A motor control method for a directional rotary steering tool

Abstract

The present application discloses a motor control method for a pointing rotary steering tool, which relates to the technical field of drilling operation control systems, including: establishing a mathematical model of the motor; establishing a simulation model based on the mathematical model; initializing motor control parameters; iterating the motor control parameters, and inputting the iterated motor control parameters into the simulation model after each iteration to determine whether the motor control parameters meet the requirements; and controlling the motor of the pointing rotary steering tool using the final motor control parameters. The present application uses genetic algorithms and Simulink simulation to simulate the motor control parameters for different motor parameters and inertias in advance, providing motor control parameter selection under various working conditions for actual engineering applications, and avoiding the problems of the original motor control parameters causing the control system to have reduced control accuracy, reduced stability, insufficient robustness, and increased energy consumption when the motor's rotational inertia changes due to high temperature or changes in the formation.

Description

Technical Field

[0001] The present application relates to the technical field of drilling operation control systems, and in particular to a motor control method for a directional rotary steering tool. Background Art

[0002] Due to the scarcity and difficulty of domestic oil and gas resources, China's crude oil imports have increased annually, and its dependence on foreign crude oil has reached over 70% in recent years. Conventional oil and gas production can no longer meet this growing energy demand. To ensure energy security and address some of the challenges and demands of traditional drilling technology, directional rotary steerable tools have emerged.

[0003] A directional rotary steerable tool (RSS) is a crucial piece of equipment in oil well drilling, used to control the direction and trajectory of the drill bit. Control system performance is crucial for RSS. Well-designed control systems and the application of excellent control strategies can provide more precise control of drill bit attitude and wellbore trajectory. Optimizing motor control parameters is crucial to the overall system's control performance. For precise trajectory control, adjusting motor control parameters directly affects the drilling tool's rotational speed and direction, thereby impacting the accuracy and stability of the wellbore trajectory. Regarding dynamic responsiveness, the system must rapidly respond to changes in formations and rock types to ensure tool stability in complex formations. Appropriate motor control parameters can enhance the system's dynamic responsiveness, enabling it to more flexibly adapt to diverse geological environments. Regarding energy consumption, efficient motor control parameter settings help optimize energy consumption and reduce drilling system operating costs. By adjusting motor control parameters in different field applications of rotary steerable tools, it is possible to optimize performance while reducing energy consumption.

[0004] However, existing directional rotary steerable tools have the following two problems:

[0005] 1. As the well depth increases and the motor's service life prolongs, the heat generated by the motor and the ambient temperature continue to rise, causing the local and internal temperature of the motor to continue to rise over time. High temperature will cause the electrical parameters of the motor to change. Unchanged motor control parameters are difficult to match the control system with changing motor parameters. Therefore, the accuracy of the control system is easily affected by changes in motor parameters.

[0006] 2. When facing complex and changing geological environments, drill bits of different models and sizes are required. Replacing the drill bit will cause the motor's moment of inertia to change, thereby affecting the optimal matching of the control system's control parameters. Summary of the Invention

[0007] An embodiment of the present application provides a motor control method for a directional rotary steering tool, which is used to solve the problem in the prior art that the control system is affected by temperature increase and drill bit replacement.

[0008] In one aspect, an embodiment of the present application provides a motor control method for a pointing rotary steerable tool, comprising:

[0009] Establish a mathematical model of the motor;

[0010] Establish the FOC (field oriented control) three-loop control simulation model of the motor based on the mathematical model;

[0011] Initialize motor control parameters according to temperature and drill bit conditions;

[0012] Iterate the control parameters using a genetic algorithm, input the iterated motor control parameters into a FOC three-closed-loop control simulation model after each iteration, determine whether the iterated motor control parameters meet the requirements based on the output of the FOC three-closed-loop control simulation model, output the final motor control parameters if they meet the requirements, and continue iterating if they do not meet the requirements until the iterated motor control parameters meet the requirements or the iteration ends;

[0013] The final motor control parameters are used to control the motor of the pointing rotary steerable tool.

[0014] The motor control method of a directional rotary steering tool in this application has the following advantages:

[0015] 1. Applying genetic algorithms and Simulink simulation, we simulate in advance the motor control parameters under different working conditions, that is, different motor parameters and inertia. This provides motor control parameter selection under various working conditions for actual engineering applications. This avoids problems such as reduced control accuracy, stability, insufficient robustness, and increased energy consumption caused by changes in motor parameters under high temperature conditions or changes in the motor's moment of inertia due to changes in the stratum.

[0016] 2. The genetic algorithm is directly combined with the Simulink simulation model for parameter optimization, which avoids the difficulty in obtaining the transfer function of most vector control systems containing space vector pulse width modulation (SVPWM) in practical applications, making it impossible to use classical control theory to establish a reasonable model. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0018] Figure 1 A flowchart of a motor control method for a pointing rotary steerable tool provided in an embodiment of the present application;

[0019] Figure 2 Schematic diagram of the FOC three-closed-loop control simulation model provided in an embodiment of the present application. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0021] Figure 1 This is a flow chart of a motor control method for a directional rotary steerable tool provided in an embodiment of the present application. This embodiment of the present application provides a motor control method for a directional rotary steerable tool, comprising:

[0022] S100, establishing a mathematical model of the motor.

[0023] Exemplarily, S100 specifically includes: S101, establishing a motor model in a three-phase stationary coordinate system; S102, performing Clark transformation on the motor model in the three-phase stationary coordinate system to obtain a motor model in a two-phase stationary coordinate system; S103, performing Park transformation on the motor model in the two-phase stationary coordinate system to obtain a motor model in a rotating coordinate system, that is, a mathematical model.

[0024] In S101, the motor model includes the voltage vector equation, the flux equation, and the electromagnetic torque equation. The voltage vector equation of the motor in the three-phase stationary coordinate system is as follows:

[0025]

[0026] Among them, u a ,u b ,u c is the three-phase stator voltage, i a ,i b ,i c is the three-phase stator current, ψa , ψ b , ψ c is the stator flux, and R is the stator phase resistance.

[0027] The magnetic flux equation is expressed as:

[0028]

[0029] Among them, L aa , L bb , L cc is the stator winding self-inductance, M ab , M bc , M ca is the mutual inductance of the stator winding, ψ f is the permanent magnet flux value, θ e is the rotor position.

[0030] The electromagnetic torque equation is:

[0031]

[0032] Where p n is the number of pole pairs of the permanent magnet synchronous motor, θ m is the mechanical angle.

[0033] In S102, the PMSM (permanent magnet synchronous motor) is a typical complex system with multiple inputs and multiple outputs. Designing a motor control system based on this is difficult, significantly increasing the computational resources required for the control algorithm. Therefore, it is necessary to find an appropriate coordinate transformation method to reduce the order of the PMSM. The motor model of the PMSM in a three-phase stationary coordinate system is transformed into a two-phase stationary coordinate system through Clark transformation. The transformed voltage vector equation is:

[0034]

[0035] The back EMF equation is:

[0036]

[0037] Where, ω e is the electrical angular velocity, u α 、u β ,i α 、i β , e α 、e β are the components of voltage, current and back EMF on the α-β axis respectively.

[0038] The electromagnetic torque equation can be expressed as:

[0039]

[0040] The magnetic flux equation can be expressed as:

[0041]

[0042] Where, ψ α , ψ β is the axial component of the magnetic flux in the α-β coordinate system.

[0043] In S103, the motor model in the two-phase stationary coordinate system is transformed by Park to obtain the motor model in the dq coordinate system. The voltage vector equation after the transformation is expressed as:

[0044]

[0045] The magnetic flux equation is:

[0046]

[0047] The stator voltage equation is:

[0048]

[0049] Among them, u d 、u q are the d and q axis voltages, i d 、i q are the d-axis and q-axis currents, ψ d , ψ q are the total magnetic flux of d and q axes respectively, L d 、L q are the d-axis and q-axis inductances respectively.

[0050] The electromagnetic torque equation is:

[0051]

[0052] The equilibrium equation of motion is:

[0053]

[0054] Where J is the moment of inertia, w m is the mechanical angular velocity, T L is the load torque, and B is the damping coefficient.

[0055] Adopt i d =0 in vector control, the stator voltage equation can be simplified to:

[0056]

[0057] The electromagnetic torque equation is:

[0058]

[0059] From the above equations, it can be seen that by controlling i q The torque can be controlled, and the d-axis voltage is only related to the i q This is beneficial to the control of the motor.

[0060] S110, establishing a FOC three-closed-loop control simulation model of the motor based on the mathematical model.

[0061] For example, Figure 2 As shown in S110, the current loop of the FOC three-loop control simulation model is the innermost loop, the speed loop is the middle loop, and the position loop is the outermost loop; in the current loop, the three-phase current i a 、i b 、i c After Clark transformation and Park transformation, the q-axis current i is obtained. q and the d-axis current i d , respectively calculate the difference between the q-axis current Iq and the d-axis current Id and the corresponding set values ​​Iq_Ref and Id_Ref, substitute the q-axis current error value into the q-axis current PI controller to calculate the q-axis voltage u q , substitute the d-axis current error value into the d-axis current PI (proportional integral) controller to calculate the d-axis voltage u d Then, the q-axis voltage Vq and the d-axis voltage Vd are subjected to inverse Park transformation to obtain the α-axis voltage u α and β-axis voltage u β , the α-axis voltage Vα and β-axis voltage Vβ are calculated using the SVPWM algorithm to obtain the three-phase voltage u a 、u b and u c Finally, the three-phase voltages Va, Vb, and Vc are input into the mathematical model of the motor. In the speed loop, the input of the speed loop is the difference between the actual speed of the motor and the speed setting value Speed_Ref. The difference is calculated by the speed PI controller and used as the input of the current loop. In the position loop, the difference between the current position of the motor and the position setting value Position_Ref is calculated, and the difference is substituted into the position PI controller, and the output result is used as the speed setting value Speed_Ref.

[0062] exist Figure 2 In FIG, PMSM represents a motor model of a permanent magnet synchronous motor. In the FOC three-closed-loop control simulation model, the mathematical model established in step S100 can be used to complete the simulation of the motor control process.

[0063] S120, initializing motor control parameters according to the temperature and the condition of the drill bit.

[0064] For example, the motor control parameters mentioned in this application are Figure 2 The proportional and integral terms of the PI controllers in the current, velocity, and position loops are three in total. Since there are three loops, there are three proportional and three integral terms, for a total of six motor control parameters. When initializing the motor control parameters, we first determine the temperature and drill data. Then, we determine the corresponding motor parameters based on these data. Finally, we determine the initialized motor control parameters based on the motor parameters.

[0065] Specifically, before initializing the motor control parameters, the factors that affect the motor control parameters must be clearly identified. For permanent magnet synchronous motors used in directional rotary steerable tools, as the well depth increases and the motor is used for a longer time, the heat generated by the motor and the ambient temperature continue to rise. High temperature will cause changes in the motor's electrical parameters. When the operating temperature of the coil (also known as the motor winding) changes, the stator resistance of the motor coil (i.e., R s ) can vary significantly. Copper is a common material used to make windings. The following formula approximates the linear relationship between resistance and temperature:

[0066] R=R0[1+α(T-T0)]

[0067] Where R is the resistance at temperature T in Ω, R0 is the resistance at temperature T0 in Ω, and α is the temperature coefficient of the material in degrees Celsius (°C). -1 ) as the unit, T is the final temperature of the material in degrees Celsius (℃), and T0 is the reference temperature of the material in degrees Celsius (℃).

[0068] For example, the stator resistance R s At 20℃, it is 10Ω. Its winding material is copper and its temperature coefficient is 0.00393℃. -1 If the motor temperature rises to 150°C, the new stator resistance is:

[0069] R=10Ω[1+0.00393℃ -1 (150℃-20℃)]=15.109Ω

[0070] As can be seen from the above formula, as the temperature rises, the resistance changes significantly, increasing by about 52%.

[0071] Similarly, high temperatures can cause changes in the magnetic properties of permanent magnet materials. Permanent magnet synchronous motors typically use permanent magnets as the magnetic material for the rotor. At high temperatures, the magnetic properties of permanent magnet materials may weaken, causing changes in the magnetic permeability of the dq-axis magnetic flux link, thereby affecting the dq-axis inductance value. In addition, changes in the stator resistance at high temperatures also affect the dq-axis inductance value. The relationship between the inductance of the motor's dq axes and temperature is nonlinear, but as the temperature gradually increases, the motor's dq-axis inductance will also increase. Regarding the rotor permanent magnet flux, high temperatures will cause the residual magnetic field strength of the permanent magnet to weaken, resulting in a gradual decrease in the main magnetic flux of the motor, that is, the motor's flux linkage gradually decreases.

[0072] When faced with complex and changing geological environments, rotary steerable tools require replacement drill bits, such as roller cone bits, PDC (polycrystalline diamond compact) diamond bits, or eccentric bits. These bits vary in size and quality, causing the mass rotating with the motor rotor to change, leading to changes in the motor's moment of inertia. As can be seen from the following formula for the initial values ​​of the motor control parameters, both of these factors affect the value of the motor's control parameter, PI.

[0073] After determining the factors that affect the motor control parameters, the initial values ​​of the PI values ​​of the motor control parameters can be determined based on these factors. p The initial value is generally set to a smaller value, usually 1, K i Generally K p One tenth of the integral gain is optimized by experimenting and observing the response of the system. The integral gain can be set to 0.1 during the initial debugging. Parameter debugging and optimization are carried out in combination with the specific system characteristics and control requirements to obtain the best initial value setting. The proportional terms K of the speed loop and current loop are p and the integral term K i The initial value calculation process is as follows:

[0074]

[0075]

[0076]

[0077] Where Bandwidth is the bandwidth of the current loop control system; T is the current loop control period.

[0078]

[0079]

[0080] Where β is the desired bandwidth of the speed loop, and are the proportional term and integral term of the current loop respectively, and They are the proportional term and integral term of the speed loop respectively.

[0081] S130, using a genetic algorithm to iterate the control parameters, inputting the iterated motor control parameters into the FOC three-closed-loop control simulation model after each iteration, and determining whether the iterated motor control parameters meet the requirements based on the output of the FOC three-closed-loop control simulation model. If they meet the requirements, output the final motor control parameters; if they do not meet the requirements, continue iterating until the iterated motor control parameters meet the requirements or the iteration ends.

[0082] For example, when using a genetic algorithm to iterate the control parameters, the initialized motor control parameters are first genetically encoded, and then the performance of each genetic encoding is evaluated using a fitness function. A portion of individuals (i.e., genetic encoding) is selected as parents based on the fitness value of the genetic encoding, and a crossover operation is performed on the parents to generate new individuals. The generated new individuals are then mutated, and the performance of the newly generated individuals is evaluated using a fitness function. The newly generated individuals replace a portion of individuals with lower fitness in the current population (i.e., the set of genetic encodings) to complete one iteration.

[0083] After each iteration, the resulting motor control parameters are applied to the FOC three-loop closed-loop control simulation model to simulate the PMSM. After the simulation, the PMSM's system error, controller output, and rise time are input into the objective function to obtain the corresponding function value. This function value is then used to determine whether the iterated motor control parameters meet the requirements, until the required motor control parameters are found or the iteration ends.

[0084] The objective function includes system error, controller output, rise time, and their corresponding weights. When designing the objective function, the three major control performances of the system are rapidity (rise time and adjustment time), stability (maximum speed fluctuation and overshoot), and accuracy (steady-state error and deviation, and the control amount should not be too large). The specific function form is:

[0085]

[0086] Where e(t) is the system error, u(t) is the controller output, t u is the rise time, w1, w2, and w3 are e(t), u(t), and t u The corresponding weight.

[0087] In order to avoid overshoot, a penalty function is used. That is, once overshoot occurs, the overshoot is used as the optimal indicator. At this time, the objective function is expressed as:

[0088]

[0089] Where ey(t) = y(t) - y(t-1), y(t) is the output of the controlled object, w4 is the weight, and w4>>max(w1,w2,w3).

[0090] Furthermore, when establishing the objective function, the system error, controller output and rise time are first standardized to obtain standardized data, and then the corresponding information entropy is calculated based on the standardized data. Finally, the corresponding weights of the system error, controller output and rise time are determined based on the information entropy.

[0091] Specifically, due to the contradictions between various performance indicators and the different dimensions and magnitudes, the entropy weight method is used to rationally allocate them. The entropy weight method calculation mainly involves the following three steps:

[0092] Process 1: Standardize the data.

[0093]

[0094] In the formula, i is the sequence of data, j is the number of indicators. i_max 、x i_min are the maximum and minimum values ​​under the j index respectively.

[0095] Process 2: Calculate the information entropy of each data.

[0096]

[0097] p ij is the proportion of single data under indicator j.

[0098]

[0099] Process 3: Determine the weight of each data.

[0100]

[0101] S140: Control the motor of the pointing rotary steering tool using the final motor control parameters.

[0102] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present application.

[0103] Obviously, those skilled in the art may make various changes and modifications to this application without departing from the spirit and scope of this application. Thus, if these modifications and variations of this application fall within the scope of the claims of this application and their equivalents, this application is intended to include these modifications and variations.

Claims

1. A motor control method for a directional rotary steering tool, characterized in that: include: Establish a mathematical model of the motor; Establishing a FOC three-closed-loop control simulation model of the motor based on the mathematical model; Initialize motor control parameters based on temperature and drill bit size data; Iterating the motor control parameters using a genetic algorithm, inputting the iterated motor control parameters into the FOC three-closed-loop control simulation model after each iteration, determining whether the iterated motor control parameters meet requirements based on outputs of the FOC three-closed-loop control simulation model, outputting final motor control parameters if they meet requirements, and continuing iteration if they do not meet requirements until the iterated motor control parameters meet requirements or the iteration ends; Controlling a motor of a pointing rotary steering tool using the final motor control parameters; Wherein, the mathematical model of the motor is established, including: Establish a motor model in a three-phase stationary coordinate system; Perform Clark transformation on the motor model in the three-phase stationary coordinate system to obtain the motor model in the two-phase stationary coordinate system; Performing Park transformation on the motor model in the two-phase stationary coordinate system to obtain the motor model in the rotating coordinate system, i.e., the mathematical model; In the FOC three-closed-loop control simulation model, the current loop is the innermost loop, the speed loop is the middle loop, and the position loop is the outermost loop; in the current loop, the three-phase current i a 、 i b and i c After Clark transformation and Park transformation, the q-axis current is obtained i q and d-axis current i d , respectively, the q-axis current i q and d-axis current i d Calculate the difference with the corresponding set values ​​Iq_Ref and Id_Ref, and substitute the q-axis current error value into the q-axis current PI controller to calculate the q-axis voltage u q , substitute the d-axis current error value into the d-axis current PI controller to calculate the d-axis voltage u d , then the q-axis voltage u q and d-axis voltage u d Perform inverse Park transform to obtain the α-axis voltage u α and β-axis voltage u β , for the α-axis voltage u α and β-axis voltage u β The three-phase voltage is calculated using the SVPWM algorithm u a 、 u b and u c , and finally the three-phase voltage u a 、 u b and u c Input to the mathematical model of the motor; in the speed loop, the input of the speed loop is the difference between the actual speed of the motor and the speed setting value Speed_Ref, and the result of the difference calculated by the speed PI controller is used as the input of the current loop; in the position loop, the difference between the current position of the motor and the position setting value Position_Ref is calculated, and the difference is substituted into the position PI controller, and the output result is used as the speed setting value Speed_Ref.

2. The motor control method of a directional rotary steering tool according to claim 1, characterized in that: When initializing the motor control parameters, the temperature and drill size data are first determined, then the corresponding motor parameters are determined according to the temperature and drill size data, and finally the initialized motor control parameters are determined according to the motor parameters.

3. The motor control method of a directional rotary steering tool according to claim 1, characterized in that: When the motor control parameters are iterated using a genetic algorithm, the initialized motor control parameters are first genetically encoded, and then the performance of each genetic encoding is evaluated using a fitness function. A portion of individuals is selected as parents based on the fitness value of the genetic encoding, and a crossover operation is performed on the parents to generate new individuals. Then, a mutation operation is performed on the generated new individuals, and the performance of the newly generated individuals is evaluated using a fitness function. The newly generated individuals replace a portion of individuals with lower fitness in the current population to complete one iteration.

4. The motor control method for a directional rotary steering tool according to claim 1, characterized in that: Before inputting the iterated motor control parameters into the FOC three-closed-loop control simulation model, an objective function is also established, which includes the system error, PI controller output, rise time and their corresponding weights. After inputting the iterated motor control parameters into the FOC three-closed-loop control simulation model, the system error, PI controller output and rise time output by the FOC three-closed-loop control simulation model are input into the objective function to obtain corresponding function values, and whether the iterated motor control parameters meet the requirements is determined based on the function values.

5. The motor control method of a directional rotary steering tool according to claim 4, characterized in that: When establishing the objective function, the system error, PI controller output and rise time are first standardized to obtain standardized data, and then the corresponding information entropy is calculated based on the standardized data. Finally, the corresponding weights of the system error, PI controller output and rise time are determined based on the information entropy.

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