relationship between the hand force torque data and the driving data through the corresponding self-learning method, so that the corresponding hand force torque data can be obtained according to a driving data.

[0062] This torque self-learning model can be reset after each vehicle start, and then start to learn the mapping relationship between the hand force torque data and the form data after this start. That is, the torque self-learning model re-learns every time the vehicle starts to meet the accurate mapping relationship under different drivers or different driving states of the vehicle.

[0063] Step S303, if it is detected that the current vehicle driving data is not valid data, determine that the target hand force torque is zero.

[0064] Among them, if the current vehicle driving data is invalid data, it indicates that the driving data given by the braking system is also not safe. For the driving safety of the vehicle, the current vehicle driving data cannot be used to determine the target hand force torque. At this time, the vehicle steering assist cannot be controlled by any form of data. Therefore, the target hand force torque is set to zero, that is, the power steering system's assistance to the steering system is cut off.

[0065] See Figure 4 , which is a schematic flowchart of a steering assist control method provided in the fourth embodiment of the present application. As Figure 4 shown, in the above step S104, according to the safety curve and the target hand force torque in the vehicle safety state, determining the steering assist torque may specifically further include the following steps:

[0066] Step S401: Obtain the safety curve when the vehicle enters the safe state.

[0067] Among them, for abnormal situations, there is a first correspondence between the steering assist torque and the hand force torque. Under normal circumstances, there is a second correspondence between the steering assist torque and the sensed hand torque data of the torque sensor. The first correspondence and the second correspondence may be the same or different. In this embodiment, for abnormal situations, a safety curve (i.e., the first correspondence) is re-calibrated as the curve when the vehicle enters the safe state, and is used to obtain the corresponding steering assist torque according to the hand force torque and the safety curve.

[0068] Among them, the safety curve is a curve calibrated based on abnormal situations, and the safety curve is used to characterize the mapping relationship between the hand force torque, vehicle speed, and steering assist.

[0069] Step S402: Obtain the steering assist torque according to the target hand force torque, the safety curve, and the current vehicle speed in the current vehicle driving data.

[0070] In the embodiment of the present application, when the hand force torque is the same, different vehicle speeds may correspond to different output steering assist torques. This safety curve combined with the vehicle speed can more accurately determine the steering assist torque and ensure driving safety.

[0071] The current vehicle speed can be obtained from the above current vehicle driving data. Of course, if the current vehicle speed does not exist in the current vehicle driving data, the vehicle speed data can be obtained from the corresponding sensor or CAN bus.

[0072] In one implementation manner, determining the target hand force torque according to the normal torque sensing data includes:

[0073] Using the normal torque sensing data as the target hand force torque.

[0074] Among them, for the abnormal type where only one torque sensing data is abnormal and the other torque sensing data is normal, the normal torque sensing data can be used to obtain the target hand force torque. At this time, the data is still in an abnormal situation, and the above safety curve needs to be used to obtain the steering assist torque, which can more accurately determine the magnitude of the steering assist torque and ensure driving safety.

[0075] See Figure 5 , which is a schematic flowchart of a steering assist control method provided in Embodiment 5 of the present application. On the basis that the hand force torque data includes two torque sensing data in the above Embodiment 2, as Figure 5 shown, in the above step S102, performing abnormal detection on the hand force torque data to obtain a data detection result, which may specifically further include the following steps:

[0076] Step S501: Perform single-channel verification on the two torque sensing data in the hand force torque data respectively to obtain the single-channel verification result of each torque sensing data.

[0077] Step S502: Perform synchronization verification on the difference between the two torque sensing data to obtain the synchronization verification result.

[0078] In the embodiment of the present application, the single-channel verification method is used to verify each torque sensing data respectively to obtain the corresponding verification result, and the synchronization verification method is used to verify the difference between the two torque sensing data to obtain the corresponding verification result.

[0079] Among them, the single-channel verification is used to characterize whether each data can pass the verification by itself. For example, verification using a communication protocol and verification using upper and lower limit thresholds are used. The synchronization verification is to judge the difference between the two torque sensing data. If the difference between the two torque sensing data is large and exceeds a threshold, it means that the two torque sensing data are inconsistent and the sensed data is incorrect. If the difference between the two torque sensing data is small and does not exceed a threshold, it means that the two torque sensing data are known and the sensed data may be valid data.

[0080] Step S503: If at least one of all the single-channel verification results and the synchronization verification result is abnormal, it is determined that the data detection result is abnormal.

[0081] Step S504: If none of all the single-channel verification results and the synchronization verification result is abnormal, it is determined that the data detection result is not abnormal.

[0082] Among them, only when none of all the single-channel verification results and the synchronization verification result is abnormal, the data detection result is not abnormal. The case of not being abnormal can refer to the method in Embodiment Seven below to determine the steering assist torque. In other cases, the data detection result is abnormal, and the steering assist torque can be determined according to the methods in Embodiments One to Four above.

[0083] The embodiment of the present application verifies the two torque sensing data, so as to give a more reasonable verification result, and then use corresponding processing measures based on this verification result to deal with different abnormal situations to ensure the driving safety of the vehicle.

[0084] See Figure 6 , which is a schematic flowchart of a steering assist control method provided by Embodiment Six of the present application. As Figure 6 shown, after the above step S503, the following steps may specifically be included:

[0085] Step S601: If the synchronization verification result is verification passed, and one of the two single-channel verification results is verification passed while the other is verification failed, then determine that the abnormal type in the data detection result is that one torque sensing data is normal and the other torque sensing data is abnormal.

[0086] Step S602: If the synchronization verification result is verification failed, or both of the two single-channel verification results are verification failed, then determine that the abnormal type in the data detection result is that both torque sensing data are abnormal.

[0087] In the embodiment of the present application, the determination of the abnormal type is adapted to the method for dividing the abnormal type in the second embodiment above. When the synchronization verification result is verification failed, or both of the two single-channel verification results are verification failed, it is impossible to determine the normal torque sensing data. Therefore, by using the processing method with the abnormal type that both torque sensing data are abnormal for processing, a relatively accurate steering assist torque can be obtained. Similarly, when the difference between the two torque sensing data is small and one of them is normal, the processing method corresponding to the normal torque sensing data can be used for processing, and a relatively accurate steering assist torque can be obtained.

[0088] See Figure 7 , which is a schematic flowchart of a steering assist control method provided in the seventh embodiment of the present application. As Figure 7 shown, in the above step S102, after performing abnormal detection on the hand force torque data to obtain the data detection result, the following steps are specifically further included:

[0089] Step S701: When there is no abnormality in the data detection result, determine the steering assist torque according to the hand force torque data.

[0090] Among them, in the case of no abnormality, the hand force torque data is normal data. Therefore, the hand force torque data can be used to determine the steering assist torque.

[0091] In an implementation manner, a normal assist curve is configured in the power steering system. The normal assist curve is a curve calibrated under the condition of normal torque sensing. The normal assist curve represents the mapping relationship among the hand force torque, vehicle speed, and steering assist torque. Based on this, the steering assist torque can be obtained according to the hand force torque data, so as to control the power steering system to perform assistance.

[0092] For the case where the above manual torque data includes two torque sensing data, both torque sensing data being normal may be that in the fifth embodiment above, if all single-channel verification results and synchronous verification results are normal, it is determined that the data detection result is normal. At this time, the average value of the two torque sensing data can be used as the manual torque, and according to this manual torque, the normal assist curve, the current vehicle speed, etc., the steering assist torque can be obtained.

[0093] See Figure 8 , which is a schematic structural diagram of an electric power steering system provided by the eighth embodiment of the present application. The Figure 8 modules herein are obtained by modularizing all the functions in the first to seventh embodiments above. Among them, taking EPS1 as an example, EPS1 drives a motor 3. In EPS1, there are a torque calculation and diagnosis module 11, a normal feel module 12, an arbitration module 13, a safety monitoring status judgment module 14, a torque self-learning module 15, and a safety feel module 16. In addition, EPS1 is connected to a torque sensor 2 to obtain two torque sensing data T1 and T2, and EPS1 is connected to a braking system 4 to obtain the driving data of the vehicle.

[0094] The torque calculation and diagnosis module 11 receives T1 and T2, processes the signals according to the sensor specification, first obtains two torque values Torque1 and Torque2, and then outputs the average value of the two torque values as Torque; on the other hand, the signals are diagnosed, including but not limited to communication protocol diagnosis, upper and lower limit diagnosis, and two-channel synchronization verification. The single-channel verification results are err_flagT1 and err_flagT2 respectively, and the synchronization verification diagnosis result is err_flagT. Among them, the signal content of err_flagX is that the signal is normal and equal to 0, and the signal is abnormal and equal to 1.

[0095] The normal feel module 12 receives Torque and the vehicle speed and its validity signal given by the braking system 4, and outputs a request torque AssistTorReq for assistance according to the normal feel function. The normal feel function module generally includes multiple modules, and the above-mentioned assist curves can be configured, for example, basic assist, return assist, damping assist, end protection, etc. The required signals are not limited to Torque and the vehicle speed and its validity signal.

[0096] The arbitration module 13 receives the Status signal from the safety monitoring status judgment module 14. When the value of the Status signal is 0, it indicates that all torque sensing data is normal. The arbitration module 13 outputs Torque_Arb to adopt the requested assist AssistTorReq of the normal feel module 12 and ignores the requested safety assist of the safety feel module 16. When the value of the Status signal is 1, it represents abnormal torque sensing. The arbitration module 13 outputs Torque_Arb to use the requested safety assist SafetyTorReq of the safety feel module 16. When the value of the Status signal is 2, it means that both the torque sensing data and the driving data are abnormal and the vehicle status cannot be determined. The arbitration module 13 directly cuts off the assist.

[0097] The safety monitoring status judgment module 14 receives Torque, Torque1, and Torque2 from the torque calculation and diagnosis module 11, as well as err_flagT, err_flagT1, and err_flagT2. It judges the values of the three err_flag values and obtains Status1, Status2, and Status. Status1 = 0 indicates that there is no abnormality in the torque signal. Status1 = 1 indicates that the torque signal on the T1 path is abnormal. Status1 = 2 indicates that the torque signal on the T2 path is abnormal. Status1 = 3 indicates that both torque signals are abnormal. Status2 is the validity of the driving data. When all driving data is valid, Status2 is 0. When at least one data is invalid, Status2 is 1. Status is obtained from Status1 and Status2. See Tables 1 and 2 as follows:

[0098] Table 1

[0099]

[0100] Table 2

[0101] Serial number Status1 Status2 Status 1 0 0 0 2 1 0 1 3 2 0 1 4 3 0 1 5 0 1 0 6 1 1 1 7 2 1 1 8 3 1 2

[0102] The torque self-learning module 15 bears the above torque self-learning model, and its trigger conditions and output logic are as follows:

[0103] (1) When Status1 = 0 and Status2 = 0, it indicates that both the torque signal and the driving data are normal. At this time, the self-learning module is activated to record the value of Torque, and the hand force torque output by the torque self-learning module = Torque;

[0104] (2) When Status1 = 0 and Status2 = 1, the driving data is abnormal, the self-learning module cannot be activated, and the hand force torque = Torque;

[0105] (3) When Status1 = 1 and Status2 = 0, T1 fails and the output manual torque = Torque2;

[0106] (4) When Status1 = 2 and Status2 = 0, T2 fails and the output manual torque = Torque1;

[0107] (5) When Status1 = 1 and Status2 = 1, T1 fails and the output manual torque = Torque2;

[0108] (6) When Status1 = 2 and Status2 = 1, T2 fails and the output manual torque = Torque1;

[0109] (7) When Status1 = 3 and Status2 = 0, both torque sensors fail and the output manual torque is equal to the calibrated torque output by the torque self - learning model;

[0110] (8) When Status1 = 3 and Status2 = 1, both torque sensors fail and the output value of the manual torque cannot be predicted according to the driving data, and the steering assist output needs to be directly cut off.

[0111] The safety feel module 16 internally calibrates a safety curve. This safety curve is calibrated independently of the feel module curve and is only related to the vehicle speed and the calibrated torque.

[0112] The embodiment of the present application further provides a vehicle, which includes the steering assist control method in the above - mentioned embodiment. Specifically, the device carrying this steering assist control method can be the controller of the power steering system in the vehicle.

[0113] In the above - mentioned embodiments, the descriptions of each embodiment have their own emphases. For the parts not detailed or recorded in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0114] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed in this article can be implemented by electronic hardware, or by a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of this application.

[0115] In the embodiments provided in the present application, it should be understood that the disclosed device / control device and method can be implemented in other ways. For example, the device / control device embodiments described above are only illustrative. For example, the division of modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling or direct coupling or communication connection between each other can be through some interfaces. The indirect coupling or communication connection of the device or unit can be in electrical, mechanical or other forms.

[0116] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0117] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A steering assist control method, characterized in that, the steering assist control method includes: Obtaining the hand force torque data of the driver controlling the vehicle to steer; Performing anomaly detection on the hand force torque data to obtain a data detection result; When the data detection result is abnormal, determining the target hand force torque according to the abnormal type in the data detection result; Determining the steering assist torque according to the safety curve when the vehicle enters the safe state and the target hand force torque, and providing steering assist to the vehicle according to the steering assist torque.

2. The steering assist control method according to claim 1, characterized in that, after performing anomaly detection on the hand force torque data to obtain a data detection result, it further includes: When the data detection result is not abnormal, determining the steering assist torque according to the hand force torque data.

3. The steering assist control method according to claim 1, characterized in that, the hand force torque data includes two torque sensing data, and determining the target hand force torque according to the abnormal type in the data detection result includes: If the abnormal type in the data detection result is that one torque sensing data is normal and the other torque sensing data is abnormal, determining the target hand force torque according to the normal torque sensing data; If the abnormal type in the data detection result is that both torque sensing data are abnormal, determining the target hand force torque according to the current vehicle driving data.

4. The steering assist control method according to claim 3, characterized in that, determining the target hand force torque according to the current vehicle driving data includes: Detecting whether the current vehicle driving data is valid data; If it is detected that the current vehicle driving data is valid data, using a torque self-learning model to perform torque calculation on the current vehicle driving data to obtain the target hand force torque; If it is detected that the current vehicle driving data is not valid data, determining that the target hand force torque is zero.

5. The steering assist control method according to claim 4, characterized in that, determining the steering assist torque according to the safety curve when the vehicle enters the safe state and the target hand force torque includes: Obtaining the safety curve when the vehicle enters the safe state, where the safety curve is a curve calibrated based on abnormal conditions, and the safety curve is used to characterize the mapping relationship between hand force torque, vehicle speed and steering assist; Obtaining the steering assist torque according to the target hand force torque, the safety curve and the current vehicle speed in the current vehicle driving data.

6. The steering assist control method according to claim 5, characterized in that, determining the target hand force torque according to the normal torque sensing data includes: Taking the normal torque sensing data as the target hand force torque.

7. The steering assist control method according to claim 3, characterized in that, performing anomaly detection on the hand force torque data to obtain a data detection result includes: Performing single-channel verification on the two torque sensing data in the hand force torque data respectively to obtain the single-channel verification result of each torque sensing data; Perform a synchronization check on the difference between the two torque sensing data to obtain a synchronization check result; If at least one of all the single-channel check results and the synchronization check result is abnormal, it is determined that the data detection result is abnormal; If none of all the single-channel check results and the synchronization check result is abnormal, it is determined that the data detection result is not abnormal.

8. The steering assist control method according to claim 7, wherein, after the step of if at least one of all the single-channel check results and the synchronization check result is abnormal, it is determined that the data detection result is abnormal, the method further includes: if the synchronization check result is passed, and one of the two single-channel check results is passed and the other is not passed, it is determined that the abnormal type in the data detection result is that one torque sensing data is normal and the other torque sensing data is abnormal.

9. The steering assist control method according to claim 7, wherein, after the step of if at least one of all the single-channel check results and the synchronization check result is abnormal, it is determined that the data detection result is abnormal, the method further includes: if the synchronization check result is not passed, or both of the two single-channel check results are not passed, it is determined that the abnormal type in the data detection result is that both torque sensing data are abnormal.

10. A vehicle, wherein, the vehicle includes the steering assist control method according to any one of claims 1 to 9.

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