Intelligent control method for motor pump

Abstract

This invention provides an intelligent control method for an electric motor pump, relating to the field of electric steering technology for new energy vehicles. The method includes: driving the low-voltage winding to provide power to assist steering in the event of a high-voltage loss; determining the real-time calibrated values ​​of the motor's speed and torque based on the vehicle's real-time speed and steering angle; determining whether to perform coarse or fine adjustment based on the real-time value of the vehicle's steering wheel's rotational acceleration; adjusting the gain coefficient of the PID control algorithm based on the real-time value of the vehicle's steering wheel's rotational acceleration during coarse adjustment; and introducing a correction term into the PID control algorithm based on the real-time value of the vehicle's steering wheel's rotational acceleration during fine adjustment. This invention promptly switches to the low-voltage winding for power supply in the event of a high-voltage loss, avoiding the problem of not being able to provide steering assistance when the high-voltage winding fails. Furthermore, it adaptively performs coarse or fine adjustment based on the real-time value of rotational acceleration to ensure that appropriate steering assistance is provided to the vehicle more quickly.

Description

Technical Field

[0001] This invention relates to the field of electric steering technology for new energy vehicles, specifically an intelligent control method for motor pumps. Background Technology

[0002] With the popularization of new energy vehicles, mechanical hydraulic power steering pumps driven by engine belts have been replaced by electric power steering pumps. Current electric power steering pumps are typically driven by a high-voltage motor directly connected to the vehicle's high-voltage battery system (e.g., 500V or higher). While this design is efficient, it carries a single point of failure risk: if the high-voltage power system fails due to a collision, a blown fuse, or a controller malfunction, power steering will be completely lost instantly, posing a significant safety threat to vehicles traveling at high speeds. Therefore, there is an urgent need in this field for a reliable solution that can automatically and quickly activate a backup power source when the main power source fails, ensuring that steering function is not completely lost.

[0003] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent control method for motor pumps to solve the problems mentioned in the background art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] A smart control method for an electric motor pump, applied to a dual-source motor steering pump including a low-voltage winding and a high-voltage winding, includes the following steps:

[0007] S1, Real-time monitoring of whether high voltage loss occurs in the high voltage winding, and execution of step S2 when high voltage loss occurs;

[0008] S2, cut off the power supply to the high-voltage winding, drive the power supply to the low-voltage winding to provide steering assistance, and determine the real-time calibration values ​​of the motor speed and torque based on the vehicle's real-time speed and real-time steering angle.

[0009] S3. Based on the real-time value of the vehicle steering wheel rotation acceleration, determine whether to perform coarse adjustment. If yes, proceed to step S4; otherwise, proceed to step S5.

[0010] S4. Based on the PID control algorithm, analyze the real-time calibration values ​​of the speed and torque to make coarse adjustments to the motor speed and torque, and combine the real-time value of the vehicle steering wheel rotation acceleration to adjust the gain coefficient of the PID control algorithm.

[0011] S5 analyzes the real-time calibration values ​​of speed and torque based on the PID control algorithm to finely adjust the speed and torque of the motor, and introduces a correction term into the PID control algorithm in combination with the real-time value of the steering wheel's rotational acceleration.

[0012] Furthermore, the logic for determining whether a high-voltage loss has occurred is as follows: obtain the real-time voltage value of the high-voltage winding, calculate the difference between the real-time voltage value and the voltage value at the previous time step, and use it as the drop value. If the drop value exceeds the drop threshold, it is determined that a high-voltage loss has occurred; otherwise, it is determined that a high-voltage loss has not occurred.

[0013] Furthermore, based on the analysis of the vehicle's real-time speed and real-time steering angle using a deep neural network, the real-time calibration values ​​of the motor's speed and torque are determined. The deep neural network includes an input layer for receiving real-time vehicle speed and real-time steering angle, a hidden layer for extracting features from real-time vehicle speed and real-time steering angle, and an output layer for outputting real-time calibration values ​​of speed and torque.

[0014] Furthermore, the logic for determining whether to perform coarse adjustment is as follows: preset a high threshold and a low threshold for rotational acceleration. If the absolute value of the real-time value of rotational acceleration is not lower than the high threshold or not higher than the low threshold, then the coarse adjustment strategy is executed. If the absolute value of the real-time value of rotational acceleration is between the high threshold and the low threshold, then the fine adjustment strategy is executed, and the high threshold is greater than the low threshold.

[0015] Furthermore, the logic for adjusting the gain coefficients of the PID control algorithm is as follows: if the absolute value of the real-time rotational acceleration is not lower than the high threshold of rotational acceleration, then the relative difference between the absolute value of the real-time rotational acceleration and the high threshold of rotational acceleration is calculated as a correction fluctuation term; if the absolute value of the real-time rotational acceleration is not higher than the low threshold of rotational acceleration, then the relative difference between the absolute value of the real-time rotational acceleration and the low threshold of rotational acceleration is calculated as a correction fluctuation term, and a correction constant term of not less than 1 is predefined. The sum of the correction fluctuation term and the correction constant term is calculated as the correction coefficient. The initial values ​​of each gain coefficient are preset, and the product of the initial value of each gain coefficient and the correction coefficient is calculated as the adjusted real-time gain coefficients.

[0016] Furthermore, a correction threshold is preset, and the minimum value between the correction coefficient and the correction threshold is taken as the final correction coefficient.

[0017] Furthermore, the calculation logic of the correction term is as follows: within the numerical range formed by the high threshold of rotational acceleration as the upper limit and the low threshold of rotational acceleration as the lower limit, a suitable range of rotational acceleration is selected, the deviation between the real-time value of rotational acceleration and the suitable range of rotational acceleration is calculated, and the product of the deviation and the preset adjustment step size is used as the correction term.

[0018] Furthermore, the specific logic for performing fine adjustments is as follows: if the real-time value of rotational acceleration is within the appropriate range of rotational acceleration, the deviation is set to 0, and the output of the real-time speed adjustment signal and the real-time torque adjustment signal is set to 0, so that the speed and torque of the motor remain constant.

[0019] If the real-time value of rotational acceleration is higher than the upper limit of the suitable range of rotational acceleration, the relative difference between the upper limit of the suitable range of rotational acceleration and the real-time value of rotational acceleration is calculated and negative, which is used as the degree of deviation and a correction term is introduced into the formula of the PID control algorithm.

[0020] If the real-time value of rotational acceleration is lower than the lower limit of the suitable range of rotational acceleration, the relative difference between the lower limit of the suitable range of rotational acceleration and the real-time value of rotational acceleration is calculated as the degree of deviation, and a correction term is introduced into the formula of the PID control algorithm.

[0021] Furthermore, during the power supply process based on the low-voltage winding, a power limit value is set, and the power limit value is lower than the maximum operating power of the low-voltage winding. The motor speed and torque are adjusted with the motor output power not exceeding the power limit value as a constraint.

[0022] Compared with the prior art, the beneficial effects of the present invention are:

[0023] The intelligent control method for motor pumps of the present invention, through the coordinated setting of high-voltage winding and low-voltage winding, promptly switches to low-voltage winding for power supply when high-voltage loss occurs, avoiding the problem of not being able to provide steering assistance when the high-voltage winding fails. During the power supply based on the low-voltage winding, the motor speed and torque are adaptively adjusted by coarse or fine adjustment based on the real-time value of rotational acceleration, so as to ensure that appropriate steering assistance is provided to the vehicle more quickly, avoiding the problem of loss of steering control due to excessive steering assistance or difficulty in steering due to insufficient steering assistance. Attached Figure Description

[0024] Figure 1 This is a schematic flowchart of the overall method of the present invention;

[0025] Figure 2 This is a schematic diagram of the rotational acceleration feedback when this scheme is applied. Detailed Implementation

[0026] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0027] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0028] Example:

[0029] Please see Figure 1-2 This invention provides an intelligent control method for electric motor pumps, applied to dual-source motor steering pumps with the following structure:

[0030] An electric motor housing for mounting the stator and rotor;

[0031] A stator is installed inside the motor housing, and the stator has two completely independent winding systems: a high-voltage winding and a low-voltage winding. The high-voltage winding operates at 800V and has a rated power of 5kW. It uses high-voltage resistant insulation material, has many turns, and thin wire diameter, and is used to connect to the 800V high-voltage platform. The low-voltage winding operates at 24V and has a maximum power of 2.5kW. It uses conventional insulation material, has fewer turns, and thicker wire diameter, and is used to connect to the 24V low-voltage battery. The two windings are arranged in layers or slots to ensure sufficient electrical clearance and creepage distance. They work together on the same rotor.

[0032] A rotor, disposed within the motor housing and driven by the stator;

[0033] A steering pump connected to the front end of the rotor output shaft is used to provide steering assistance to the vehicle;

[0034] A low-voltage controller integrated into the rear end of the motor housing by bolts and seals contains an inverter bridge composed of MOSFETs or IGBTs and its drive circuit, which is specifically used to drive the low-voltage winding. It is electrically connected to the low-voltage winding, specifically through terminals to the vehicle's 24V battery and the vehicle's CAN bus, for driving and controlling the low-voltage winding.

[0035] An electronic control unit is electrically connected to the high-voltage power supply circuit, the high-voltage winding, and the low-voltage controller. It is used to monitor whether a high-voltage loss occurs and control the switching of the working state of the two windings. Specifically, when a high-voltage loss is detected, the power supply to the high-voltage winding is cut off, and a start signal is sent to the low-voltage controller so that the low-voltage controller drives the low-voltage winding to work.

[0036] The specific control methods are as follows:

[0037] S1, Real-time monitoring of whether high voltage loss occurs in the high voltage winding, and execution of step S2 when high voltage loss occurs;

[0038] The logic for determining whether a high voltage loss has occurred is as follows: The vehicle's own ECU monitors the voltage value of the high voltage winding in real time to obtain the real-time voltage value of the high voltage winding. The difference between the real-time voltage value and the voltage value at the previous time step is calculated as the drop value. If the drop value exceeds the drop threshold, it is determined that a high voltage loss has occurred; otherwise, it is determined that no high voltage loss has occurred. The ECU drives the high voltage winding to continue working through the high voltage inverter.

[0039] As one implementation method, the time step can be set to 0.1 seconds, 0.2 seconds, 0.5 seconds, etc., to accurately identify whether the high-voltage power supply has failed. For example, when the time step is 0.1 seconds, the difference between the real-time voltage value at the current moment and the voltage value 0.1 seconds ago is calculated as the drop value. The specific value of the drop threshold is set by the staff according to the actual situation. For example, for the 800V high voltage in this solution, if the voltage drops to below 100V in a very short time, it can be regarded as the high-voltage power supply failing due to collision, fuse blowing, controller failure, etc., and the power steering will be completely lost instantly. Therefore, the drop threshold can be set to 700V.

[0040] S2, cut off the power supply to the high-voltage winding, drive the power supply to the low-voltage winding to provide steering assistance, and determine the real-time calibration values ​​of the motor speed and torque based on the vehicle's real-time speed and real-time steering angle.

[0041] The system analyzes the vehicle's real-time speed and steering angle using a deep neural network to determine the real-time calibration values ​​of the motor's rotational speed and torque. The deep neural network includes an input layer for receiving the real-time vehicle speed and steering angle, a hidden layer for extracting features from these values, and an output layer for outputting the real-time calibration values ​​of rotational speed and torque. The input layer has two nodes for receiving the real-time vehicle speed and steering angle, respectively. The hidden layer can have 6-8 layers, with the number of nodes in each layer adjusted according to the actual situation, such as 64, 128, or 256 nodes. The ReLU function is used to improve the model's non-linearity. The output layer has two nodes for outputting the corresponding real-time calibration values ​​of rotational speed and torque. The training process for the deep neural network is as follows:

[0042] Multiple vehicle speed test points and steering angle test points are pre-set and arranged in combination to construct several test scenarios with different vehicle speeds and steering angles. The same model of vehicle is tested in a closed test site to determine the speed and torque of the motor in the dual-source motor steering pump when the vehicle can maintain stable steering in different test scenarios. These are used as the speed calibration values ​​and torque calibration values ​​for the corresponding test scenarios. The vehicle speed, steering angle, speed calibration values, and torque calibration values ​​for each test scenario are summarized to form a sample set.

[0043] As one implementation method, the vehicle speed measurement points are sampled at 5 km / h intervals, and the speed is obtained at equal intervals within the range of 0-80 km / h. The steering angle measurement points are sampled at 5° intervals, and the speed is obtained at equal intervals within the range of 0°-60°.

[0044] It should be noted that when determining whether stable steering is met, it can be done by analyzing the vehicle's slip angle and steering response time during steering. For example, a slip angle of no more than 5 degrees and a steering response time of no more than 1 second are considered necessary conditions for stable steering. The vehicle speed, steering angle, rotational speed, and torque are specifically monitored and obtained in real time through the vehicle's speed sensor, steering sensor, motor control system, and motor drive system. This is existing technology and will not be elaborated here.

[0045] The sample set is divided into training, testing, and validation sets in a 70:15:15 ratio. Batch size and training epochs are set, with the batch size between 32 and 256 and the training epochs between 30 and 50. Vehicle speed and steering angle from the training set are used as inputs, and the corresponding speed and torque calibration values ​​are used as output labels to train the deep neural network. Mean squared error is used as the loss function. During training, model parameters are updated through backpropagation to minimize the loss function. Specifically, optimization algorithms such as Adam and SGD can be used to update the model parameters during the training process. In this process, model hyperparameters such as learning rate, batch size, and number of hidden layers are adjusted using a validation set to optimize model performance. The initial value of the learning rate can be set between 0.001 and 0.01. After a predetermined training period, the test set is input into the deep neural network for performance testing. If the relative error is less than a preset threshold, the training is considered complete. Otherwise, the model hyperparameters are adjusted and retraining is performed. The preset threshold can be set between 3% and 8% to ensure that the trained model has good simulation fitting ability. The specific value can be set by the staff according to the actual situation and is not restricted here.

[0046] S3: Based on the real-time value of the vehicle's steering wheel rotation acceleration, determine whether to perform a coarse adjustment. If yes, proceed to step S4; otherwise, proceed to step S5. The specific logic is as follows:

[0047] Preset high and low thresholds for rotational acceleration. If the absolute value of the real-time rotational acceleration is not lower than the high threshold, it indicates that the steering wheel response is too sensitive, posing a risk of loss of steering control. This suggests that the real-time speed or torque value deviates significantly from its calibration value. Therefore, a coarse adjustment strategy is implemented to quickly adjust the motor's torque and speed to bring them closer to the calibration value, thus avoiding the risk of loss of steering control. Similarly, if the absolute value of the real-time rotational acceleration is not higher than the low threshold, it indicates that the steering wheel response is too slow, posing a risk of not being able to steer in time. This suggests that the real-time speed or torque value deviates significantly from its calibration value. If the real-time torque value deviates significantly from its calibration value, a coarse adjustment strategy is implemented to quickly adjust the motor's torque and speed to bring them close to the calibration value, thus avoiding the risk of not being able to steer in time. If the absolute value of the real-time rotational acceleration is between the high and low thresholds of rotational acceleration, it indicates that the steering wheel is controllable, which means that the real-time speed or torque value is close to its calibration value. However, the calibration value is only data determined by the test site and may not be suitable for the current environmental conditions of the vehicle. Therefore, a fine adjustment strategy is implemented to make the real-time speed and torque values ​​approach their ideal values.

[0048] It should be noted that the real-time value of rotational acceleration is collected by a gyroscope installed on the steering wheel, with clockwise rotation as positive and counterclockwise rotation as negative. Its sampling frequency is consistent with that of torque and speed to ensure timestamp alignment. The specific values ​​of the high threshold and low threshold of rotational acceleration are set by the staff according to the actual situation. For example, the high threshold of rotational acceleration can be set between 7° / s² and 10° / s² to determine whether the steering wheel response is too sensitive, and the low threshold of rotational acceleration can be set between 1° / s² and 4° / s² to determine whether the steering wheel response is too sluggish. The specific values ​​are not specifically limited here.

[0049] S4. Based on the PID control algorithm, analyze the real-time calibration values ​​of the speed and torque to make coarse adjustments to the motor speed and torque, and combine the real-time value of the vehicle steering wheel rotation acceleration to adjust the gain coefficient of the PID control algorithm.

[0050] The mathematical expression for coarse adjustment of the motor speed and torque based on the PID control algorithm is as follows:

[0051]

[0052] In the formula, This is the real-time torque value. Indicates the current moment. This is the real-time torque calibration value, which is obtained based on real-time vehicle speed and real-time steering angle. The torque real-time error is the difference between the real-time torque calibration value and the real-time torque value. The larger the absolute value of the torque real-time error, the greater the deviation of the real-time torque value from the real-time torque calibration value.

[0053] In the formula, This is a real-time torque adjustment signal used to adjust the motor's torque. , , These are the real-time proportional gain coefficient, the real-time integral gain coefficient, and the real-time differential gain coefficient, all of which are adjusted and determined based on the real-time value of the vehicle's steering wheel rotational acceleration. This indicates the initial moment, that is, the moment when the low-voltage winding begins to supply power. The time variable is the time from the initial time to the current time. Let be the torque error at time t, and , , These are the torque calibration value and torque value at time t, respectively. The real-time differential term for torque is calculated as follows: the difference between the real-time torque error and the previous torque error is calculated, and the ratio of this difference to the sampling time interval is calculated as the real-time differential term for torque. The specific sampling time interval is determined based on the sampling frequency, which is generally set between 100Hz and 500Hz. For example, if the sampling frequency is set to 100Hz, the sampling time interval is 0.01 seconds, that is, the torque is sampled once every 0.01 seconds. The difference between the real-time torque error in the current sampling round and the torque error in the previous sampling round is calculated, and then the difference is divided by 0.01 seconds to obtain the real-time differential term for torque.

[0054] In the formula, This is the real-time value of the rotational speed. This is the real-time calibration value for the engine speed, which is obtained based on the real-time vehicle speed and real-time steering angle. The real-time speed error is the difference between the real-time speed calibration value and the real-time speed value. The larger the absolute value of the real-time speed error, the greater the deviation of the real-time speed value from the real-time speed calibration value.

[0055] In the formula, This is a real-time speed control signal used to adjust the motor speed. , , These are the real-time proportional gain coefficient, real-time integral gain coefficient, and real-time differential gain coefficient of the vehicle's steering wheel, all of which are determined based on the real-time value of the vehicle's steering wheel rotational acceleration. Let be the rotational speed error at time t, and , , These are the speed calibration value and speed value at time t, respectively. The real-time differential term for rotational speed is calculated as follows: the difference between the real-time error of rotational speed and the difference between the previous rotational speed error is calculated, and the ratio of this difference to the sampling time interval is calculated as the real-time differential term of rotational speed. The sampling frequencies of rotational speed and torque are the same to align the time axis.

[0056] The logic for adjusting the gain coefficients of the PID control algorithm is as follows: If the absolute value of the real-time rotational acceleration is not lower than the high threshold of rotational acceleration, the relative difference between the absolute value of the real-time rotational acceleration and the high threshold is calculated as a correction fluctuation term. If the absolute value of the real-time rotational acceleration is not higher than the low threshold of rotational acceleration, the relative difference between the absolute value of the real-time rotational acceleration and the low threshold is calculated as a correction fluctuation term. A correction constant term of not less than 1 is predefined. The sum of the correction fluctuation term and the correction constant term is calculated as the correction coefficient. Initial values ​​for each gain coefficient are preset, and the product of each initial value of the gain coefficient and the correction coefficient is calculated as the adjusted real-time gain coefficients. The mathematical expression is as follows:

[0057]

[0058] In the formula, This represents the initial value of the gain coefficient. These represent the initial values ​​of the torque proportional gain coefficient, torque integral gain coefficient, torque differential gain coefficient, speed proportional gain coefficient, speed integral gain coefficient, and speed differential gain coefficient, respectively. This represents the adjusted real-time gain coefficient. These represent the real-time proportional gain coefficient, real-time integral gain coefficient, real-time differential gain coefficient, real-time proportional gain coefficient, real-time integral gain coefficient, and real-time differential gain coefficient of torque, respectively. To correct the constant term, This is the real-time value of rotational acceleration. For high threshold of rotational acceleration, Low threshold for rotational acceleration;

[0059] As an implementation method, the torque proportional gain coefficient and the speed proportional gain coefficient directly affect the system's response speed. Their initial values ​​are generally set between 0.5 and 1. The torque integral gain coefficient and the speed integral gain coefficient are used to eliminate steady-state errors. Their initial values ​​are generally set between 0.01 and 1, which are smaller than the initial values ​​of the torque proportional gain coefficient and the speed proportional gain coefficient. The torque differential gain coefficient and the speed differential gain coefficient are used to predict the future behavior of the system, thereby reducing overshoot and oscillation. Their initial values ​​are generally set between 0 and 1, which are smaller than the initial values ​​of the torque proportional gain coefficient and the speed proportional gain coefficient. The correction constant term is generally set between 1 and 1.5 to avoid excessive amplification of the gain coefficient, which could lead to excessive fluctuations in system regulation.

[0060] It should be noted that the larger the correction fluctuation term, the worse the steering wheel operability, which in turn indicates that the current output steering assistance is too large or too small, and the greater the deviation of the real-time speed or torque value from its calibration value. The adjustment process needs to be accelerated so that the real-time speed or torque value can quickly approach its calibration value, and therefore the amplification degree of the gain coefficient is also higher.

[0061] Furthermore, a correction threshold is preset, and the minimum value of the correction coefficient and the correction threshold is taken as the final correction coefficient for the real-time gain coefficient calculation in the following text. This avoids the problem of excessive amplification of the gain coefficient, which would lead to excessive fluctuations in system adjustment. The specific value of the correction threshold can be set between 2 and 3, and the specific setting is determined by the staff according to the actual situation. It will not be elaborated here.

[0062] S5, based on the PID control algorithm, analyzes the real-time calibration values ​​of speed and torque to finely adjust the speed and torque of the motor, and introduces a correction term into the PID control algorithm in combination with the real-time value of the steering wheel's rotational acceleration.

[0063] The calculation logic of the correction term is as follows: within the numerical range formed by the high threshold of rotational acceleration as the upper limit and the low threshold of rotational acceleration as the lower limit, a suitable range of rotational acceleration is selected, the deviation between the real-time value of rotational acceleration and the suitable range of rotational acceleration is calculated, and the product of the deviation and the preset adjustment step size is used as the correction term.

[0064] It should be noted that the specific value of the adjustment step size is set by the staff according to the actual situation. For example, it can be set to between 1% and 5% of the maximum adjustment amount in a single operation to ensure the degree of fine adjustment when performing fine adjustments and avoid the problem of excessive fluctuations in system adjustment.

[0065] The specific logic for fine adjustment is as follows: if the real-time value of rotational acceleration is within the appropriate range of rotational acceleration, it indicates that the real-time value of rotational acceleration is appropriate, which in turn indicates that the steering assistance of the vehicle is in an ideal state. This means that the real-time values ​​of speed and torque are close to the ideal values. Therefore, the deviation is set to 0, the correction term is also set to 0, and the output of the real-time speed adjustment signal and the real-time torque adjustment signal is set to 0, so that the speed and torque of the motor remain unchanged.

[0066] If the real-time value of rotational acceleration is higher than the upper limit of the suitable range for rotational acceleration, it indicates that the real-time value of rotational acceleration is too large. This means that although the steering wheel is controllable, its sensitivity is still too high, indicating that the vehicle's steering assistance is too strong. The engine speed or torque should be appropriately reduced. Therefore, the relative difference between the upper limit of the suitable range for rotational acceleration and the real-time value of rotational acceleration is calculated and taken as negative to represent the degree of deviation. A correction term is introduced into the PID control algorithm formula. Because both the degree of deviation and the correction term are negative, the real-time speed and torque adjustment signals are reduced from their original output values, thus avoiding the problem of the motor's speed and torque deviating significantly from their ideal values. For example, in... When the value is positive, it indicates that the real-time torque value is smaller than the real-time torque calibration value. According to a conventional PID control algorithm, the torque should be increased. However, the steering assist is already too high at this point, and further increases would lead to excessive steering assist. Introducing a negative correction term in this solution reduces the increase in torque, ensuring that the steering assist is not too high and affects operation. For example, in... When the value is negative, it indicates that the real-time torque value is too large compared to the real-time torque calibration value. According to the conventional PID control algorithm, the torque should be reduced. In fact, the steering assist is also too large at this time. After introducing the negative correction term in this solution, the speed of torque reduction will be accelerated to reduce the duration of excessive steering assist.

[0067] If the real-time value of rotational acceleration is lower than the lower limit of the suitable range, it indicates that the real-time value of rotational acceleration is too small. This means that although the steering wheel is controllable, its sensitivity is still low, indicating that the vehicle's steering assistance is too weak. The engine speed or torque should be appropriately increased. Therefore, the relative difference between the lower limit of the suitable range and the real-time value of rotational acceleration is calculated as the degree of deviation. A correction term is introduced into the PID control algorithm formula. Since both the degree of deviation and the correction term are positive, the real-time speed and torque adjustment signals are increased based on their original output values. This avoids the problem of the motor's speed and torque deviating significantly from their ideal values. For example... When the value is positive, it indicates that the real-time torque value is smaller than the real-time torque calibration value. According to the conventional PID control algorithm, the torque should be increased. In fact, the steering assist is also too low at this time. After introducing the positive correction term in this scheme, the speed of torque increase will be accelerated, thereby reducing the duration of low steering assist. For example, in... When the value is negative, it indicates that the real-time torque value is too large compared to the real-time torque calibration value. According to the conventional PID control algorithm, the torque should be reduced. However, the steering assist is already too small at this time. If it is reduced further, it will lead to the problem of insufficient steering assist. However, after introducing the positive correction term in this solution, the amount of torque reduction will be reduced to ensure that the steering assist is not too small and will affect the operation.

[0068] It should be noted that the real-time calibration values ​​of speed and torque are measured under test conditions and may not necessarily reflect the current environmental conditions of the vehicle. For example, the current weight of the vehicle and the coefficient of friction of the ground on which the vehicle is currently located are quite different from those of the vehicle under test conditions. Therefore, although the real-time calibration values ​​may be close to the current optimal ideal values, they may not be the current ideal values. Since the ideal values ​​are difficult to calculate directly, a correction term is introduced based on the real-time value of rotational acceleration during the adjustment process when the steering wheel is controllable, so that the speed and torque of the motor are close to the optimal ideal values ​​to ensure the suitability of vehicle operation.

[0069] The specific mathematical expression for the degree of deviation is as follows:

[0070]

[0071] In the formula, , These are the lower and upper limits of the suitable range for rotational acceleration, respectively. This indicates the degree of deviation determined based on the real-time value of rotational acceleration. The specific logic of this mathematical expression has been described above and will not be repeated here.

[0072] It should be noted that the specific values ​​of the lower and upper limits of the suitable range of rotational acceleration are set by the staff according to the actual situation. For example, the upper limit of the suitable range of rotational acceleration can be set between 6° / s² and 7° / s², and the lower limit of the suitable range of rotational acceleration can be set between 4° / s² and 5° / s² to ensure the appropriateness of the steering wheel response. The specific values ​​are not specifically limited here.

[0073] The specific mathematical expressions for fine-tuning the motor speed and torque based on the PID control algorithm are as follows:

[0074]

[0075]

[0076] In the formula, The specific logic of this mathematical expression for setting the adjustment step size has been described above and will not be repeated here.

[0077] Please see below. Figure 2 Based on this scheme, the rotational acceleration curves obtained in real time during the adjustment of speed and torque are shown below. Figure 2 As shown, in the initial stage when the low-voltage winding starts supplying power, the steering assistance provided is low, and the rotational acceleration is also low. As time progresses, the torque and speed are continuously adjusted to update and optimize the steering assistance. Coarse adjustment is performed in the time range of 0-1.5 seconds to quickly increase the speed and torque to rapidly increase the steering assistance, so that the rotational acceleration as feedback increases rapidly until it rises to a suitable value of about 4.2° / s². The steering assistance reaches a relatively suitable state, and then fine adjustment is performed to gradually and finely adjust the torque and speed according to the environment to ensure that a relatively good steering assistance is provided, so that the rotational acceleration as feedback is maintained within a suitable range.

[0078] Furthermore, during the power supply process based on the low-voltage winding, a power limit value is set, which is lower than the maximum operating power of the low-voltage winding. The motor speed and torque are adjusted under the constraint that the motor output power does not exceed the power limit value. Specifically, before executing the real-time torque adjustment signal and the real-time speed adjustment signal, the torque adjustment value is determined based on the real-time torque adjustment signal and the real-time torque value. Similarly, the speed adjustment value is determined based on the real-time speed adjustment signal and the real-time speed value. Finally, the motor output power adjustment value is determined by combining the torque adjustment value and the speed adjustment value. If the motor output power adjustment value exceeds the power limit value, the real-time torque adjustment signal and the real-time speed adjustment signal are not executed; otherwise, they are executed. This is to prevent the motor output power adjustment value from exceeding the power limit value, which could lead to a low-voltage winding overload fault. The specific value of the power limit value is determined by the operator based on the actual situation. For example, for a low-voltage winding with a maximum operating power of 2.5 kW in this solution, the power limit value can be set to 2 kW.

[0079] It should be noted that the specific mathematical expression for determining the output power based on the rotational speed and torque is as follows:

[0080]

[0081] In the formula, This represents torque, measured as the product of Newtons and meters. This indicates the rotational speed, measured in revolutions per minute. This indicates the output power, measured in watts. This is a common formula and will not be explained here.

[0082] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0083] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0084] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0085] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. An intelligent control method for an electric motor pump, applied to a dual-source motor steering pump including a low-voltage winding and a high-voltage winding, characterized in that, Includes the following steps: S1, Real-time monitoring of whether high voltage loss occurs in the high voltage winding, and execution of step S2 when high voltage loss occurs; S2, cut off the power supply to the high-voltage winding, drive the power supply to the low-voltage winding to provide steering assistance, and determine the real-time calibration values ​​of the motor speed and torque based on the vehicle's real-time speed and real-time steering angle. S3. Based on the real-time value of the vehicle steering wheel rotation acceleration, determine whether to perform coarse adjustment. If yes, proceed to step S4; otherwise, proceed to step S5. S4. Based on the PID control algorithm, analyze the real-time calibration values ​​of the speed and torque to make coarse adjustments to the motor speed and torque, and combine the real-time value of the vehicle steering wheel rotation acceleration to adjust the gain coefficient of the PID control algorithm. S5, based on the PID control algorithm, analyzes the real-time calibration values ​​of speed and torque to finely adjust the speed and torque of the motor, and introduces a correction term into the PID control algorithm in combination with the real-time value of the steering wheel's rotational acceleration. The logic for determining whether a high-voltage loss has occurred is as follows: obtain the real-time voltage value of the high-voltage winding, calculate the difference between the real-time voltage value and the voltage value at the previous time step, and use it as the drop value. If the drop value exceeds the drop threshold, it is determined that a high-voltage loss has occurred; otherwise, it is determined that a high-voltage loss has not occurred.

2. The intelligent control method for an electric pump according to claim 1, characterized in that: The vehicle's real-time speed and steering angle are analyzed using a deep neural network to determine the real-time calibration values ​​of the motor's speed and torque. The deep neural network includes an input layer for receiving real-time vehicle speed and steering angle, a hidden layer for extracting features from real-time vehicle speed and steering angle, and an output layer for outputting the real-time calibration values ​​of speed and torque.

3. The intelligent control method for an electric pump according to claim 1, characterized in that, The logic for determining whether to perform coarse adjustment is as follows: preset a high threshold and a low threshold for rotational acceleration. If the absolute value of the real-time value of rotational acceleration is not lower than the high threshold or not higher than the low threshold, then the coarse adjustment strategy is executed. If the absolute value of the real-time value of rotational acceleration is between the high threshold and the low threshold, then the fine adjustment strategy is executed, and the high threshold is greater than the low threshold.

4. The intelligent control method for an electric pump according to claim 3, characterized in that, The logic for adjusting the gain coefficients of the PID control algorithm is as follows: If the absolute value of the real-time rotational acceleration is not lower than the high threshold of rotational acceleration, the relative difference between the absolute value of the real-time rotational acceleration and the high threshold of rotational acceleration is calculated as a correction fluctuation term. If the absolute value of the real-time rotational acceleration is not higher than the low threshold of rotational acceleration, the relative difference between the absolute value of the real-time rotational acceleration and the low threshold of rotational acceleration is calculated as a correction fluctuation term. A correction constant term of not less than 1 is predefined. The sum of the correction fluctuation term and the correction constant term is calculated as the correction coefficient. The initial values ​​of each gain coefficient are preset, and the product of the initial value of each gain coefficient and the correction coefficient is calculated as the adjusted real-time gain coefficients.

5. The intelligent control method for an electric pump according to claim 4, characterized in that: A preset correction threshold is set, and the minimum value between the correction coefficient and the correction threshold is taken as the final correction coefficient.

6. The intelligent control method for an electric motor pump according to claim 3, characterized in that, The calculation logic of the correction term is as follows: within the numerical range formed by the high threshold of rotational acceleration as the upper limit and the low threshold of rotational acceleration as the lower limit, a suitable range of rotational acceleration is selected, the deviation between the real-time value of rotational acceleration and the suitable range of rotational acceleration is calculated, and the product of the deviation and the preset adjustment step size is used as the correction term.

7. The intelligent control method for an electric pump according to claim 6, characterized in that, The specific logic for performing fine adjustments is as follows: if the real-time value of rotational acceleration is within the appropriate range of rotational acceleration, set the deviation to 0, and set the output of the real-time speed adjustment signal and the real-time torque adjustment signal to 0, so that the speed and torque of the motor remain constant. If the real-time value of rotational acceleration is higher than the upper limit of the suitable range of rotational acceleration, the relative difference between the upper limit of the suitable range of rotational acceleration and the real-time value of rotational acceleration is calculated and negative, which is used as the degree of deviation and a correction term is introduced into the formula of the PID control algorithm. If the real-time value of rotational acceleration is lower than the lower limit of the suitable range of rotational acceleration, the relative difference between the lower limit of the suitable range of rotational acceleration and the real-time value of rotational acceleration is calculated as the degree of deviation, and a correction term is introduced into the formula of the PID control algorithm.

8. The intelligent control method for an electric pump according to claim 1, characterized in that: In the process of power supply based on low-voltage winding, a power limit value is set, which is lower than the maximum operating power of the low-voltage winding. The motor speed and torque are adjusted with the motor output power not exceeding the power limit value as a constraint.

Images