Clearance angle determination

Abstract

Examples described herein provide a computer-implemented method that includes calculating, by a processing device, a motor acceleration error based at least in part on a motor torque and a motor speed. The method also includes calculating, by the processing device, a regression fit line based at least in part on the motor acceleration error. The method also includes identifying, by the processing device, a zero point using the regression fit line. The method also includes determining, by the processing device, a difference value by comparing the zero point to a reference datum. The method also includes integrating, by the processing device, the difference value to determine a backlash angle. The method also includes controlling, by the processing device, the motor based at least in part on the backlash angle.

Description

Technical Field

[0001] This invention relates to the detection of the lash angle of a motor. Background Technology

[0002] Modern vehicles (such as cars, motorcycles, boats, or any other type of vehicle) may be equipped with one or more electric motors to drive the vehicle's wheels. For example, an electric motor may be mechanically coupled to the vehicle's wheels to apply rotational force, thus forming a drivetrain. In this example, the connection between the electric motor and the wheels includes gears / splines. Due to manufacturing tolerances, the gears / splines within the drivetrain may have clearance or free play. When changes occur (such as changes in the direction, speed, torque, etc. of the electric motor), the clearance or free play in the gears / splines can cause backlash (or "backlash") in the drivetrain. In particular, backlash is a void or freewheeling in a mechanism caused by the gap between parts (such as two gears). Backlash can lead to poor vehicle ride quality. Summary of the Invention

[0003] In one exemplary embodiment, a computer-implemented method for determining a clearance angle is provided. The method includes calculating a motor acceleration error by a processing device based at least partially on motor torque and motor speed. The method also includes calculating a regression line by the processing device based at least partially on the motor acceleration error. The method further includes identifying a zero point by the processing device using the regression line. The method also includes determining a difference by the processing device comparing the zero point to a reference. The method further includes integrating the difference by the processing device to determine the clearance angle. The method also includes controlling the motor by the processing device based at least partially on the clearance angle.

[0004] In addition to one or more features described herein, or as an alternative, further embodiments of the method may include a motor disposed in the vehicle.

[0005] In addition to one or more features described herein, or alternatively, further embodiments of the method may include calculating the electric motor acceleration error by calculating the electric motor acceleration error "n" times, and calculating the regression fitting line by vectorizing the electric motor acceleration error for the "n" times.

[0006] In addition to one or more features described herein, or as an alternative, further embodiments of the method may include using linear least squares regression to compute a regression fit line.

[0007] In addition to one or more features described herein, or alternatively, further embodiments of the method may include calculating a regression fitted line, including calculating the slope and intercept.

[0008] In addition to one or more features described herein, or as an alternative, further embodiments of the method may include identifying zeros by dividing the inverted value of the intercept by the slope.

[0009] In addition to one or more features described herein, or as an alternative, further embodiments of the method may include controlling the torque of a vehicle motor at least in part based on the clearance angle.

[0010] In another exemplary embodiment, a system includes a memory having computer-readable instructions. The system also includes processing means for executing the computer-readable instructions, which control the processing means to perform operations for determining a motor clearance angle. These operations include calculating a motor acceleration error by the processing means based at least partially on motor torque and motor speed. These operations also include calculating a regression line by the processing means based at least partially on the motor acceleration error. These operations further include identifying a zero point by the processing means using the regression line. The operations also include determining a difference by the processing means comparing the zero point to a reference. The operations further include integrating the difference by the processing means to determine the clearance angle. These operations also include controlling the motor by the processing means based at least partially on the clearance angle.

[0011] In addition to one or more features described herein, or alternatively, further embodiments of the system may include a motor disposed in the vehicle.

[0012] In addition to one or more features described herein, or alternatively, further embodiments of the system may include calculating the electric motor acceleration error by calculating the electric motor acceleration error "n" times, and calculating the regression fitting line by vectorizing the electric motor acceleration error for the "n" times.

[0013] In addition to one or more features described herein, or as an alternative, further embodiments of the system may include using linear least squares regression to compute a regression fit line.

[0014] In addition to one or more features described herein, or alternatively, further embodiments of the system may include calculating a regression fitted line, including calculating the slope and intercept.

[0015] In addition to one or more features described herein, or alternatively, further embodiments of the system may include identifying zeros by dividing the inverted value of the intercept by the slope.

[0016] In addition to one or more features described herein, or as an alternative, further embodiments of the system may include controlling the torque of the vehicle motor at least in part based on the clearance angle.

[0017] In yet another exemplary embodiment, the computer program product includes a computer-readable storage medium having program instructions contained therein, wherein the computer-readable storage medium itself is not a transient signal, the program instructions being executable by a processing device to cause the processing device to perform operations for determining a clearance angle. These operations include calculating a motor acceleration error by the processing device based at least partially on motor torque and motor speed. These operations also include calculating a regression line by the processing device based at least partially on the motor acceleration error. These operations further include identifying a zero point by the processing device using the regression line. The operations also include determining a difference by the processing device comparing the zero point to a reference. The operations further include integrating the difference by the processing device to determine the clearance angle. These operations also include controlling the motor by the processing device based at least partially on the clearance angle.

[0018] In addition to one or more features described herein, or alternatively, further embodiments of the computer program product may include a motor disposed in a vehicle.

[0019] In addition to one or more features described herein, or alternatively, further embodiments of the computer program product may include calculating the electric motor acceleration error by calculating the electric motor acceleration error "n" times, and calculating the regression fitting line by vectorizing the electric motor acceleration error for the "n" times.

[0020] In addition to one or more features described herein, or alternatively, further embodiments of the computer program product may include using linear least squares regression to compute a regression fit line.

[0021] In addition to one or more features described herein, or alternatively, further embodiments of the computer program product may include calculating a regression fitted line, including calculating a slope and an intercept, and identifying zero points, including dividing the inverted value of the intercept by the slope.

[0022] In addition to one or more features described herein, or as an alternative, further embodiments of the computer program product may include controlling the torque of a vehicle motor, at least in part, based on the clearance angle.

[0023] The above-described features and advantages, as well as other features and advantages, of this disclosure will become apparent from the following detailed description when taken in conjunction with the accompanying drawings. Attached Figure Description

[0024] Other features, advantages, and details appear only by way of example in the following detailed description, which refers to the accompanying drawings, wherein:

[0025] Figure 1A vehicle is described, including a processing system for determining clearance angles according to one or more embodiments described herein;

[0026] Figure 2 A flowchart is depicted illustrating a method for determining a clearance angle according to one or more embodiments described herein;

[0027] Figure 3A A block diagram of a system for calculating motor acceleration error according to one or more embodiments described herein is depicted;

[0028] Figure 3B A graph of motor acceleration error over time is depicted according to one or more embodiments described herein;

[0029] Figure 4 A block diagram of a system for calculating a regression fitted line according to one or more embodiments described herein is depicted;

[0030] Figure 5 A block diagram of a system for solving a regression fit line to determine the gap exit time, according to one or more embodiments described herein, is depicted.

[0031] Figure 6 A block diagram of a system for determining a gap angle factor according to one or more embodiments described herein is depicted;

[0032] Figure 7 A flowchart is depicted illustrating a method for determining a clearance angle according to one or more embodiments described herein;

[0033] Figure 8 A graph depicting the gap angle as a function of time according to one or more embodiments described herein;

[0034] Figure 9 A graph depicting the change of clearance angle error over time according to one or more embodiments described herein; and

[0035] Figure 10 A block diagram is depicted of a processing system for implementing the techniques described herein, according to exemplary embodiments. Detailed Implementation

[0036] The following description is exemplary in nature only and is not intended to limit this disclosure, its application, or use. It should be understood that in all the figures, corresponding reference numerals denote the same or corresponding parts and features. As used herein, the term module refers to processing circuitry, which may include application-specific integrated circuits (ASICs), electronic circuitry, processors (shared, dedicated, or grouped) and memories executing one or more software or firmware programs, combinational logic circuitry, and / or other suitable components that provide the described functionality.

[0037] The technical solution described in this article provides a method for determining the clearance angle. Driveline clearance is a result of motor transitions (e.g., changes in direction, speed, torque, etc.) and can lead to poor drive quality in vehicles equipped with that motor. Conventional techniques for reducing the effects of clearance include predicting the clearance angle and programmatically considering it. The clearance angle is the amount of rotation that occurs during transitions when any part of a mechanical system moves without applying force or motion to the next part of the system. In vehicles, the clearance angle changes over time. As a result, reduced drive quality can occur during the vehicle's service life due to incorrect clearance angle estimation and / or changes in the clearance angle over time. Furthermore, gear wear and manufacturing differences affect the clearance transition performance between vehicles. For example, two similar vehicles may have different clearance angles due to gear wear, driving style, manufacturing differences, etc.

[0038] This technique addresses these and other shortcomings of existing technologies by using motor acceleration to algorithmically detect the clearance endpoints of the drivetrain backlash, while avoiding false positives due to noise. Discretely differentiating the motor speed helps to find the actual motor acceleration; however, this calculation is unstable and prevents the use of low values ​​as thresholds to detect clearance exits using motor acceleration errors without generating erroneous triggers. In the example, linear regression is used to detect the end of the drivetrain backlash. This technique also provides the ability to compare the detected clearance endpoints with data and generate closed-loop feedback that can learn the physical clearance angle of the vehicle drivetrain in real time.

[0039] According to one or more embodiments described herein, by utilizing the trend of motor acceleration (see, for example, see...) Figure 3B By applying linear regression to find zero points (e.g., the end of the gap time) without the risk of inaccurate erroneous triggering, basic physics can be used to determine gap exit. After linear regression is triggered by motor acceleration, multiple (e.g., a predetermined number) data points associated with the trigger are saved and used to calculate coefficients of a first-order curve representing the data points associated with the trigger. These coefficients are used to calculate the time value of the gap existence (e.g., the position where the motor acceleration error crosses zero). This value is added to the trigger gap exit detection and integrated over time with each gap transition. The result of the integration is then multiplied by the gap angle estimate to produce a feedback control loop of gap state and gap angle estimate.

[0040] Figure 1 A vehicle 100 is depicted, which includes a processing system 110 for determining clearance angles according to one or more embodiments described herein. Figure 1In the example, vehicle 100 includes a processing system 110 and an electric motor 120 coupled to a drivetrain 122. Vehicle 100 may be a car, truck, van, bus, motorcycle, boat, airplane, or other suitable means of transport.

[0041] The processing system 110 includes a motor speed / torque engine 112, a clearance angle determination engine 114, and a control engine 116. Although not shown, the processing system 110 may include other components, engines, modules, etc., such as processors (e.g., central processing units, graphics processing units, microprocessors, etc.), memory (e.g., random access memory, read-only memory, etc.), data storage (e.g., solid-state drives, hard disk drives, etc.).

[0042] According to one or more embodiments described herein, regarding Figure 1 The various components, modules, engines, etc., described in the processing system 110 can be implemented as instructions stored on a computer-readable storage medium, hardware modules, special-purpose hardware (e.g., special-purpose hardware, application-specific integrated circuits (ASICs), special-purpose processors (ASSPs), field-programmable gate arrays (FPGAs), embedded controllers, hardwired circuits, etc.), or as one or more combinations thereof. According to aspects of this disclosure, the engine described herein can be a combination of hardware and programming. The program can be processor-executable instructions stored in tangible memory, and the hardware can include processing means (e.g., processing devices for executing these instructions) for executing these instructions. Figure 10 The processor 1021). Therefore, the system memory (e.g. Figure 10 The RAM 1024 can store program instructions that, when executed by the processing device, implement the engine described herein. Other engines can also be used to include other features and functions described in other examples herein. The features and functions of the engine of the processing system 110 are further described herein.

[0043] The processing system 110 of the vehicle 100, which uses the motor speed / torque engine 112, monitors various aspects of the motor 120, including, for example, motor speed and torque. Using the information about the motor 120, the processing system 110 performs clearance angle determination of the transmission 122 of the vehicle 100 by using the clearance angle determination engine 114. Furthermore, the processing system 110 can control the motor 120 using the control engine 116 to reduce the adverse effects of clearance.

[0044] According to one or more embodiments described herein, the clearance angle determination engine 114 calculates motor acceleration using the motor speed and commanded motor torque received from the motor speed / torque engine 112, divided by the derivative of the motor's inertia. The clearance angle determination engine 114 then takes the difference between the two, and when the difference is far from zero, it indicates the end of the drivetrain-clearance transition. When the difference exceeds a calibration threshold, linear regression can be performed on recorded data points before and after the threshold to determine when the motor acceleration difference exceeds zero. For example, a regression technique is used to determine the zero point, which is then recorded and compared with a reference to the clearance exit point. This difference is then integrated and multiplied by a reference clearance angle estimate to form a feedback loop to learn the true physical clearance angle. The process is further described with reference to the following figures.

[0045] Specifically, Figure 2 A flowchart illustrating a method 200 for determining a clearance angle according to one or more embodiments described herein is provided. Method 200 can be performed by any suitable system or device, such as… Figure 1 Processing system 110 Figure 10 The processing system 1000 or any other suitable processing system and / or processing device (e.g., processor).

[0046] In box 202, the clearance angle is determined by engine 114 based at least in part on motor acceleration error calculated using motor speed and motor torque. Motor speed / torque engine 112 receives motor speed and motor torque directly or indirectly from motor 120 (e.g., from a device associated with motor 120, not shown). Motor speed indicates how fast the motor is rotating, and motor torque indicates how much torque the motor is applying. Now described... Figure 3A This diagram depicts a block diagram of a system 300 for calculating motor acceleration error according to one or more embodiments described herein. As shown, a motor torque command 302 and a motor speed 304 (e.g., from a motor speed / torque engine 112 monitoring motor 120) are received and fed into an inertia block 306 and a discrete increment block 308, respectively. The inertia block 306 determines the commanded acceleration based solely on the motor inertia, as the reciprocal of the motor inertia. The output of the inertia block 306 is aligned at blocks 310a, 310b, and this output is input into an error calculation block 312. The discrete increment block 308 uses the indicated motor speed to determine the calculated acceleration as the time derivative of the motor speed, and the output of the discrete increment block 308 is also input into the error calculation block 312. The error calculation block 312 determines a motor acceleration error (or difference) 314. For example, since inertia is only used for motor 120, motor 120 experiences a gap when the acceleration error (or difference) is close to zero.

[0047] Figure 3BA graph 320 depicts the positive gap transition according to one or more embodiments described herein, plotted as a motor acceleration error 322 varying over time 324. In graph 320, a gap region 326 is shown. These data points represent the motor acceleration error 322 at which the gap occurs. When the motor acceleration error 322 crosses a threshold 328 (e.g., at point 330), a trigger is established. Figure 2 Method 200. That is, the trigger gap adaptation technique. Points 332 before and after point 330 (e.g., the trigger point) are used to fit a linear regression curve / line (see, for example, see...). Figure 4 ).

[0048] Back Figure 2 The discussion in box 204 states that the clearance angle of engine 114 is determined at least in part based on the regression fitting line calculated from the motor acceleration error calculated in box 202. Now, the description... Figure 4 This diagram depicts a block diagram of a system 400 for calculating a regression fit line according to one or more embodiments described herein. System 400 receives a motor acceleration error (or difference) 314, which is input into a delay box 402. Delay box 402 vectorizes the last “n” (e.g., 5, 3, 7, 4, 11, etc.) data points of the motor acceleration error and inputs the vectorized values ​​into a regression calculation box 404 (also known as “linear least squares (LLS)”). Regression calculation box 404 performs regression analysis (e.g., linear least squares regression) to approximate regression coefficients (e.g., slope 406 and intercept 408), which together define the regression fit line. Regression calculation box 404 may also utilize a time value 410 (i.e., single([-1:3]) and an EnblLog value 412. According to one or more embodiments described herein, regression calculation box 404 may be an embedded controller (e.g., a digital signal processor, microprocessor, field-programmable gate array, etc.). It should be understood that by using… Figure 4 The regression-based method reduces and / or eliminates false triggering caused by motor noise because regression is used to generate the gap angle.

[0049] Back Figure 2 The discussion in box 206, where the gap angle determination engine 114 uses the regression fitted line calculated in box 204 to identify the zero point. Now described. Figure 5This diagram depicts a block diagram of a system 500 for solving a regression fitted line to determine a gap exit time, according to one or more embodiments described herein. System 500 takes a slope 406 and an intercept 408 as inputs. The intercept 408 is inverted at block 502, and at block 504, the inverted values ​​of the intercept 408 and the slope 406 are used to solve for the gap exit time 506 (i.e., the time when the gap ends). For example, using the equation y = mx + b, where m is the slope 406 and b is the intercept 408, this equation can be solved to find the gap exit time 506 (e.g., for y = 0, x = -b / m). That is, block 504 divides the inverted value of the intercept 408 (e.g., "-b") by the slope 406 (e.g., "m") to determine the gap exit time 506.

[0050] Back Figure 2 In the discussion at box 208, the gap angle determination engine 114 compares the zero point identified at box 206 with a reference to determine the difference. The reference is the point at which the estimated gap angle has reached its threshold to indicate the end of the gap. This can be determined using a conventional gap exit algorithm. The comparison between the zero point identified at box 206 and the reference is done by observing the number of time steps the zero point (identified at box 206) takes before or after the reference, and an identification error is generated in the system, which is then used to adjust the angle estimation.

[0051] In box 210, the clearance angle determining engine 114 integrates this difference to determine the clearance angle (e.g., clearance angle factor). Now described Figure 6 This describes a block diagram of a system 600 for determining a gap angle factor 602 according to one or more embodiments described herein. System 600 uses an integrator 604 to continuously sum motor acceleration errors and generate an adaptive factor (e.g., gap angle factor 602) for generating a feedback loop. Integrator 604 can take one or more of the following as inputs: a maximum gap angle factor 606, a minimum gap angle factor 608, an angle step error value 610, an adaptive integer gain value 612, an enable value 614, a Boolean value 616, and single values ​​618, 620. Integrator 604 provides an accumulation of error, where 0 = no error. This error is output as a gap angle error 622 and can be inverted at block 624. This causes method 200 to terminate from the integral gap angle loop used for gap estimation. Accumulator 626 adds a unit (1) to the gap angle error 622 to convert it into a multiplier. For example, gap angle factor 602 is equal to gap angle calibration value 628 multiplied by gap angle error 622.

[0052] Back Figure 2In the discussion at box 212, the clearance angle determines that the motor 120 of the vehicle 100 is controlled at least in part based on the clearance angle of the engine 114. For example, using the clearance angle (e.g., clearance angle factor 622), the torque of the motor 120 can be controlled. By controlling the torque of the motor 120 based on the clearance angle, both the motor 120 and the vehicle 100 are improved. For example, as the clearance angle changes, such as due to gear wear, the driving / riding quality of the vehicle 100 can improve over time. Similarly, since regression is used to generate the clearance angle, false triggering caused by motor noise is reduced.

[0053] Additional processes may also be included, and it should be understood that... Figure 2 The processes described herein are illustrative, and other processes may be added or existing processes may be removed, modified or rearranged without departing from the scope and spirit of this disclosure.

[0054] Figure 7 A flowchart illustrating a method 700 for determining a clearance angle according to one or more embodiments described herein is provided. Method 700 can be performed by any suitable system or device, such as… Figure 1 Processing system 110 Figure 10 The processing system 1000 or any other suitable processing system and / or processing device (e.g., processor).

[0055] In block 702, the gap transition occurs. Block 704 illustrates a standard gap exit algorithm, where the gap angle is calculated using the closer speed of the drivetrain (block 706), and the exit gap is determined when the gap angle reaches a calibration threshold (block 708). Subsequently, in block 710, motor 120 is controlled based on the gap angle. This method is prone to false triggering due to motor noise in motor 120, thus leading to inaccurate learning because, unlike one or more embodiments described herein, no regression method is used.

[0056] Specifically, one or more embodiments described herein utilize flow paths shown at least in blocks 712 and 714, which respectively detect gap exit and adjust the gap angle. Within block 712, as described herein, motor acceleration error is calculated in block 716, regression coefficients are calculated in block 718, and a regression fit line for the zero-crossing motor acceleration error is solved in block 720. Within block 714, the time step difference between 1) the solved exit point (from block 720) and 2) the baseline exit point (the point at which the estimated gap angle has reached its threshold to indicate the end of the gap) is calculated in block 722. In block 724, the difference from block 722 is integrated to produce a gap adaptation factor as described herein. In block 726, the gap angle is adjusted by multiplying the existing angle calibration threshold by the gap adaptation factor. This is shown in more detail in block 728, where the clearance angle coefficient is fed into zero-protection overdrive block 730 and multiplied in block 732 by the output of array index block 734 (used to select a clearance angle estimate specific to the drivetrain arrangement used) to produce a positive clearance threshold 756 and a negative clearance threshold 738. According to one example, the clearance angle input is an array of values, each representing the clearance angle for a specific drivetrain arrangement. Array index block 734 is used to select a specific clearance angle threshold for the drivetrain equation. In block 740, the clearance angle is now in the feedback loop of method 200 (i.e., the adaptive algorithm) and can be used to control the motor. Specifically, in block 742, motor 120 is controlled by controlling the torque based on the clearance angle from block 714.

[0057] Additional processes may also be included, and it should be understood that... Figure 7 The processes described herein are illustrative, and other processes may be added or existing processes may be removed, modified or rearranged without departing from the scope and spirit of this disclosure.

[0058] Figure 8A graph 800 depicts the gap angle 802 versus time 804 according to one or more embodiments described herein. Line 806 represents a device threshold with a slope of 0.25, and line 808 represents an adapted threshold. Graph 800 was generated for a 500-second run, showing a device angle that first increases and then becomes constant (see line 806). In this example, based on a torque input of 10000 Nm ± 0% of a random value between -2000 and 4000, the initial gap angle error is 0%, and the torque rate is 200 Nm / s. In graph 800, there is a time step delay for a detected exit, the device angle increases linearly to 125% of its original value, and the adapted estimate tracks the device angle. In particular, graph 800 shows how method 200 learns the device gap angle over time. During the first portion of the run (e.g., less than approximately 250 seconds), the true gap angle increases, and the estimated value is learning to change over time, as shown by line 806. During the second part (e.g., more than about 250 seconds), the true gap angle flattens out, and this is also known in the estimation, as shown in line 806.

[0059] Figure 9 A graph 900 depicts the gap angle error 902 as a function of time 904 according to one or more embodiments described herein. Graph 900 shows three sets of data with different initial and final estimated percentage errors, such as line 906 (e.g., estimated threshold angle of 0.85), line 908 (e.g., estimated threshold angle of 1.00), and line 910 (e.g., estimated threshold angle of 1.15). As shown, for each of these cases, the estimate self-corrects over time and is able to learn the true angle, as indicated by the convergence of lines 906, 908, and 910.

[0060] It should be understood that one or more embodiments described herein can be implemented in conjunction with any other type of computing environment now known or developed in the future. For example, Figure 10 A block diagram of a processing system 1000 for implementing the techniques described herein is depicted. In the example, the processing system 1000 has one or more central processing units (“processors” or “processing resources”) 1021a, 1021b, 1021c, etc. (collectively or collectively referred to as processors 1021 and / or processing devices). In aspects of this disclosure, each processor 1021 may include a Reduced Instruction Set Computer (RISC) microprocessor. The processor 1021 is coupled to system memory (e.g., random access memory (RAM) 1024) and various other components via a system bus 1033. Read-only memory (ROM) 1022 is coupled to the system bus 1033 and may include a basic input / output system (BIOS) that controls certain basic functions of the processing system 1000.

[0061] Input / output (I / O) adapter 1027 and network adapter 1026 coupled to system bus 1033 are also depicted. I / O adapter 1027 may be a Small Computer System Interface (SCSI) adapter that communicates with hard disk 1023 and / or storage device 1025 or any other similar component. I / O adapter 1027, hard disk 1023, and storage device 1025 are collectively referred to herein as mass storage 1034. Operating system 1040 for execution on processing system 1000 may be stored in mass storage 1034. Network adapter 1026 interconnects system bus 1033 with external network 1036, enabling processing system 1000 to communicate with other such systems.

[0062] A display (e.g., a display monitor) 1035 is connected to the system bus 1033 via a display adapter 1032, which may include a graphics adapter to improve performance for graphics-intensive applications and a video controller. In one aspect of this disclosure, adapters 1026, 1027, and / or 1032 may be connected to one or more I / O buses, which are connected to the system bus 1033 via an intermediate bus bridge (not shown). Suitable I / O buses for connecting peripheral devices such as hard disk controllers, network adapters, and graphics adapters typically include common protocols such as Peripheral Component Interconnect (PCI). Additional input / output devices are shown connected to the system bus 1033 via a user interface adapter 1028 and a display adapter 1032. A keyboard 429, a mouse 430, and a speaker 431 (or other suitable input and / or output, such as a touchscreen in an infotainment system) may be interconnected to the system bus 433 via a user interface adapter 428, which may include, for example, a super I / O chip integrating multiple device adapters into a single integrated circuit.

[0063] In some aspects of this disclosure, the processing system 1000 includes a graphics processing unit 1037. The graphics processing unit 1037 is a specialized electronic circuit designed to manipulate and modify memory to accelerate the creation of images in a frame buffer, which are intended for output to a display. Generally, the graphics processing unit 1037 is highly efficient in manipulating computer graphics and image processing, and has a highly parallel architecture, making it more efficient than a general-purpose CPU for algorithms that process large blocks of data in parallel.

[0064] Therefore, as configured herein, the processing system 1000 includes processing power in the form of a processor 1021, storage capacity including system memory (e.g., RAM 1024) and mass storage 1034, input devices such as a keyboard 1029 and a mouse 1030, and output capacity including a speaker 1031 and a display 1035. In some aspects of this disclosure, a portion of the system memory (e.g., RAM 1024) and the mass storage 1034 jointly store an operating system 1040 to coordinate the functions of the various components shown in the processing system 1000.

[0065] For illustrative purposes, various examples of this disclosure have been described, but these descriptions are not intended to be exhaustive or limiting to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described technology. The terminology used herein has been chosen to best explain the principles of the technology, its practical application, or technical improvements to technologies found in the market, or to enable others skilled in the art to understand the technology disclosed herein.

[0066] While the foregoing disclosure has been described with reference to exemplary embodiments, those skilled in the art will understand that various changes can be made and equivalents can replace its elements without departing from its scope. Furthermore, many modifications can be made to adapt particular situations or materials to the teachings of this disclosure without departing from the essential scope of this disclosure. Therefore, it is intended that the technology be limited to the specific embodiments disclosed, but will include all embodiments falling within the scope of this application.

Claims

1. A computer-implemented method for determining a motor clearance angle, the method comprising: The motor acceleration error is calculated by the processing device based at least in part on the motor torque and motor speed; The regression fitting line is calculated by the processing device based at least in part on the motor acceleration error; The zero point is identified by the processing device using the regression fitting line; The processing unit compares the zero point with a reference to determine the difference. The gap angle is determined by integrating the difference using a processing device. as well as The motor is controlled by the processing device based at least in part on the clearance angle.

2. The computer-implemented method according to claim 1, wherein, The motor is installed in the vehicle.

3. The computer-implemented method according to claim 1, wherein, Calculating the motor acceleration error includes calculating the motor acceleration error "n" times, and wherein calculating the regression fitting line includes vectorizing the motor acceleration error for the "n"th time.

4. The computer-implemented method according to claim 1, wherein, Linear least squares regression is used to calculate the regression fit line.

5. The computer-implemented method according to claim 1, wherein, Calculating the regression fit line includes calculating the slope and intercept.

6. The computer-implemented method according to claim 5, wherein, Identifying the zero point involves dividing the inverted value of the intercept by the slope.

7. The computer-implemented method according to claim 1, wherein, Controlling the motor based at least in part on the clearance angle includes controlling the motor torque based at least in part on the clearance angle.

8. A system comprising: Memory including computer-readable instructions; as well as A processing device for executing computer-readable instructions, the computer-readable instructions controlling the processing device to perform operations for determining a motor clearance angle, said operations including: The motor acceleration error is calculated by the processing device based at least in part on the motor torque and motor speed; The regression fitting line is calculated by the processing device based at least in part on the motor acceleration error; The zero point is identified by the processing device using the regression fitting line; The processing unit compares the zero point with a reference to determine the difference. The gap angle is determined by integrating the difference using a processing device; and The motor is controlled by the processing device based at least in part on the clearance angle.

9. The system according to claim 8, wherein, The motor is installed in the vehicle.

10. The system according to claim 8, wherein, Calculating the motor acceleration error includes calculating the motor acceleration error "n" times, and wherein calculating the regression fitting line includes vectorizing the motor acceleration error for the "n"th time.

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