Automobile headlamp automatic adjusting system and automobile

Abstract

According to the automobile headlamp automatic adjusting system and the automobile, a passenger detection module in the automobile headlamp automatic adjusting system detects passenger riding state data, and a mechanical calculation module calculates the pitching angle of an automobile body according to the passenger riding state data; the fuzzy algorithm control module carries out fuzzy algorithm processing on the input variable to obtain a headlamp adjusting angle, and the execution module carries out angle adjustment on the headlamp optical axis of the automobile through a headlamp adjusting motor according to the headlamp adjusting angle. According to the invention, the posture of the headlamp can be corrected in real time according to the change of the riding state of the passenger, so that the actual optical axis direction of the headlamp is always kept the same as or close to the normal optical axis direction, thereby reducing the influence of the posture change of the automobile body on the optical axis direction of the headlamp due to the passenger getting on and off the automobile; therefore, a driver can obtain a proper irradiation range of the headlamp, a safe driving environment is created, and traffic safety is guaranteed. The invention is widely applied to the technical field of automobiles.

Description

Technical Field

[0001] The present invention relates to the technical field of automobiles, in particular to an automatic adjustment system for automobile headlights and an automobile. Background Art

[0002] The headlights of a car can illuminate the area in front of the car, allowing the driver to see the traffic conditions in the area in front of the car clearly even in poor lighting conditions such as at night and when entering a tunnel, thereby driving safely.

[0003] The direction of a car's headlights' optical axis affects the headlight's illumination angle, and thus the headlight's illumination range. The headlight's optical axis must be maintained in the correct position. A misaligned optical axis can affect driving safety and increase the risk of accidents. For example, if the optical axis is tilted upward, it can cause glare to oncoming vehicles. If it's tilted downward, the headlight's illumination range is too narrow, affecting the driver's field of vision and making it difficult to see the road ahead.

[0004] During vehicle production and maintenance, the optical axis direction of the vehicle's headlights can be checked and adjusted to the appropriate position by adjusting the headlight's position and orientation. However, since the headlights are mounted at the front of the vehicle, their orientation is susceptible to changes in the vehicle's body position. Therefore, even after an adjustment, the orientation of the headlights may shift during vehicle use, causing optical axis deviation and posing a significant traffic safety risk. Summary of the Invention

[0005] In view of the technical problems that the posture of current automobile headlights changes with the posture of the vehicle body, thereby posing a greater traffic safety risk, the purpose of the present invention is to provide an automatic adjustment system for automobile headlights and an automobile.

[0006] In one aspect, an embodiment of the present invention includes an automatic headlight adjustment system for an automobile, the automatic headlight adjustment system for an automobile including:

[0007] An occupant detection module is used to detect occupant riding status data;

[0008] A mechanical calculation module, configured to calculate a vehicle body pitch angle based on the passenger riding state data;

[0009] a fuzzy algorithm control module, configured to perform fuzzy algorithm processing on input variables to obtain a headlight adjustment angle; the input variables are determined based on the vehicle body pitch angle, suspension compression, and slope information;

[0010] The execution module is used to adjust the angle of the light axis of the vehicle's headlights through the headlight adjustment motor according to the headlight adjustment angle.

[0011] Furthermore, the detecting of the passenger's riding status data includes:

[0012] Detect the seating status, weight and position distribution of passengers in each seat of the car;

[0013] The occupant riding state data is composed of the riding state, occupant weight, and position distribution.

[0014] Furthermore, the calculating of the vehicle body pitch angle according to the occupant riding state data includes:

[0015] Calculating front axle load information and rear axle load information of the vehicle according to the passenger riding state data;

[0016] Calculating front suspension compression and rear suspension compression according to the front axle load information and the rear axle load information;

[0017] The vehicle body pitch angle is calculated according to the front suspension compression amount and the rear suspension compression amount.

[0018] Furthermore, the calculating of the front axle load information and the rear axle load information of the vehicle according to the passenger riding state data includes:

[0019] Setting a weight coefficient for each passenger seat on the vehicle; the weight coefficient represents the proportion of the passenger seat's weight distributed to the front axle;

[0020] According to the formula

[0021]

[0022] Calculate; where ΔW front is the front axle load information, ΔW rear is the rear axle load information, N is the total number of passenger seats on the car, K i is the weight coefficient of the occupant on the i-th seat in the car, m i is the weight data of the occupant in the i-th seat in the car, and g is the acceleration due to gravity.

[0023] Furthermore, the calculating of the front axle load information and the rear axle load information of the vehicle according to the passenger riding state data includes:

[0024] Get the wheelbase of the car;

[0025] Obtain the distance between the center of mass of each passenger seat on the vehicle and the front axle;

[0026] According to the formula

[0027]

[0028] Calculate; where ΔW front is the front axle load information, ΔW rear is the rear axle load information, N is the total number of passenger seats on the car, m i is the weight data of the occupant on the i-th seat in the car, g is the acceleration of gravity, L wheelbase is the wheelbase of the car, l_f i is the distance between the center of mass of the occupant in the i-th seat and the front axle of the car.

[0029] Furthermore, the calculating of the front axle load information and the rear axle load information of the vehicle based on the passenger riding state data includes:

[0030] Get the wheelbase of the car;

[0031] Obtain the distance between the center of mass of each passenger seat on the vehicle and the front axle;

[0032] Get the total weight, longitudinal acceleration and center of mass height of the car including all passengers;

[0033] According to the formula

[0034]

[0035] Calculate; where ΔW front is the front axle load information, ΔW rear is the rear axle load information, N is the total number of passenger seats on the car, m i is the weight data of the occupant on the i-th seat in the car, g is the acceleration of gravity, L wheelbase is the wheelbase of the car, l_f i is the distance between the center of mass of the occupant on the i-th seat and the front axle, W is the total weight, a x is the longitudinal acceleration, h cg is the height of the center of mass.

[0036] Furthermore, the calculating of the front suspension compression and the rear suspension compression according to the front axle load information and the rear axle load information includes:

[0037] Obtaining a suspension force-displacement curve; the suspension force-displacement curve represents a corresponding relationship between suspension compression and load;

[0038] determining the front suspension compression amount according to the front axle load information and the suspension force-displacement curve;

[0039] The rear suspension compression amount is determined according to the rear axle load information and the suspension force-displacement curve.

[0040] Furthermore, the calculating of the front suspension compression and the rear suspension compression according to the front axle load information and the rear axle load information includes:

[0041] Obtain the front suspension stiffness, rear suspension stiffness, front tire stiffness, and rear tire stiffness of the vehicle;

[0042] According to the formula

[0043]

[0044] Calculate; where K eq_front is the equivalent stiffness of the front suspension, K SUS_front (Δh front ) is the front suspension stiffness, Δh front is the front suspension compression, K tire_front is the front tire stiffness, K eq_rear is the equivalent stiffness of the rear suspension, K SUS_rear (Δh rear ) is the rear suspension stiffness, Δh rear is the rear suspension compression, K tire_rear is the rear tire stiffness;

[0045] Pair equation

[0046]

[0047] Solve to determine the front suspension compression Δh front and the rear suspension compression Δh rear .

[0048] Furthermore, the performing of fuzzy algorithm processing on the input variables to obtain the headlight adjustment angle includes:

[0049] Detect the slope information of the car's current location;

[0050] Acquire multiple fuzzy sets of the vehicle body pitch angle, multiple fuzzy sets of the front suspension compression amount, multiple fuzzy sets of the rear suspension compression amount, and multiple fuzzy sets of the slope information to form the input variables;

[0051] Establish a fuzzy rule base based on expert experience;

[0052] Fuzzy reasoning is performed according to the input variables and the fuzzy rule base to obtain the headlight adjustment angle.

[0053] On the other hand, an embodiment of the present invention further includes a car, comprising:

[0054] An automatic adjustment system for automobile headlights in an embodiment.

[0055] The beneficial effects of the present invention are as follows: the automatic adjustment system for automobile headlights in the embodiment can realize automatic angle adjustment of the headlights, thereby eliminating the need for manual operation, and can correct the posture of the headlights in real time according to changes in the riding status of the occupants, so that the actual optical axis direction of the headlights always remains the same as or close to the normal optical axis direction, thereby reducing the impact of changes in the posture of the automobile body caused by the occupants getting on and off the vehicle on the optical axis direction of the headlights, so that the driver can obtain an appropriate illumination range of the headlights, thereby creating a safe driving environment and ensuring traffic safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 Schematic diagram of the principle of the automatic adjustment system for automobile headlights applied in the embodiment;

[0057] Figure 2 This is a schematic diagram of the structure of the automatic adjustment system for automobile headlights used in the embodiment;

[0058] Figure 3 Schematic diagram of the steps of applying the method for automatically adjusting automobile headlights in an embodiment. DETAILED DESCRIPTION

[0059] Reference Figure 1 During production or routine maintenance, the position and posture of the headlights can be adjusted so that the optical axis of the headlights is in the appropriate position, that is, the headlights have the normal optical axis direction indicated by the blue line. However, when passengers (including the driver, non-drivers, and their luggage) enter the vehicle, their weight will exert downward pressure on the vehicle body, causing the posture of the vehicle body to change, causing the headlights to have the actual optical axis direction indicated by the yellow line. If the headlight posture is not adjusted, the actual optical axis direction will deviate from the normal optical axis direction, thus causing traffic safety risks.

[0060] Due to the different weights and positions of passengers in the vehicle, the posture of the vehicle body changes differently, resulting in different actual optical axis directions. Therefore, the vehicle headlights can be configured to be posture-adjustable (only the vertical adjustment degree of freedom can be considered), and the headlight posture can be adjusted using an actuator module such as an adjustment motor. The headlight adjustment angle is determined based on the passenger's riding state, that is, the actual optical axis direction of the vehicle headlight is adjusted to the same angle as the normal optical axis direction. The actuator module is controlled to adjust the headlight posture according to the headlight adjustment angle. The above process can be performed dynamically, for example, by setting multiple adjustment times, detecting the passenger's riding state at each adjustment time, calculating the headlight adjustment angle in real time, and controlling the actuator module to adjust the headlight posture in real time. This allows the actuator module to adjust the headlight posture in real time based on the changes in the passenger's riding state, so that the actual optical axis direction of the headlight always remains the same as or close to the normal optical axis direction, thereby reducing the impact of the vehicle body posture changes caused by passengers getting on and off the vehicle on the headlight optical axis direction.

[0061] Based on the above principles, in this embodiment, a system for automatically adjusting automobile headlights is provided. Figure 2 The automatic headlight adjustment system for a vehicle includes an occupant detection module, a mechanical calculation module, a fuzzy algorithm control module, and an execution module. Specifically, weight sensors distributed across the vehicle's passenger seats (including the driver's seat and non-driver's seats, and also the front trunk or rear trunk) can serve as the occupant detection module, an electronic control unit (ECU) (specifically, the software algorithm running therein) can serve as the mechanical calculation module and the fuzzy algorithm control module, and an adjustment motor can serve as the execution module.

[0062] By running the automatic headlight adjustment system, you can run the automatic headlight adjustment method. Figure 3 , the method for automatically adjusting automobile headlights includes the following steps:

[0063] S1. Detecting passenger riding status data;

[0064] S2. Calculate the vehicle pitch angle based on the occupant status data;

[0065] S3. Perform fuzzy algorithm processing on the input variables to obtain the headlight adjustment angle; the input variables are determined based on the vehicle body pitch angle, front and rear suspension compression, slope information, etc.

[0066] S4. Adjust the angle of the light axis of the vehicle's headlights through the headlight adjustment motor according to the headlight adjustment angle.

[0067] Among them, step S1 is executed by the occupant detection module, step S2 is executed by the mechanical calculation module, step S3 is executed by the fuzzy algorithm control module, and step S4 is executed by the execution module.

[0068] By executing steps S1-S4, the headlights can be automatically adjusted in angle without manual operation. The posture of the headlights can be corrected in real time according to changes in the passengers' riding status, so that the actual optical axis direction of the headlights always remains the same as or close to the normal optical axis direction, thereby reducing the impact of changes in the posture of the car body caused by passengers getting on and off the car on the optical axis direction of the headlights, so that the driver can obtain the appropriate illumination range of the headlights, thereby creating a safe driving environment and ensuring traffic safety.

[0069] In this embodiment, when executing step S1, the occupant detection module can detect the occupant sitting status, occupant weight and position distribution on each seat in the car; the occupant sitting status data is composed of the above-mentioned sitting status, occupant weight and position distribution.

[0070] For example, taking the weight sensors installed at passenger seats S1 (driver's seat), S2 (passenger seat), S3 (left rear seat), S4 (middle rear seat) and S5 (right rear seat) as an example, the weight data m1g of passenger seat S1, the weight data m2g of passenger seat S2, the weight data m3g of passenger seat S3, the weight data m4g of passenger seat S4 and the weight data m5g of passenger seat S5 can be detected respectively, forming vector data [m1g, m2g, m3g, m4g, m5g] as passenger riding status data.

[0071] In this embodiment, m1g and the like can be precise weight data (for example, with an accuracy of 1kg), or data that is categorized into light load (indicating less than 50kg), medium load (indicating greater than 50kg and less than 75kg), or heavy load (indicating greater than 75kg). Alternatively, data coded as 0 (indicating a weight less than a threshold and no passenger is seated) or 1 (indicating a weight greater than a threshold and a passenger is seated, with the passenger weight set to 75kg according to industry practice). In this embodiment, precise weight data is used as an example for illustration.

[0072] In this embodiment, when the mechanical calculation module executes step S2, that is, the step of calculating the vehicle body pitch angle based on the passenger seating state data, the following steps may be specifically performed:

[0073] S201. Calculate the front axle load information and rear axle load information of the vehicle based on the occupant status data;

[0074] S202. Calculate the front suspension compression and the rear suspension compression based on the front axle load information and the rear axle load information;

[0075] S203. Calculate the vehicle body pitch angle based on the front suspension compression and the rear suspension compression.

[0076] In this embodiment, when the mechanical calculation module executes step S201, that is, the step of calculating the front axle load information and the rear axle load information of the vehicle based on the passenger riding state data, the following steps may be specifically performed:

[0077] S20101A. Set the weight coefficient of each passenger seat on the car;

[0078] S20102A. According to the formula

[0079]

[0080] Perform calculations.

[0081] Steps S20101A-S20102A are the first execution method of step S201.

[0082] In this embodiment, each passenger seat in the car is numbered respectively. After numbering, the i-th passenger seat in the car, when i=1, 2, 3, 4, 5, represents the driver's seat, the front passenger seat, the rear left seat, the rear middle seat and the rear right seat respectively.

[0083] In step S20101A, for the i-th passenger seat on the car, its weight coefficient is determined to be K i , and stored in the electronic control unit ECU, and read when executing step S20101B. i It represents the ratio of the load on the ith passenger seat (the weight of the passenger) distributed to the front axle of the car, that is, the load m of the ith passenger seat i The load g transmitted to the front axle of the car is K i m i g, accordingly, the load transmitted to the rear axle of the car is (1-K i )m i g.

[0084] In this embodiment, K i is a constant that can be calibrated by the car manufacturer during design or production. For example, in a certain car model, the driver's seat is i=1, and K i=0.667. When a passenger with a mass of 75kg sits in the driver's seat, the load transmitted to the front axle of the car by the driver's seat is equivalent to the load generated by a mass of 75kg×0.667=50kg, and the load transmitted to the front axle of the car is equivalent to the load generated by a mass of 25kg.

[0085] In step S20102A, assuming that the car is provided with a driver's seat, a passenger seat, a rear left seat, a rear middle seat, and a rear right seat, the total number of passenger seats N in the car is 5, m i g can be obtained from the passenger's riding state detected in step S1. Finally, the front axle load information ΔW is calculated. front and rear axle load information ΔW rear .

[0086] In this embodiment, the front axle load information ΔW calculated by steps S20101A-S20102A is front The rear axle load information ΔW represents the total load generated by all passengers in the vehicle's passenger seats (some passenger seats may not have passengers sitting) and is transmitted to the front axle. rear This refers to the portion of the total load generated by the occupants of all passenger seats in the vehicle that is transmitted to the rear axle.

[0087] In this embodiment, when the mechanical calculation module executes step S201, that is, the step of calculating the front axle load information and the rear axle load information of the vehicle based on the passenger riding state data, the following steps may be specifically performed:

[0088] S20101B. Get the wheelbase of the car;

[0089] S20102B obtains the distance between the center of mass position of each passenger seat on the car and the front axle;

[0090] S20103B. According to the formula

[0091]

[0092]

[0093] Calculate; where ΔW front is the front axle load information, ΔW rear is the rear axle load information, N is the total number of passenger seats on the car, m i is the weight of the occupant on the i-th seat in the car, g is the acceleration of gravity, L wheelbase is the wheelbase of the car, l_f i is the distance between the center of mass of the occupant in the i-th seat and the front axle of the car.

[0094] Steps S20101B-S20103B are a second execution method of step S201.

[0095] In step S20101B, the wheelbase L of the car wheelbase It is a constant, which can be calibrated by the manufacturer of the car during design or production, and stored in the electronic control unit ECU, and read when executing step S20101B.

[0096] In step S20102B, if the position of the passenger seat is not adjustable, the distance l_f between the center of mass of the i-th passenger seat and the front axle is i is a constant, which can be calibrated by the automobile manufacturer during design or production and stored in the electronic control unit ECU, and read when executing step S20102B. In the case that the position of the passenger seat is adjustable, the electronic control unit ECU can call the passenger seat position sensor to detect the current position of the passenger seat (specifically, the position of a certain point on the passenger seat), and use the current position of the passenger seat as the center of mass position to calculate the distance l_f between the center of mass position of the occupant on the i-th seat and the front axle. i .

[0097] In step S20103B, the front axle load information ΔW is calculated. front and rear axle load information ΔW rear , which has the same meaning as the front axle load information ΔW calculated in steps S20101A-S20102A front and rear axle load information ΔW rear same.

[0098] The front axle load information ΔW calculated in steps S20101A-S20102A front and rear axle load information ΔW rear Compared to the calculation of front axle load information ΔW in steps S20101B-S20103B front and rear axle load information ΔW rear The relative position relationship between the occupant position and the axle is also introduced to obtain more accurate front axle load information ΔW front and rear axle load information ΔW rear .

[0099] In this embodiment, when the mechanical calculation module executes step S201, that is, the step of calculating the front axle load information and the rear axle load information of the vehicle based on the passenger riding state data, the following steps may be specifically performed:

[0100] S20101C. Get the wheelbase of the car;

[0101] S20102C obtains the distance between the center of mass position of each passenger seat on the vehicle and the front axle;

[0102] S20103C obtains the total weight of the vehicle including all occupants, longitudinal acceleration and center of mass height;

[0103] S20104C. According to the formula

[0104]

[0105] Perform calculations.

[0106] Steps S20101C-S20104C are the third execution method of step S201.

[0107] The principles of steps S20101C-S20102C are the same as those of steps S20101B-S20102B.

[0108] In step S20103C, the vehicle can be calibrated during production or maintenance to obtain the vehicle's curb mass W0, which is stored in the electronic control unit ECU as a constant. The total weight W of the vehicle including all passengers is the sum of the curb mass W0 and the weight of all passengers, which can be calculated by the formula

[0109]

[0110] Calculated.

[0111] In step S20103C, the electronic control unit ECU can call the acceleration sensor set on the car to detect the current longitudinal acceleration a of the car. x Among them, the longitudinal acceleration a x Indicates the acceleration of the car in the direction of the line connecting the rear and the front of the car.

[0112] In step S20103C, the centroid height h to be obtained cg Indicates the height of the vehicle's center of mass from the ground when the vehicle is loaded. Specifically, when a sensor is installed, the electronic control unit ECU can call the center of mass height h detected by the sensor. cg In the absence of a sensor, the center of mass height of the vehicle under half load can be obtained by calibration and stored in the electronic control unit ECU as a constant. The electronic control unit ECU calls the center of mass height under half load as the center of mass height h to be obtained in step S20103C. cg .

[0113] In step S20104C, the front axle load information ΔW is calculated. front and rear axle load information ΔW rear, which has the same meaning as the front axle load information ΔW calculated in steps S20101A-S20102A or S20101B-S20103B front and rear axle load information ΔW rear same.

[0114] and the front axle load information ΔW calculated in steps S20101B-S20103B front and rear axle load information ΔW rear Compared to the above, steps S20101C-S20104C calculate the front axle load information ΔW front and rear axle load information ΔW rear The influence of vehicle acceleration and deceleration is also taken into account to obtain more accurate front axle load information ΔW front and rear axle load information ΔW rear .

[0115] In this embodiment, when executing step S20103C, if the detected longitudinal acceleration a x If the load is within a specific range (e.g. 0.1g-0.5g, indicating that the vehicle is in a gentle acceleration / deceleration state), then step S20104C can be continued to obtain the front axle load information ΔW. front and rear axle load information ΔW rear On the contrary, if the detected longitudinal acceleration a x Outside the specific range, step S20104C will not be executed. The principle is that when the longitudinal acceleration a x Outside the specific range, it means that the car is undergoing rapid acceleration and deceleration, which is an emergency situation. At this time, the car body posture changes dramatically and the driver's attention is also focused on dealing with the emergency situation. Therefore, this working condition is not considered.

[0116] In this embodiment, when the mechanical calculation module executes step S202, that is, the step of calculating the front suspension compression and the rear suspension compression based on the front axle load information and the rear axle load information, the following steps may be specifically performed:

[0117] S20201A. Obtain the suspension force-displacement curve;

[0118] S20202A. Determine the front suspension compression based on the front axle load information and the suspension force-displacement curve;

[0119] S20203A. Determine the rear suspension compression based on the rear axle load information and the suspension force-displacement curve.

[0120] Steps S20201A-S20203A are the first execution method of step S202.

[0121] In step S20201A, the automobile manufacturer can calibrate the compression and force of the automobile's suspension through a test bench to obtain multiple suspension compressions and the suspension load corresponding to each suspension compression; these suspension compressions and their corresponding suspension loads are fitted into a curve (generally, they can be fitted into a high-order polynomial curve, such as a quintic curve or a sextic curve), thereby obtaining a suspension force-displacement curve representing the corresponding relationship between the suspension compression and the suspension load.

[0122] In step S20201A, during calibration, the same calibration process can be used for the front suspension and rear suspension of the vehicle to obtain a suspension force-displacement curve applicable to both the front suspension and the rear suspension. Alternatively, the front suspension and the rear suspension can be calibrated separately to obtain a suspension force-displacement curve specifically for the front suspension and a suspension force-displacement curve specifically for the rear suspension.

[0123] The suspension force displacement curve obtained in step S20201A can be expressed as

[0124] Δh=γ6x 6 +γ5x 5 +γ4x 4 +γ3x 3 +γ2x 2 +γ1x 1 +γ0. Among them, Δh represents the suspension compression, γ0, γ1, γ2, γ3, γ4, γ5 and γ6 are fitting coefficients, which can be stored in the electronic control unit ECU; x represents the load. For example, when the suspension force displacement curve is used for the front suspension, x can be calculated by taking half of the front axle load information, that is, When the suspension force displacement curve is used for the rear suspension, x can be calculated by taking half of the rear axle load information, that is,

[0125] In step S20202A, the front axle load information ΔW can be front Substitute into the suspension force displacement curve to calculate the front suspension compression Δh front In step S20203A, the rear axle load information ΔW rear Substitute into the suspension force displacement curve to calculate the rear suspension compression Δh rear .

[0126] Specifically, if a general suspension force-displacement curve is used, then the suspension force-displacement curves in step S20202A and step S20203A are the same suspension force-displacement curve; if a dedicated suspension force-displacement curve is used, then the suspension force-displacement curve in step S20202A is a suspension force-displacement curve dedicated to the front suspension, and the suspension force-displacement curve in step S20203A is a suspension force-displacement curve dedicated to the rear suspension.

[0127] The front suspension compression amount Δh calculated by executing steps S20201A-S20203A front Indicates the travel of the front suspension of the vehicle compressed by the weight of the occupant (the distance between the occupant and the front axle and the acceleration of the vehicle may also be considered) when the occupant's riding status data is detected by the occupant detection module; the rear suspension compression amount Δh calculated by executing steps S20201A-S20203A rear It indicates the stroke by which the rear suspension of the vehicle is compressed due to the weight of the occupant (the distance between the occupant and the front axle and the acceleration of the vehicle may also be considered) when the occupant detection module detects the occupant's riding status data.

[0128] In this embodiment, when the mechanical calculation module executes step S202, that is, the step of calculating the front suspension compression and the rear suspension compression based on the front axle load information and the rear axle load information, the following steps may be specifically performed:

[0129] S20201B. Obtain the front suspension stiffness, rear suspension stiffness, front tire stiffness, and rear tire stiffness of the vehicle;

[0130] S20202B. According to the formula

[0131]

[0132] Perform calculations;

[0133] S20203B. For Eq.

[0134]

[0135] Solve to determine the front suspension compression Δh front and rear suspension compression Δh rear .

[0136] Steps S20201B-S20203B are a second execution method of step S202.

[0137] In step S20201B, the front tire stiffness K tire_front and rear tire stiffness K tire_rear It can be a constant, which can be specifically calibrated by the manufacturer of the automobile during design or production, and stored in the electronic control unit ECU, and read when executing step S20201B.

[0138] In step S20201B, the front suspension stiffness K of the vehicle SUS_front (Δh front ) represents the stiffness of the front suspension itself, which is generally a function of the front suspension compression Δh front(At this time, the front suspension compression amount Δh front The variable related to the problem (yet to be determined) is generally a piecewise function containing linear and nonlinear regions, which can be expressed as

[0139]

[0140] Among them, h preload is the linear pre-compression of the front suspension, β is the stiffness gradient coefficient, which can be obtained by suspension bench calibration. preload and β.

[0141] Similarly, the rear suspension stiffness K of the car SUS_rear (Δh rear ) represents the stiffness of the rear suspension itself, which is generally a function of the rear suspension compression Δh rear (At this time, the rear suspension compression amount Δh rear Rear suspension stiffness K SUS_rear (Δh rear ) can be compared with the front suspension stiffness K SUS_front (Δh front ), it is represented as a piecewise function containing linear and nonlinear regions.

[0142] In step S20202B, the calculated K eq_front is the equivalent stiffness of the front suspension, which represents the stiffness of the entire front suspension and front tire. Similarly, the calculated K eq_rear is the equivalent stiffness of the rear suspension, which represents the stiffness of the entire rear suspension and front tire. The calculated equivalent stiffness of the front suspension K eq_front The unknown quantity front suspension compression Δh is included front , rear suspension equivalent stiffness K eq_rear The unknown quantity rear suspension compression Δh is included in rear .

[0143] At the same time, the front suspension equivalent stiffness K eq_front and front suspension compression Δh front Satisfaction relationship

[0144]

[0145] The front axle load information ΔW front It has been calculated in step S201, so this equation can be solved to calculate the front suspension compression Δh front Similarly, the equivalent stiffness of the rear suspension K eq_rear and rear suspension compression Δh rear Satisfaction relationship

[0146]

[0147] The rear axle load information ΔW rear It has been calculated in step S201, so this equation can be solved to calculate the rear suspension compression Δh rear .

[0148] The suspension compression Δh calculated by executing steps S20201B-S20203B front and rear suspension compression Δh rear , and the suspension compression Δh calculated by executing steps S20201A-S20203A front and rear suspension compression Δh rear Have the same meaning.

[0149] The suspension compression amount Δh is calculated by executing step S202 front and rear suspension compression Δh rear Afterwards, the mechanical calculation module can execute step S203, according to the front suspension compression Δh front and rear suspension compression Δh rear , through the formula

[0150]

[0151] Calculate the vehicle body pitch angle θ. The vehicle body pitch angle θ represents the angle at which the front of the vehicle rises or falls.

[0152] For example, the current suspension compression Δh front Less than the rear suspension compression Δh rear , the vehicle body pitch angle θ is negative, which means that the angle at which the front of the vehicle is tilted upward is θ (take the absolute value).

[0153] By executing step S2, the vehicle body pitch angle θ and the front suspension compression Δh can be obtained. front and rear suspension compression Δh rear These data are accurate values ​​and can be used to directly determine the headlight adjustment angle based on the vehicle body pitch angle θ. For example, the vehicle body pitch angle θ can be used as the headlight adjustment angle. When θ is negative, it indicates that the front of the vehicle is tilted upward. When the execution module executes step S4, it can drive the headlights to rotate downward by an angle θ (taken as an absolute value) based on the size of the headlight adjustment angle. When θ is positive, it indicates that the front of the vehicle is pressed downward. When the execution module executes step S4, it can drive the headlights to rotate upward by an angle θ (taken as an absolute value) based on the size of the headlight adjustment angle.

[0154] While driving a car, although the weight and position distribution of occupants are generally stable, the occupant status data detected by the occupant detection module may change over time due to factors such as bumps. The vehicle body pitch angle θ obtained in step S2 also changes over time. If the headlight adjustment angle is determined directly based on the vehicle body pitch angle θ, on the one hand, the execution module may need to operate continuously, and on the other hand, the optical axis of the headlights may change too frequently, resulting in a poor driver's field of vision. Therefore, in this embodiment, when the fuzzy algorithm control module executes step S3, i.e., performing fuzzy algorithm processing on the input variables to obtain the headlight adjustment angle, the following steps may be performed:

[0155] S301. Detecting the slope information of the current location of the car;

[0156] S302. Obtain multiple fuzzy sets of vehicle body pitch angles, multiple fuzzy sets of front suspension compression amounts, multiple fuzzy sets of rear suspension compression amounts, and multiple fuzzy sets of ramp information to form input variables;

[0157] S303. Establish a fuzzy rule base based on expert experience;

[0158] S304. Perform fuzzy reasoning based on the input variables and the fuzzy rule base to obtain the headlight adjustment angle.

[0159] In step S301 , the fuzzy algorithm control module may call the slope angle sensor of the vehicle to detect the slope information α of the current position of the vehicle.

[0160] In step S302, the vehicle body pitch angle θ and the front suspension compression amount Δh are calculated. front , rear suspension compression Δh rear The slope information α is fuzzy processed to obtain the input variables.

[0161] Specifically, for the front suspension compression amount Δh front , can be divided into three fuzzy sets: small (S), medium (M), and large (L); for the rear suspension compression Δh rear, can be divided into three fuzzy sets: small (S), medium (M), and large (L); the vehicle pitch angle θ can be divided into five fuzzy sets: negative large (NB), negative small (NS), zero (Z), positive small (PS), and positive large (PB); the slope information α can be divided into five fuzzy sets: zero (Z), uphill small (SS), uphill large (SL), downhill small (XS), and downhill large (XL). The headlight adjustment angle γ can be divided into five fuzzy sets: negative large (NB, downward adjustment -0.25° to -0.1°), negative small (NS, downward fine adjustment -0.15° to -0.05°), zero (Z, no adjustment -0.05° to 0.05°), positive small (PS, upward fine adjustment 0.05° to 0.15°), and positive large (PB, upward adjustment 0.15° to 0.25°).

[0162] In step S302, according to the vehicle body pitch angle θ, the front suspension compression amount Δh front , rear suspension compression Δh rear and the exact value of the ramp information α to determine the membership of each fuzzy set.

[0163] In step S303, a fuzzy rule base can be established based on the experience of automotive experts. The fuzzy rule base includes multiple rules, some of which are as follows:

[0164] Rule 1: If the front suspension compression Δh front is small, rear suspension compression Δh rear is medium, the slope information α is zero, and the vehicle body pitch angle θ is negative medium, then the headlight adjustment angle γ is negative medium (indicating that the front of the vehicle body is higher than the rear, the vehicle is not on a slope, and the headlights should be adjusted downward by an appropriate amount);

[0165] Rule 2: If the front suspension compression Δh front is small, rear suspension compression Δh rear If the slope information α is small and the vehicle body pitch angle θ is zero, the headlight adjustment angle γ is positive and small (indicating that the front and rear of the vehicle body change synchronously, the vehicle is on a downhill slope, the slope is small, a small part of the vehicle body load is transferred to the front axle, and the headlights need to be slightly adjusted upwards)

[0166] Rule 3: If the front suspension compression Δh front is small, rear suspension compression Δh rear is medium, the slope information α is large uphill, and the vehicle body pitch angle θ is negative medium, then the headlight adjustment angle γ is negative large (indicating that the front of the vehicle body is high and the back is low, the car is on an uphill slope, the slope is large, most of the load of the vehicle body is transferred to the rear axle, and the headlights need to be adjusted downward significantly).

[0167] S304. Perform fuzzy reasoning based on the input variables and the fuzzy rule base to obtain the headlight adjustment angle.

[0168] In step S304, the activation strength of each rule can be calculated based on the membership determined in step S302 and the rule obtained in step S303. For example, for a rule, the membership of all fuzzy sets corresponding to the rule can be ANDed, that is, the minimum value among all memberships can be taken to obtain the membership output of the rule. The membership of all rules forms a membership distribution curve, which can be defuzzified using the centroid method. Specifically, the centroid of the area under the membership curve can be calculated, and the precise value of the headlight adjustment angle can be determined based on the position of the centroid.

[0169] After executing steps S301-S304 to obtain the precise value of the headlight adjustment angle, the fuzzy algorithm control module transmits this precise value to the execution module. In step S4, the execution module drives the headlights to rotate vertically based on the precise value of the headlight adjustment angle, thereby reducing or offsetting the downward pressure of the vehicle body caused by the weight of the occupants, as well as the deviation of the actual optical axis from the normal optical axis caused by the vehicle's nose tilting due to bumps during driving. Furthermore, by using the fuzzy algorithm, it can simulate the control thinking of a person driving a car, similar to "there are a lot of passengers in the back row, the vehicle body is slightly higher in front and lower in the back, and the headlights need to be adjusted slightly upward." This makes the headlight angle adjustment more consistent with the user's usage habits and improves the user experience.

[0170] It should be noted that, unless otherwise specified, when a feature is referred to as being "fixed" or "connected" to another feature, it may be directly fixed or connected to the other feature, or it may be indirectly fixed or connected to the other feature. In addition, the descriptions of up, down, left, right, etc. used in this disclosure are only relative to the relative positional relationships of the components of the present disclosure in the accompanying drawings. The singular forms of "a", "" and "the" used in this disclosure are also intended to include the plural forms, unless the context clearly indicates otherwise. In addition, unless otherwise defined, all technical and scientific terms used in this embodiment have the same meaning as those generally understood by those skilled in the art. The terms used in the specification of this embodiment are only for describing specific embodiments and are not intended to limit the invention. The term "and / or" used in this embodiment includes any combination of one or more related listed items.

[0171] It should be understood that, although the present disclosure may adopt the term first, second, third etc. to describe various elements, these elements should not be limited to these terms.These terms are only used to distinguish the elements of the same type from each other.For example, without departing from the scope of the present disclosure, the first element may also be referred to as the second element, and similarly, the second element may also be referred to as the first element.The use of any and all examples or exemplary language ("for example", "such as" etc.) provided by the present embodiment is only intended to better illustrate embodiments of the present invention, and unless otherwise required, the scope of the present invention will not be limited.

[0172] It should be appreciated that embodiments of the present invention can be implemented or practiced by computer hardware, a combination of hardware and software, or by computer instructions stored in a non-transitory computer-readable memory. The methods can be implemented in a computer program using standard programming techniques - including a non-transitory computer-readable storage medium configured with a computer program, wherein the storage medium so configured causes the computer to operate in a specific and predefined manner - according to the methods and figures described in the specific embodiments. Each program can be implemented in a high-level procedural or object-oriented programming language to communicate with the computer system. However, if desired, the program can be implemented in assembly or machine language. In any case, the language can be a compiled or interpreted language. In addition, the program can be run on a programmed application-specific integrated circuit for this purpose.

[0173] In addition, the operations of the processes described in this embodiment may be performed in any suitable order, unless otherwise indicated in this embodiment or otherwise clearly contradicted by the context. The processes described in this embodiment (or variations and / or combinations thereof) may be performed under the control of one or more computer systems configured with executable instructions, and may be implemented as code (e.g., executable instructions, one or more computer programs, or one or more applications) that is executed collectively on one or more processors, by hardware, or a combination thereof. A computer program includes multiple instructions that can be executed by one or more processors.

[0174] Furthermore, the method can be implemented in any type of computing platform that is operably connected to a suitable computer, including but not limited to a personal computer, a minicomputer, a mainframe, a workstation, a network or distributed computing environment, a separate or integrated computer platform, or in communication with a charged particle tool or other imaging device, etc. Various aspects of the present invention can be implemented as machine-readable code stored on a non-transitory storage medium or device, whether removable or integrated into a computing platform, such as a hard disk, an optical read and / or write storage medium, RAM, ROM, etc., so that it can be read by a programmable computer, and when the storage medium or device is read by the computer, it can be used to configure and operate the computer to perform the process described herein. In addition, the machine-readable code, or portions thereof, can be transmitted over a wired or wireless network. When such media includes instructions or programs that implement the above steps in conjunction with a microprocessor or other data processor, the invention of this embodiment includes these and other different types of non-transitory computer-readable storage media. When programmed according to the methods and techniques of the present invention, the present invention also includes the computer itself.

[0175] The computer program can be applied to input data to perform the functions of the present embodiment, thereby converting the input data to generate output data that is stored in a non-volatile memory. The output information can also be applied to one or more output devices such as a display. In a preferred embodiment of the present invention, the converted data represents a physical and tangible object, including a specific visual depiction of the physical and tangible object produced on the display.

[0176] The above are merely preferred embodiments of the present invention. The present invention is not limited to the aforementioned embodiments. As long as the technical effects of the present invention are achieved by the same means, any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention. Within the scope of protection of the present invention, various modifications and variations of the technical solutions and / or implementation methods may be made.

Claims

1. An automatic adjustment system for automobile headlights, characterized in that: The automobile headlight automatic adjustment system comprises: An occupant detection module is used to detect occupant riding status data; A mechanical calculation module, configured to calculate a vehicle body pitch angle based on the passenger riding state data; a fuzzy algorithm control module, configured to perform fuzzy algorithm processing on input variables to obtain a headlight adjustment angle; the input variables are determined based on the vehicle body pitch angle, suspension compression, and slope information; The execution module is used to adjust the angle of the light axis of the vehicle's headlights through the headlight adjustment motor according to the headlight adjustment angle.

2. The automatic headlight adjustment system for automobiles according to claim 1, characterized in that: The detecting of the passenger riding status data includes: Detect the seating status, weight and position distribution of passengers in each seat of the car; The occupant riding state data is composed of the riding state, occupant weight, and position distribution.

3. The automatic headlight adjustment system for automobiles according to claim 2, characterized in that: The calculating the vehicle body pitch angle according to the passenger seating state data includes: Calculating front axle load information and rear axle load information of the vehicle according to the passenger riding state data; Calculating front suspension compression and rear suspension compression according to the front axle load information and the rear axle load information; The vehicle body pitch angle is calculated according to the front suspension compression amount and the rear suspension compression amount.

4. The automatic headlight adjustment system for automobiles according to claim 3, characterized in that: Calculating the front axle load information and the rear axle load information of the vehicle according to the passenger riding state data includes: Setting a weight coefficient for each passenger seat on the vehicle; the weight coefficient represents the proportion of the passenger seat's weight distributed to the front axle; According to the formula Calculate; where ΔW front is the front axle load information, ΔW rear is the rear axle load information, N is the total number of passenger seats on the car, K i is the weight coefficient of the occupant on the i-th seat in the car, m i is the weight data of the occupant in the i-th seat in the car, and g is the acceleration due to gravity.

5. The automatic headlight adjustment system for automobiles according to claim 3, characterized in that: Calculating the front axle load information and the rear axle load information of the vehicle according to the passenger riding state data includes: Get the wheelbase of the car; Obtain the distance between the center of mass of each passenger seat on the vehicle and the front axle; According to the formula Calculate; where ΔW front is the front axle load information, ΔW rear is the rear axle load information, N is the total number of passenger seats on the car, m i is the weight data of the occupant on the i-th seat in the car, g is the acceleration of gravity, L wheelbase is the wheelbase of the car, l_f i is the distance between the center of mass of the occupant in the i-th seat and the front axle of the car.

6. The automatic headlight adjustment system for automobiles according to claim 3, characterized in that: The calculating of the front axle load information and the rear axle load information of the vehicle according to the passenger riding state data includes: Get the wheelbase of the car; Obtain the distance between the center of mass of each passenger seat on the vehicle and the front axle; Get the total weight, longitudinal acceleration and center of mass height of the car including all passengers; According to the formula Calculate; where ΔW front is the front axle load information, ΔW rear is the rear axle load information, N is the total number of passenger seats on the car, m i is the weight data of the occupant on the i-th seat in the car, g is the acceleration of gravity, L wheelbase is the wheelbase of the car, l_f i is the distance between the center of mass of the occupant on the i-th seat and the front axle, W is the total weight, a x is the longitudinal acceleration, h cg is the height of the center of mass.

7. The automatic headlight adjustment system for automobiles according to claim 3, characterized in that: Calculating the front suspension compression amount and the rear suspension compression amount according to the front axle load information and the rear axle load information includes: Obtaining a suspension force-displacement curve; the suspension force-displacement curve represents a corresponding relationship between suspension compression and load; determining the front suspension compression amount according to the front axle load information and the suspension force-displacement curve; The rear suspension compression amount is determined according to the rear axle load information and the suspension force-displacement curve.

8. The automatic headlight adjustment system for automobiles according to claim 3, characterized in that: Calculating the front suspension compression amount and the rear suspension compression amount according to the front axle load information and the rear axle load information includes: Obtain the front suspension stiffness, rear suspension stiffness, front tire stiffness, and rear tire stiffness of the vehicle; According to the formula Calculate; where K eq_front is the equivalent stiffness of the front suspension, K SUS_front (Δh front ) is the front suspension stiffness, Δh front is the front suspension compression, K tire_front is the front tire stiffness, K eq_rear is the equivalent stiffness of the rear suspension, K SUS_rear (Δh rear ) is the rear suspension stiffness, Δh rear is the rear suspension compression, K tire_rear is the rear tire stiffness; Pair equation Solve to determine the front suspension compression Δh front and the rear suspension compression Δh rear .

9. The automatic headlight adjustment system for automobiles according to claim 3, characterized in that: The step of performing fuzzy algorithm processing on the input variables to obtain the headlight adjustment angle includes: Detect the slope information of the car's current location; Acquire multiple fuzzy sets of the vehicle body pitch angle, multiple fuzzy sets of the front suspension compression amount, multiple fuzzy sets of the rear suspension compression amount, and multiple fuzzy sets of the slope information to form the input variables; Establish a fuzzy rule base based on expert experience; Fuzzy reasoning is performed according to the input variables and the fuzzy rule base to obtain the headlight adjustment angle.

10. An automobile, characterized in that: The car includes: The automatic adjustment system for automobile headlights according to any one of claims 1 to 9.

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