A driving feedback optimization control method and system for a pure electric sludge transport vehicle

Abstract

The present application provides a driving feedback optimization and control method and system for a pure electric sludge transport vehicle, which includes the following steps: obtaining the expected dynamic response information of the pure electric sludge transport vehicle in the absence of sludge disturbance based on driver operation information, current speed information and vehicle gross mass information; evaluating the degree of dynamic disturbance caused by sludge shaking based on the dynamic characteristics of the deviation between the actual dynamic response information and the expected dynamic response information changing over time to obtain a sludge disturbance evaluation result; determining a target control strategy based on the sludge disturbance evaluation result and the vehicle gross mass information, and then controlling the pure electric sludge transport vehicle according to the target control strategy; this method can effectively solve the problem of incorrect vehicle control and insufficient accuracy and reliability of parameter control due to the inability to distinguish between the acceleration of the vehicle itself in response to the driver's instructions and the disturbance acceleration caused by sludge shaking.

Description

Technical Field

[0001] The present application relates to the technical field of pure electric sludge transport vehicles, and in particular to a driving feedback optimization and control method and system for a pure electric sludge transport vehicle. Background Art

[0002] As an environmentally friendly specialty vehicle, a pure electric sludge transporter operates on a fixed transport route, typically connecting a sewage treatment plant with a designated sludge disposal site, forming a cyclical operation cycle. The vehicle departs the disposal site unloaded, travels to the sewage treatment plant to load sludge, and then returns to the disposal site loaded with sludge for unloading. During this operation, the vehicle's gross mass varies significantly between unloaded and loaded states. Furthermore, the amount of sludge transported each time is not fixed but fluctuates based on the sewage treatment plant's daily output, making the actual gross mass of the vehicle on each loaded trip an uncertain variable.

[0003] What is even more complicated is that the transported sludge is not a solid cargo, but a semi-fluid substance with a certain degree of fluidity. This means that during the vehicle's driving process, especially during dynamic operations such as acceleration, braking, turning or passing through uneven roads, the sludge in the tank will shake violently. This shaking is not just a simple transfer of mass. It will produce dynamic and unpredictable impact force and cause real-time, high-frequency changes in the vehicle's overall center of gravity.

[0004] Traditional vehicle control systems rely on sensors installed on the vehicle body (such as accelerometers and angular velocity sensors) to sense the dynamic state of the vehicle and control the parameters of the vehicle system based on the dynamic state of the vehicle. However, the signals measured by these sensors are the superposition of the vehicle's own acceleration in response to driver commands (such as throttle, brakes, and steering) and the disturbance acceleration caused by sludge shaking. Traditional vehicle control systems cannot directly separate the signals from these two sources. This signal aliasing may cause the system to misjudge the acceleration fluctuations caused by sludge shaking as changes caused by driver commands, thereby performing incorrect vehicle control parameter compensation. For example, when the vehicle performs a braking operation before entering a curve, the sludge will surge forward and generate a forward thrust. The system may mistakenly believe that the driver is accelerating the vehicle. At this time, the system mistakenly increases the output torque of the drive motor and reduces the control parameters related to vehicle body stability, thereby increasing the risk of rollover; when passing a curve and the vehicle needs to accelerate, the system will mistakenly believe that the sludge shaking effect is reduced or reverse shaking occurs as the driver is braking the vehicle. At this time, the system mistakenly reduces the output torque of the drive motor, resulting in uneven output of driving force and a "rushing" feeling of the vehicle. It can be seen that the existing technology has the problem of incorrect vehicle regulation due to the inability to distinguish between the acceleration of the vehicle itself in response to driver commands (such as throttle, brake, and steering) and the disturbance acceleration caused by sludge shaking, and the accuracy and reliability of parameter control are insufficient, which leads to a decrease in driving safety and driving experience.

[0005] There is no effective technical solution to the above problems. It should be noted that the above information disclosed in this section is only used to understand the background of the present invention, and therefore may contain information that does not constitute prior art. Summary of the Invention

[0006] The purpose of this application is to provide a driving feedback optimization and control method and system for a pure electric sludge transport vehicle, which can effectively solve the problem of incorrect vehicle control and insufficient accuracy and reliability of parameter control due to the inability to distinguish between the acceleration of the vehicle itself in response to the driver's instructions and the disturbance acceleration caused by sludge shaking.

[0007] In a first aspect, the present application provides a driving feedback optimization and control method for a pure electric sludge transport vehicle, which comprises the following steps:

[0008] S1. Obtaining driver operation information, actual dynamic response information, current speed information, and vehicle gross mass information of the pure electric sludge transport vehicle;

[0009] S2. obtaining expected dynamic response information of the pure electric sludge transport vehicle in the absence of sludge disturbance based on driver operation information, current speed information, and vehicle gross mass information;

[0010] S3. When the expected dynamic response information is different from the actual dynamic response information, the degree of dynamic disturbance caused by the sludge sloshing is evaluated according to the dynamic characteristics of the deviation between the actual dynamic response information and the expected dynamic response information over time, so as to obtain a sludge disturbance evaluation result;

[0011] S4. Determine a target control strategy based on the sludge disturbance assessment results and the vehicle gross mass information, and then control the pure electric sludge transport vehicle according to the target control strategy.

[0012] In a second aspect, the present application also provides a driving feedback optimization and control system for a pure electric sludge transport vehicle, which includes:

[0013] An information acquisition module is used to obtain driver operation information, actual dynamic response information, current speed information and vehicle gross mass information of the pure electric sludge transport vehicle;

[0014] An expected dynamic response acquisition module is used to acquire expected dynamic response information of the pure electric sludge transport vehicle in the absence of sludge disturbance based on driver operation information, current speed information and vehicle gross mass information;

[0015] A disturbance assessment module is used to assess the degree of dynamic disturbance caused by sludge shaking according to the dynamic characteristics of the deviation between the actual dynamic response information and the expected dynamic response information over time when the expected dynamic response information is different from the actual dynamic response information, so as to obtain a sludge disturbance assessment result;

[0016] The vehicle control module is used to determine the target control strategy based on the sludge disturbance assessment results and the vehicle's total mass information, and then control the pure electric sludge transport vehicle according to the target control strategy.

[0017] From the above, it can be seen that the present application provides a driving feedback optimization and control method and system for a pure electric sludge transport vehicle, which can separate and quantify the dynamic disturbance caused by sludge shaking by evaluating the degree of dynamic disturbance caused by sludge shaking based on the dynamic characteristics of the deviation between the actual dynamic response and the expected dynamic response calculated without sludge disturbance over time. That is, the present application can effectively separate the signal from the vehicle itself in response to the driver's command and the disturbance signal caused by sludge shaking. Therefore, the present application can effectively solve the problem of incorrect vehicle control due to the inability to distinguish between the acceleration of the vehicle itself in response to the driver's command and the disturbance acceleration caused by sludge shaking, and the problem of insufficient accuracy and reliability of parameter control, thereby effectively improving driving safety and driving experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flow chart of a driving feedback optimization and control method for a pure electric sludge transport vehicle provided in an embodiment of the present application.

[0019] Figure 2 A schematic structural diagram of a driving feedback optimization and control system for a pure electric sludge transport vehicle provided in an embodiment of the present application.

[0020] Reference numerals: 1. Information acquisition module; 2. Expected dynamic response acquisition module; 3. Disturbance assessment module; 4. Vehicle control module. DETAILED DESCRIPTION

[0021] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work fall within the scope of protection of the present application.

[0022] It should be noted that similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and should not be understood as indicating or implying relative importance.

[0023] In the field of traditional pure electric sludge transport vehicles, when transporting fluid sludge, the sludge inside the tank experiences dynamic sloshing, generating unpredictable disturbance forces. The vehicle control system relies on sensors mounted on the vehicle body to sense the vehicle's dynamic state and control the parameters of various vehicle systems based on this sensed state. The signals measured by these sensors are a superposition of the vehicle's acceleration in response to driver commands and the disturbance acceleration caused by sludge sloshing. This signal aliasing makes it impossible for the system to accurately distinguish between the vehicle's true dynamic response and sludge disturbances, thus affecting control accuracy.

[0024] For example, imagine a fully electric sludge transporter braking before entering a curve. The driver inputs a braking command via the brake pedal, which should cause the vehicle to decelerate accordingly. However, due to the sludge's inertia, it surges forward during braking, exerting a forward thrust on the vehicle. The signal measured by the vehicle's acceleration sensor is the superposition of the vehicle's deceleration due to braking and the acceleration (in the opposite direction of the deceleration) caused by the sludge surge. If the acceleration caused by the sludge surge is large, the net deceleration measured by the sensor may be less than the deceleration expected by the system based on the driver's braking command and the vehicle's state. It may even appear as a slight acceleration trend. The vehicle control system may misinterpret this signal as insufficient braking or even an intention to accelerate, resulting in inappropriate control actions.

[0025] If these issues are not addressed, the vehicle control system's adjustments based on aliased signals will fail to accurately reflect the driver's true intentions and the vehicle's actual force state. This can result in the system outputting erroneous control commands when precise vehicle dynamics (such as steering, braking, and acceleration) are required. For example, the system may mistakenly increase driving force or decrease braking force in a curve, increasing the risk of vehicle instability. Furthermore, inaccurate control can cause a jerky and unsmooth ride, impacting the driving experience.

[0026] In this regard, firstly, Figure 1 As shown, the present application provides a driving feedback optimization and control method for a pure electric sludge transport vehicle, which includes the following steps:

[0027] S1. Obtaining driver operation information, actual dynamic response information, current speed information, and vehicle gross mass information of the pure electric sludge transport vehicle;

[0028] S2. obtaining expected dynamic response information of the pure electric sludge transport vehicle in the absence of sludge disturbance based on driver operation information, current speed information, and vehicle gross mass information;

[0029] S3. When the expected dynamic response information is different from the actual dynamic response information, the degree of dynamic disturbance caused by the sludge sloshing is evaluated according to the dynamic characteristics of the deviation between the actual dynamic response information and the expected dynamic response information over time, so as to obtain a sludge disturbance evaluation result;

[0030] S4. Determine a target control strategy based on the sludge disturbance assessment results and the vehicle gross mass information, and then control the pure electric sludge transport vehicle according to the target control strategy.

[0031] In this embodiment, driver operation information refers to signals obtained from a driver input device. This embodiment can obtain driver operation information by using pedal sensors and steering wheel sensors for data collection or by querying existing vehicle communication networks. This driver operation information can reflect the driving intention of the driver of the pure electric sludge transport vehicle. In this embodiment, actual dynamic response information refers to the current motion state of the pure electric sludge transport vehicle. This embodiment can obtain actual dynamic response information using an inertial measurement unit or other motion sensor. This actual dynamic response information is used to represent the actual dynamic behavior of the vehicle. In this embodiment, current speed information refers to the current speed of the pure electric sludge transport vehicle. This embodiment can obtain current speed information using wheel speed sensors or a GPS module. In this embodiment, gross vehicle mass information refers to the total weight of the pure electric sludge transport vehicle (the sum of the weight of the pure electric sludge transport vehicle itself and the weight of the loaded sludge). This embodiment can obtain gross vehicle mass information by using load sensors installed on the suspension system for data collection or by estimating the gross weight of the pure electric sludge transport vehicle by analyzing the relationship between the vehicle's acceleration response and driving / braking forces. Step S2 is equivalent to calculating the dynamic performance of the vehicle under ideal conditions (i.e., without sludge shaking interference) based on the driver's input, the current motion state of the vehicle, and the load condition of the vehicle, so as to obtain the expected dynamic response information. Specifically, this embodiment can use a vehicle dynamics model to obtain the expected dynamic response information of the pure electric sludge transport vehicle under no sludge disturbance based on the driver's operation information, the current speed information, and the total mass of the vehicle. For example, a simplified vehicle model (such as a two-degree-of-freedom or three-degree-of-freedom model) is established. The model takes the driver's operation (throttle, brake, steering), the current speed, and the total mass of the vehicle as inputs, and outputs the expected dynamic response information of the vehicle under no disturbance. Dynamic responses such as acceleration and angular velocity, the model is preferably established based on physical equations and trained through data-driven methods (such as machine learning). This embodiment can also obtain expected dynamic response information by querying a pre-built mapping relationship table of driver operation information, current speed information, vehicle gross mass information and ideal vehicle dynamic response based on driver operation information, current speed information and vehicle gross mass information. The mapping relationship table stores the ideal vehicle dynamic responses corresponding to different combinations of driver operation information, current speed information and vehicle gross mass information. This embodiment can provide a reference benchmark for subsequent steps to identify disturbances by calculating the expected dynamic response information.Step S3 refers to judging and quantifying the impact of sludge sloshing on the vehicle by analyzing the dynamic characteristics of the difference when the actual dynamic response of the vehicle differs from the expected dynamic response calculated in step S2. This embodiment can use signal processing and state estimation technology to evaluate the degree of dynamic disturbance caused by sludge sloshing according to the dynamic characteristics of the deviation between the actual dynamic response information and the expected dynamic response information that changes over time. For example, the deviation signal between the actual dynamic response and the expected dynamic response is calculated, and then the additional force and torque generated by the sludge sloshing are estimated by analyzing the amplitude, frequency, phase and other time-varying characteristics of the deviation signal using a Kalman filter, a Luenberger observer or a machine learning-based algorithm to obtain a sludge disturbance evaluation result. That is, the sludge disturbance evaluation result is equivalent to a quantitative representation of the impact of sludge sloshing on vehicle dynamics. Step S3 is equivalent to separating the disturbance caused by sludge sloshing from the total vehicle dynamic response. Step S4 refers to formulating and executing corresponding vehicle control instructions based on the sludge sloshing disturbance information and the total mass information of the vehicle evaluated in step S3. Step S4 can be implemented by formulating and executing corresponding vehicle control strategies based on the sludge sloshing disturbance information and the total mass information of the vehicle. For example, the torque output of the motor, the degree of intervention of the braking system, the power assist of the steering system or the damping characteristics of the suspension system are adjusted according to the degree and mode of the sludge sloshing. The vehicle control strategy can be rule-based, fuzzy control, model predictive control (MPC) or adaptive control.

[0032] The core innovation of this application lies in separating and quantifying the dynamic disturbance caused by sludge shaking by evaluating the degree of dynamic disturbance caused by sludge shaking based on the dynamic characteristics of the deviation between the actual dynamic response and the expected dynamic response calculated without sludge disturbance over time. That is, this application can effectively separate the signal from the vehicle itself in response to the driver's command and the disturbance signal caused by sludge shaking. Therefore, this application can effectively solve the problem of incorrect vehicle control and insufficient accuracy and reliability of parameter control due to the inability to distinguish between the acceleration of the vehicle itself in response to the driver's command and the disturbance acceleration caused by sludge shaking, thereby effectively improving driving safety and driving experience.

[0033] Specifically, the method first obtains key data during vehicle operation, including the driver's control inputs (such as acceleration, braking, and steering), the vehicle's actual motion state (such as acceleration and angular velocity), the vehicle's current speed, and the vehicle's total weight. These data comprehensively reflect the vehicle's current operating conditions and the driver's driving intentions. Next, a preset vehicle model is used to calculate the dynamic response that the vehicle should theoretically produce in the absence of sludge sloshing interference based on the acquired driver operation information, current speed information, and vehicle total mass information. This expected dynamic response provides an ideal benchmark. The actual dynamic response of the vehicle is then compared with the expected dynamic response. If there is a difference between the two, it is assumed that the difference is primarily due to sludge sloshing within the tank. The sludge disturbance assessment result is obtained by analyzing the dynamic characteristics of the deviation signal between the actual response and the expected response over time, such as analyzing its frequency component and amplitude change rate, to assess the degree and pattern of sludge sloshing. This process can effectively separate the dynamic disturbance superimposed signal generated by sludge sloshing, thereby overcoming the signal aliasing problem in the prior art. Finally, an optimized control strategy that can effectively suppress the current sludge swaying effect is determined based on the sludge disturbance assessment results and the vehicle's gross mass information. For example, if the assessment results show that there is a large lateral sway disturbance, the control strategy may adjust the differential braking or steering assist to enhance lateral stability; if there is a large longitudinal sway disturbance, the motor's torque output or the distribution of the braking force may be adjusted to smooth the longitudinal impact. Since this embodiment takes the vehicle's gross mass information into consideration when determining the target control strategy, it can adapt the target control strategy to the vehicle's current load conditions. Then, according to the determined target control strategy, the drive, braking, steering, or suspension system of the pure electric sludge transport vehicle is precisely regulated, thereby improving the vehicle's driving stability, safety, and driving comfort during sludge transportation. Compared with the problem of erroneous control caused by the inability to distinguish the signal source in the existing technology, this solution can accurately identify sludge disturbances and perform targeted regulation based on them, significantly improving the accuracy and reliability of vehicle control.

[0034] As a preferred embodiment, the solution of the present application is specifically implemented as follows: the driver operation information can be provided by the accelerator pedal position sensor, the brake pedal pressure sensor and the steering wheel angle sensor. The actual dynamic response information can be provided by the inertial measurement unit installed on the vehicle, including longitudinal acceleration, lateral acceleration and yaw angular velocity. The current speed information is provided by the speed sensor. The total vehicle mass information can be estimated by the on-board weighing system or based on the load and consumption, and this information is collected into the vehicle control system through the vehicle communication network. The expected dynamic response information can be calculated by the running vehicle dynamics model in the vehicle control system. The model can predict the dynamic response of the pure electric sludge transport vehicle in the absence of sludge disturbance based on the input driver operation information, current speed and total vehicle mass, and output the corresponding expected dynamic response information. The disturbance assessment can be implemented by software in the vehicle control unit. Specifically, the sludge disturbance assessment result is obtained by comparing the deviation between the actual dynamic response and the expected dynamic response and analyzing its dynamic characteristics, for example, using a Kalman filter or a frequency analysis method to estimate the amplitude and pattern of the sludge shaking. Vehicle control can be implemented in the vehicle control unit, which determines the control instructions (such as adjusting the driving force or braking force) for the vehicle actuators (such as the drive motor, braking system, and suspension system) based on the sludge disturbance assessment results and the total vehicle mass, and then controls the pure electric sludge transporter according to these control instructions.

[0035] In some of the above-mentioned embodiments of the present application, it is proposed that when the expected dynamic response information is different from the actual dynamic response information, the degree of dynamic disturbance caused by sludge sloshing is evaluated based on the dynamic characteristics of the deviation between the actual dynamic response information and the expected dynamic response information over time. The evaluation can be specifically performed by analyzing the difference between the actual dynamic response of the vehicle, such as the longitudinal acceleration, lateral acceleration and yaw rate, and the expected dynamic response calculated based on the driver's operation, speed and total vehicle mass. For example, the existence of sludge sloshing and its approximate intensity are judged by calculating the root mean square value, peak value or amplitude of a specific frequency component of the deviation, so as to perceive the impact of sludge sloshing on the vehicle dynamics (sludge disturbance evaluation result). However, relying solely on the deviation of the vehicle's dynamic response may not fully and accurately reflect the actual situation of sludge sloshing. The characteristics of the sludge itself and the changes during transportation will also significantly affect the sludge sloshing pattern and intensity, resulting in deviations in the evaluation results, which in turn affects the accuracy and reliability of the subsequent control strategy.

[0036] In order to solve this technical problem, in some preferred embodiments, step S3 includes:

[0037] S31. When the expected dynamic response information is different from the actual dynamic response information, evaluating the degree of dynamic disturbance caused by the sludge sloshing according to the dynamic characteristics of the deviation between the actual dynamic response information and the expected dynamic response information over time, to obtain a first preliminary disturbance assessment result.

[0038] S32. Obtaining preset sludge characteristic information, transportation condition information, and transportation duration information, where the preset sludge characteristic information is information obtained by measuring the characteristics of the sludge loaded on the pure electric sludge transport vehicle before starting transportation;

[0039] S33, analyzing and obtaining current sludge characteristic information based on preset sludge characteristic information, transportation condition information, and transportation duration information;

[0040] S34. Correct the first preliminary disturbance assessment result according to the current sludge characteristic information to obtain a sludge disturbance assessment result.

[0041] Preset sludge characteristic information refers to data obtained by measuring the physical or chemical properties of the sludge sample to be loaded before the transportation mission begins. In this embodiment, the preset sludge characteristic information can be obtained through laboratory analysis, portable sensor measurement, etc. This preset sludge characteristic information can characterize the inherent properties of the sludge in its initial state, such as density and viscosity. Transportation condition information refers to external environmental and vehicle operating status data that affect the sludge state or sway during transportation. This information may include road conditions (such as flatness and slope), ambient temperature, vehicle speed, acceleration and deceleration, and steering angular velocity. This information can be obtained from vehicle sensors, GPS systems, or external data sources. Transportation duration information refers to the time elapsed from the start of sludge loading to the current moment. This information can be recorded and calculated by the vehicle's internal timer or system timestamp. This transportation duration information is used to reflect the possibility of the sludge experiencing cumulative effects over time within the tank. Current sludge characteristic information refers to the inferred physical and chemical properties of the sludge in the tank under the current driving state of the vehicle. This embodiment can obtain the current sludge characteristic information based on the preset sludge characteristic information, transportation condition information, and transportation duration information through model calculation, table lookup, or analysis based on preset characteristic change rules. The current sludge characteristic information can characterize the changes in the properties of the sludge that may occur at the current moment (for example, changes in viscosity caused by high-temperature transportation). The first preliminary disturbance assessment result refers to a preliminary judgment result on the degree of dynamic disturbance caused by sludge sloshing based solely on the dynamic characteristics of the vehicle's dynamic response deviation changing over time. The first preliminary disturbance assessment result can be expressed as a numerical value, a grade, or a descriptive indicator. The sludge disturbance assessment result refers to the final assessment result obtained after correcting the first preliminary disturbance assessment result, which more accurately reflects the actual disturbance degree of sludge sloshing. It may include information such as the degree of sludge sloshing disturbance and the sludge sloshing pattern.

[0042] The technical solution of the present application forms a more comprehensive and accurate sludge disturbance assessment mechanism by combining the preliminary disturbance assessment based on the deviation of the vehicle's dynamic response with the analysis based on the characteristics of the sludge itself and its changes during transportation. Specifically, step S31 first evaluates the degree of dynamic disturbance caused by sludge swaying according to the dynamic characteristics of the deviation between the actual dynamic response information and the expected dynamic response information over time, so as to obtain a first preliminary disturbance assessment result. This preliminary result reflects the direct impact of sludge swaying on vehicle dynamics. However, the degree of influence of sludge swaying on vehicle dynamics depends not only on the swaying itself, but is also closely related to the physical properties of the sludge and external factors during transportation. Therefore, step S32 further obtains preset sludge characteristic information, transportation condition information and transportation duration information. This information provides basic data for understanding the internal causes and changing laws of sludge swaying. Specifically, the preset sludge characteristic information provides the original state attributes of the sludge, and the transportation condition information and transportation duration information reflect the environmental impact and time accumulation effect that the sludge may experience during transportation. Step S33 infers the actual characteristics of the sludge at the current moment, such as its current viscosity, density, or stratification, by analyzing preset sludge characteristic information, transportation condition information, and transportation duration information. The current characteristics of the sludge directly affect the severity and pattern of its sloshing. Finally, step S34 uses the current sludge characteristic information obtained in step S33 to correct the first preliminary disturbance assessment result obtained in step S31. This correction process takes into account the weight or pattern of the impact of the current sludge state on the vehicle dynamic response deviation. For example, if the current sludge viscosity is low, even if the vehicle dynamic response deviation is not large, the actual sloshing disturbance may be stronger, and the correction process will increase the assessment result. Conversely, if the sludge viscosity is high and the sloshing is relatively mild, the correction process may decrease the assessment result. This embodiment is equivalent to fusing the vehicle dynamic response data with the sludge's own characteristic data, so that the final sludge disturbance assessment result can more realistically and accurately reflect the actual disturbance level of sludge sloshing, thereby effectively overcoming the assessment bias that may be caused by relying solely on the vehicle dynamic response, and thus providing reliable input for the subsequent determination of a more accurate vehicle control strategy.

[0043] In one embodiment, the specific process of sludge disturbance assessment can be implemented as follows: In step S31, the root mean square value and dominant frequency of the deviation between the actual dynamic response information and the expected dynamic response information within a time window are used as the first preliminary disturbance assessment result. In step S32, the preset sludge characteristic information can be obtained by sampling and measuring the sludge viscosity and density using a viscometer, densitometer, or other equipment before loading. Transportation condition information can be obtained by obtaining current speed, acceleration, steering angle, and other data via the vehicle's CAN bus, combined with GPS data to obtain road slope information. Transportation duration information can be recorded by a system-activated timer. In step S33, a sludge characteristic change model can be established. This model uses the preset sludge characteristic information, transportation condition information (e.g., temperature, vibration intensity), and transportation duration information as inputs, and calculates current sludge characteristic information such as density, viscosity, and solid content using a preset algorithm (e.g., a model that considers the impact of temperature on viscosity and the stratification model that may result from long transportation). In step S34, a correction function or table lookup mechanism is established. This function or mechanism takes the first preliminary disturbance assessment result and current sludge characteristic information (such as current viscosity) as input and outputs a corrected sludge disturbance assessment result. For example, if the current sludge viscosity is lower than a preset value, the correction function can proportionally increase the value of the first preliminary disturbance assessment result based on the degree of viscosity reduction, thereby obtaining a sludge disturbance assessment result that is more consistent with the actual situation. This embodiment can more accurately assess the degree of dynamic disturbance caused by sludge sloshing by combining the vehicle dynamic response deviation with the sludge's own characteristics and their changes during transportation. This overcomes the limitations of relying solely on vehicle dynamic response to assess disturbances and avoids misjudging signals caused by sludge sloshing as signals caused by driver commands. Therefore, this embodiment can obtain a sludge disturbance assessment result that is closer to the actual situation, providing a reliable basis for subsequent determination of the target control strategy, helping the vehicle control system to more accurately identify and respond to disturbances caused by sludge sloshing and avoid erroneous control interventions, thereby improving the driving safety and driving experience of the pure electric sludge transporter.

[0044] However, the disturbance caused by sludge sloshing is not only related to the characteristics of the sludge itself, but may also be affected by the internal state of the transport tank, such as attachments inside the tank. These factors may change the sludge sloshing pattern or degree, resulting in errors in the disturbance assessment results based only on sludge characteristics correction, affecting the accuracy of subsequent control.

[0045] In order to solve this technical problem, in some preferred embodiments, step S34 includes:

[0046] S341. Correcting the first preliminary disturbance assessment result according to the current sludge characteristic information to obtain a second preliminary disturbance assessment result;

[0047] S342: Acquire preset internal state information of the tank, where the preset internal state information of the tank is information obtained by detecting the state of the interior of the tank of the pure electric sludge transport vehicle before loading the sludge;

[0048] S343. Correct the second preliminary disturbance assessment result according to the preset tank internal state information to obtain a sludge disturbance assessment result.

[0049] The preset tank internal state information refers to information obtained by inspecting the interior of the tank of the pure electric sludge transport vehicle before loading the sludge. Specifically, this embodiment uses visual inspection, laser scanning, and ultrasonic inspection technologies to inspect the interior of the tank of the pure electric sludge transport vehicle. This embodiment can obtain the actual condition of the internal surface of the tank (especially whether there are attachments, the distribution location, approximate shape, and possible thickness or volume of the attachments) by inspecting the interior of the tank of the pure electric sludge transport vehicle before loading the sludge. The preset tank internal state information is pre-acquired and stored. This embodiment can take into account the potential impact of the non-ideal state of the tank interior on the sludge sloshing behavior in the sludge disturbance assessment by using the preset tank internal state information to correct the second preliminary disturbance assessment result. For example, attachments may change the effective volume, surface friction characteristics, or reflection pattern of the sloshing wave inside the tank, thereby more comprehensively reflecting the actual sloshing situation.

[0050] Based on the above technical solution, the sludge disturbance assessment process is refined into a multi-stage correction process. First, a preliminary disturbance assessment result is obtained based on the dynamic characteristics of the vehicle's dynamic response deviation over time. Based on this, a first correction is made to this preliminary disturbance assessment result using current sludge characteristics (such as density, viscosity, or solids content) to obtain a second preliminary disturbance assessment result. This correction stage takes into account the impact of the sludge's physical properties on the sloshing pattern and degree. Furthermore, preset tank internal state information is introduced to reflect non-ideal factors such as possible attachments inside the tank. These non-ideal factors will affect the flow and shaking behavior of the sludge in the tank. Therefore, this embodiment can make a second correction to the second preliminary disturbance assessment result according to the preset tank internal state information so that the final sludge disturbance assessment result not only takes into account the characteristics of the sludge itself, but also takes into account the influence of the internal state of the tank on the shaking, so that the sludge disturbance assessment result is closer to the actual situation. That is, this embodiment is equivalent to superimposing the consideration of the internal state of the tank on the basic disturbance assessment and the correction based on the sludge characteristics, so as to form a more refined and comprehensive evaluation mechanism and provide a more accurate basis for the subsequent determination of the vehicle control strategy.

[0051] As a specific embodiment, when conducting a sludge disturbance assessment, a preset correction model or algorithm is first used to correct the preliminary assessment result based on the dynamic characteristics of the deviation between the actual dynamic response of the vehicle and the expected dynamic response, combined with current sludge characteristic information, to obtain an intermediate assessment result (a second preliminary disturbance assessment result). For example, the model can adjust the estimate of slosh damping based on the current viscosity of the sludge, thereby correcting the disturbance amplitude of the preliminary assessment. Subsequently, data on the distribution of deposits inside the tank body obtained by laser scanning before loading the sludge is obtained. This data can include information such as the location coordinates, estimated thickness or volume of the deposits. Finally, another correction model or table lookup is used to further correct the intermediate assessment result using this deposit data. For example, if the deposits are concentrated in specific areas on the bottom or side walls of the tank body, the correction model can predict the impact of the deposits on the propagation or energy dissipation of the sludge slosh wave based on their distribution and volume, and adjust the intermediate assessment result accordingly, ultimately outputting a more accurate sludge disturbance assessment result. This embodiment is equivalent to correcting the preliminary disturbance assessment results according to the sludge characteristic information, further considering the influence of the internal state of the tank on the sludge sloshing, and re-correcting the corrected results based on the preset internal state information of the tank. Therefore, the sludge disturbance assessment results obtained in this embodiment can more comprehensively reflect the actual sludge sloshing situation, so as to effectively improve the accuracy of the sludge disturbance assessment, thereby providing more reliable input for the subsequent determination of the target control strategy and helping to improve the driving stability and safety of the pure electric sludge transport vehicle under the influence of sludge sloshing.

[0052] In some preferred embodiments, step S343 includes:

[0053] A1. Correcting the second preliminary disturbance assessment result according to preset tank internal state information to obtain a third preliminary disturbance assessment result;

[0054] A2. Obtain tank loading status;

[0055] A3. Correct the third preliminary disturbance assessment result according to the tank loading condition to obtain a sludge disturbance assessment result.

[0056] The tank loading condition refers to the actual filling state of the sludge in the tank (such as the actual liquid level, filling rate and distribution state of the sludge). In this embodiment, the tank loading condition can be obtained by using a liquid level sensor, a pressure sensor, an ultrasonic sensor, image recognition technology or an estimation algorithm based on the vehicle motion state.

[0057] The sludge disturbance assessment method of this embodiment realizes its function in the following manner: First, the second preliminary disturbance assessment result is corrected according to the preset internal state information of the tank to obtain a third preliminary disturbance assessment result. This step uses the fixed physical factors inside the tank to adjust the second preliminary assessment result, taking into account the influence of these fixed physical factors on the sludge sloshing pattern and energy dissipation. Subsequently, the current tank loading condition (such as the actual liquid level or filling rate of the sludge) is obtained. The actual filling state of the sludge in the tank is a key dynamic factor affecting its sloshing behavior. This filling state will affect the degrees of freedom, pattern and interaction with the internal structure of the tank. Then, the third preliminary disturbance assessment result is corrected again according to the obtained tank loading condition to obtain the final sludge disturbance assessment result. This embodiment can more comprehensively consider various factors affecting sludge sloshing by combining the current characteristics of the sludge, the preset internal state information of the tank and the actual tank loading conditions for step-by-step correction, so as to obtain a sludge disturbance assessment result that is closer to the actual situation. That is, this embodiment can dynamically correct the disturbance assessment result determined based on the dynamic characteristics of the dynamic response deviation by utilizing multiple factors so that the assessment result can more accurately reflect the actual state and degree of sludge sloshing at the current moment, thereby providing more reliable input for subsequent vehicle control.

[0058] To more specifically illustrate the technical solution of this application, the following example provides a method: Assume that the second preliminary disturbance assessment result is a numerical value representing the vehicle yaw moment caused by sludge sloshing. First, a preset correction model is used to correct this yaw moment value based on preset tank internal state information to obtain a third preliminary disturbance assessment result. For example, if there is a certain thickness of attachment at the bottom of the tank, this attachment may have a damping effect on low-speed sloshing, and therefore the yaw moment value of the second preliminary disturbance assessment result needs to be reduced. Next, an ultrasonic sensor installed on the top of the tank is used to obtain the current sludge liquid level, and this liquid level is used as the tank loading condition. Finally, a correction factor lookup table based on the liquid level height is queried based on the obtained liquid level height to obtain the corresponding correction factor. The third preliminary disturbance assessment result is then corrected by multiplying the third preliminary disturbance assessment result by the correction factor. For example, when the liquid level is at the middle position of the tank height, the sludge swaying is most violent, and the correction factor is 1.5 (equivalent to increasing the yaw moment value of the third preliminary disturbance assessment result); when the liquid level is at 4 / 5 of the tank height, the sludge swaying is relatively mild, and the correction factor is 1.1. This embodiment can, by further introducing consideration of the tank loading condition and making corrections based on the preliminary disturbance assessment result based on the preset tank internal state information, enable the sludge disturbance assessment result to more accurately reflect the sludge swaying pattern and degree in the actual filling state. Therefore, this embodiment can further improve the accuracy of the sludge disturbance assessment result, so that the vehicle control strategy subsequently determined based on this information can more effectively deal with the adverse effects of sludge swaying, thereby improving the stability and safety of the pure electric sludge transport vehicle during driving.

[0059] In some preferred embodiments, the preset internal state information of the tank body includes the attachment distribution information and the thickness and size corresponding to each attachment, and the current sludge characteristic information includes the current density of the sludge, the current viscosity of the sludge and the current solid content of the sludge. The attachment distribution information refers to the spatial position and arrangement of the attachments on the internal wall of the tank body, which can be implemented using three-dimensional coordinate data, an area division map or an attachment list. Thickness and size refer to the physical measurements of each attachment in space, which can be represented by parameters such as length, width, and height. The current density of the sludge refers to the mass of the sludge per unit volume at the current moment, which can be measured using a density sensor or obtained by calculation. The current viscosity of the sludge refers to the property of the sludge to resist flow at the current moment, which can be measured using a viscometer or estimated through a rheological model. The current solid content of the sludge refers to the proportion of solid matter in the total mass or total volume of the sludge at the current moment, which can be measured using a solid content sensor or obtained through drying analysis. Since the preset internal state information of the tank body in this embodiment includes the distribution information of attachments and the thickness and size corresponding to each attachment, this information can reflect the actual condition of the internal wall of the tank body (for example, whether there is sludge residue or agglomeration (attachments) and the spatial distribution and physical size of these attachments). The distribution, thickness and size of these attachments will change the effective volume and shape inside the tank body and affect the flow and sludge shaking pattern in the tank body. Therefore, this embodiment can obtain and utilize this detailed attachment information to more accurately consider the impact of the internal state of the tank body on sludge shaking when correcting the preliminary disturbance assessment results. At the same time, since the current sludge characteristic information of this embodiment includes the current density of the sludge, the current viscosity of the sludge and the current solid content of the sludge, which are key parameters for describing the physical properties of the sludge, and the density of the sludge affects its mass distribution and inertia, the viscosity affects the resistance and speed of the sludge flow, and the solid content is closely related to the fluidity and shaking intensity of the sludge, these sludge characteristic parameters will directly affect the shaking amplitude and frequency of the sludge during the dynamic process of the vehicle. Therefore, this embodiment can obtain and utilize these specific sludge characteristic information to more accurately quantify the impact of the properties of the sludge itself on the shaking disturbance when correcting the preliminary disturbance assessment results.

[0060] In some preferred embodiments, step S4 includes:

[0061] S41. Determine a preliminary control strategy based on the sludge disturbance assessment results and the vehicle gross mass information;

[0062] S42, obtaining road condition information of the current driving section of the pure electric sludge transport vehicle;

[0063] S43, adjusting the preliminary control strategy according to the road condition information to obtain a target control strategy;

[0064] S44. Control the pure electric sludge transport vehicle according to the target control strategy.

[0065] The preliminary control strategy in this embodiment refers to a set of vehicle control parameters or control instructions obtained through preliminary calculation or table lookup based on two primary factors: the degree of sludge disturbance and the vehicle's gross mass. Road condition information in this embodiment refers to data describing the physical characteristics of the road section the vehicle is currently traveling on (e.g., road surface smoothness, friction coefficient, slope, and bend radius). This embodiment can utilize onboard sensors (such as accelerometers, gyroscopes, and cameras) or combine the vehicle's current location with high-precision map data to obtain road condition information for the section the all-electric sludge transport vehicle is currently traveling on. Adjusting the preliminary control strategy based on road condition information in this embodiment refers to the process of modifying, optimizing, or switching the parameters or instructions in the preliminary control strategy based on the acquired road condition information to better adapt it to the current actual driving environment. The target control strategy refers to the set of control parameters or control instructions ultimately used to control the vehicle's actuators (e.g., motor, brakes, and suspension system) after adjustment based on road condition information.

[0066] This solution refines the process of determining the target control strategy and performing control. First, a preliminary control strategy is determined based on the sludge disturbance assessment results and the vehicle's total mass information. Subsequently, the road condition information of the current driving section of the pure electric sludge transport vehicle is obtained, and the road condition information reflects the actual driving environment of the vehicle. Then, the preliminary control strategy is adjusted according to the obtained road condition information to obtain the final target control strategy, which means that the target control strategy is corrected and optimized based on the actual road conditions, that is, this embodiment is equivalent to using the road condition information to adjust the preliminary strategy so that the final target control strategy is more in line with the actual driving environment, thereby improving the accuracy and effectiveness of the control. Finally, the pure electric sludge transport vehicle is controlled according to the target control strategy adjusted by the road condition information. This optimized control strategy can more effectively deal with the disturbance caused by sludge shaking and take into account the driving requirements under different road conditions, thereby improving the vehicle's driving safety, stability and driving comfort. This embodiment can generate a control strategy that is more adapted to the actual driving environment by introducing road condition information into the process of determining the control strategy, thereby improving the robustness and effectiveness of vehicle driving feedback regulation, and effectively solving the problem that sludge disturbance and vehicle gross mass information alone cannot fully cope with complex road conditions.

[0067] In one embodiment, determining a preliminary control strategy based on sludge disturbance assessment results and vehicle gross mass information can be accomplished by consulting a pre-set multidimensional lookup table. The table's input dimensions include the degree of sludge sloshing (e.g., mild, moderate, severe) and the vehicle's gross mass range (e.g., unloaded, half-loaded, fully loaded), and its output is a set of basic suspension damping coefficients and drive / brake response gains. Obtaining road condition information for the pure electric sludge transporter's current travel section can be accomplished through onboard sensor fusion. For example, accelerometer and gyroscope data can be used to analyze road surface bumps, GPS and electronic map data can be used to determine the slope and curvature of the current road section, and cameras can be used to identify road surface type (e.g., asphalt, cement, or unpaved). Adjusting the initial control strategy based on road condition information can be implemented through a fuzzy logic controller. The controller's inputs are the initial control strategy parameters and road condition information (e.g., road bump level, slope value, bend radius), and its output is an adjustment factor. These adjustment factors are applied to the initial control strategy parameters. For example, when a bumpy road is detected, the suspension damping coefficient is increased; when an uphill slope is detected, the drive response gain is appropriately increased; when a sharp bend is detected, the drive / brake response gain is reduced and the suspension roll stiffness is adjusted. Controlling the pure electric sludge transporter according to the target control strategy can be achieved by sending the adjusted suspension damping coefficient, drive response gain, and brake response gain to the vehicle's electronic control unit (ECU). The ECU then controls the corresponding actuators (e.g., the active suspension system, motor controller, and electronic braking system) to adjust the vehicle's dynamics. This embodiment can generate a more refined and adaptive target control strategy by determining a preliminary control strategy based on the sludge disturbance assessment results and the vehicle's total mass information, and further adjusting the preliminary strategy based on the road condition information of the current driving section. This comprehensive control strategy that combines the vehicle's internal state (sludge disturbance, total mass) and external environment (road conditions) can more effectively cope with the complex dynamic effects of sludge swaying under different road conditions. Therefore, this embodiment can effectively improve the robustness and accuracy of the vehicle control system, so that the pure electric sludge transport vehicle can maintain better driving stability, safety and driving comfort under various driving conditions, thereby effectively solving the problem of poor control effect caused by relying solely on sludge disturbance and total mass information and being unable to fully adapt to complex road conditions.

[0068] In some preferred embodiments, step S2 includes:

[0069] S21. Obtaining road condition information of the current driving section of the suspension system performance of the pure electric sludge transport vehicle;

[0070] S22. Obtaining expected dynamic response information of the pure electric sludge transport vehicle in the absence of sludge disturbance based on driver operation information, current speed information, vehicle gross mass information, suspension system performance, and road condition information.

[0071] The suspension system performance of this embodiment refers to the characteristics of the vehicle suspension system in supporting the vehicle body, absorbing road impact, and maintaining tire-to-ground contact. This performance can be characterized by parameters such as suspension system stiffness, damping, unsprung mass, sprung mass, and suspension geometry (e.g., kingpin inclination, camber, and toe angle). These parameters can be obtained using factory calibration data, sensor measurements during vehicle operation (e.g., suspension travel sensors and acceleration sensors), or estimation using a vehicle dynamics model. The process for acquiring road condition information in this embodiment is preferably the same as that for the above-described embodiment and will not be discussed in detail here.

[0072] Since the performance of the suspension system directly determines the dynamic response characteristics of the vehicle to road input and driver operation, different suspension adjustments will cause the vehicle to exhibit different vibration, roll and pitch characteristics under the same conditions, and the road condition information reflects the impact of the external environment on the vehicle dynamics. For example, on bumpy roads, even if the driver maintains stable operation, the vehicle will produce significant vertical and longitudinal vibrations; when driving on a curve, the vehicle will produce lateral acceleration and yaw angular velocity. Therefore, this embodiment can combine these key internal (suspension system performance) and external (road condition information) factors with driver operation information, current speed information and vehicle The method of using the vehicle gross mass information together as the input for calculating the expected dynamic response information of the vehicle in the absence of sludge disturbance enables the expected dynamic response information to more accurately reflect the ideal dynamic behavior of the vehicle under the current actual driving conditions. Therefore, this embodiment can more effectively separate the deviation caused by sludge shaking by comparing this more accurate expected dynamic response information with the actual dynamic response information of the vehicle, thereby improving the accuracy of subsequent sludge disturbance assessment, laying a more solid foundation for the entire driving feedback optimization and control method, and enabling subsequent disturbance assessment and control strategies to be more accurately optimized for the impact of sludge shaking.

[0073] In a specific embodiment, step S21 can be implemented as follows: the vehicle's suspension system performance parameters (e.g., shock absorber damping coefficient and spring stiffness) are read from the vehicle's electronic control unit (ECU). Simultaneously, road condition information for the current driving section is obtained through onboard sensor fusion (e.g., using an accelerometer and gyroscope mounted on the vehicle body to measure vehicle vibration and posture changes, combined with vehicle speed information, to estimate the road surface smoothness in real time through an algorithm; using an onboard camera to identify road markings and obstacles, and combining GPS data and electronic map information to determine the road curvature and slope). Step S22 can be implemented using a vehicle simulation model based on a multi-body dynamics model. The simulation model uses the driver's accelerator pedal opening, brake pedal opening, and steering wheel angle as control inputs, and simultaneously inputs the suspension system performance parameters and road condition information obtained from S21, as well as the vehicle's current actual speed and total mass. The simulation model calculates and outputs the vehicle's desired dynamic response information, such as the ideal longitudinal acceleration, lateral acceleration, and yaw rate, in real time based on these input parameters when there is no sludge sloshing interference. For example, when the vehicle enters a curve with a known curvature at a certain speed, the model predicts the vehicle's desired lateral acceleration and yaw rate when there is no sludge sloshing based on the curvature, current speed, total vehicle mass, suspension system characteristics, and road adhesion conditions. This embodiment can, by additionally considering the vehicle's suspension system performance and the road condition information of the current driving section when obtaining the desired dynamic response information of the pure electric sludge transport vehicle in the absence of sludge disturbance, enable the predicted expected dynamic response information to more accurately reflect the vehicle's ideal motion state under the current actual driving conditions, thereby effectively improving the accuracy of the expected dynamic response prediction.

[0074] In some preferred embodiments, the driver operation information includes the accelerator pedal opening, the brake pedal opening and the steering wheel angle, and the actual dynamic response information includes the longitudinal acceleration, the lateral acceleration and the yaw angular velocity. The driver operation information of this embodiment includes the accelerator pedal opening, the brake pedal opening and the steering wheel angle. These parameters are key input signals reflecting the driver's longitudinal acceleration, deceleration and lateral steering control of the vehicle. This embodiment can more accurately predict the expected longitudinal and lateral dynamic responses of the vehicle in the absence of sludge shaking disturbance based on these specific driver operation information. The actual dynamic response information of this embodiment includes the longitudinal acceleration, the lateral acceleration and the yaw angular velocity. The longitudinal acceleration describes the acceleration or deceleration of the vehicle in the direction of travel, the lateral acceleration describes the force and movement of the vehicle in the lateral direction, and the yaw angular velocity describes the rotation speed of the vehicle around the vertical axis. These parameters can more comprehensively capture the actual dynamic behavior of the vehicle under the action of internal and external forces such as driver operation and sludge shaking.

[0075] In some preferred embodiments, the sludge disturbance assessment results include the degree of sludge sloshing and the sludge sloshing pattern. The degree of sludge sloshing refers to the magnitude or intensity of the disturbance caused by sludge sloshing on vehicle dynamics, which can be quantified using indicators such as the amplitude, energy, or root mean square value of the deviation signal. The sludge sloshing pattern refers to the specific form, direction, or type of sludge sloshing, which can be achieved by performing spectral analysis, principal component analysis, or pattern recognition based on machine learning algorithms on the deviation signal.

[0076] From the above, it can be seen that the driving feedback optimization and control method of a pure electric sludge transport vehicle provided in the present application can separate and quantify the dynamic disturbance caused by sludge shaking by evaluating the degree of dynamic disturbance caused by sludge shaking according to the dynamic characteristics of the deviation between the actual dynamic response and the expected dynamic response calculated without sludge disturbance over time. That is, the present application can effectively separate the signal from the vehicle itself in response to the driver's command and the disturbance signal caused by sludge shaking. Therefore, the present application can effectively solve the problem of incorrect vehicle control due to the inability to distinguish between the acceleration of the vehicle itself in response to the driver's command and the disturbance acceleration caused by sludge shaking, and the problem of insufficient accuracy and reliability of parameter control, thereby effectively improving driving safety and driving experience.

[0077] Second, as Figure 2 As shown, the present application also provides a driving feedback optimization and control system for a pure electric sludge transport vehicle, which includes:

[0078] Information acquisition module 1, used to obtain driver operation information, actual dynamic response information, current speed information and vehicle gross mass information of the pure electric sludge transport vehicle;

[0079] Expected dynamic response acquisition module 2, used to obtain expected dynamic response information of the pure electric sludge transport vehicle in the absence of sludge disturbance based on driver operation information, current speed information and vehicle gross mass information;

[0080] The disturbance assessment module 3 is used to assess the degree of dynamic disturbance caused by sludge sloshing according to the dynamic characteristics of the deviation between the actual dynamic response information and the expected dynamic response information over time when the expected dynamic response information is different from the actual dynamic response information, so as to obtain a sludge disturbance assessment result;

[0081] The vehicle control module 4 is used to determine a target control strategy based on the sludge disturbance assessment result and the vehicle gross mass information, and then control the pure electric sludge transport vehicle according to the target control strategy.

[0082] The present application provides a pure electric sludge transport vehicle driving feedback optimization and control system, which includes an information acquisition module 1, an expected dynamic response acquisition module 2, a disturbance assessment module 3, and a vehicle control module 4. The pure electric sludge transport vehicle driving feedback optimization and control system provided in this embodiment is used to execute the steps in the pure electric sludge transport vehicle driving feedback optimization and control method provided in the first aspect above. The principle of the pure electric sludge transport vehicle driving feedback optimization and control system provided in this embodiment is the same as the principle of the pure electric sludge transport vehicle driving feedback optimization and control method provided in the first aspect above, and will not be discussed in detail here.

[0083] From the above, it can be seen that the present application provides a driving feedback optimization and control method and system for a pure electric sludge transport vehicle, which can separate and quantify the dynamic disturbance caused by sludge shaking by evaluating the degree of dynamic disturbance caused by sludge shaking based on the dynamic characteristics of the deviation between the actual dynamic response and the expected dynamic response calculated without sludge disturbance over time. That is, the present application can effectively separate the signal from the vehicle itself in response to the driver's command and the disturbance signal caused by sludge shaking. Therefore, the present application can effectively solve the problem of incorrect vehicle control due to the inability to distinguish between the acceleration of the vehicle itself in response to the driver's command and the disturbance acceleration caused by sludge shaking, and the problem of insufficient accuracy and reliability of parameter control, thereby effectively improving driving safety and driving experience.

[0084] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the above-mentioned units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another robot, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interface, the indirect coupling or communication connection of the device or unit can be electrical, mechanical or other forms.

[0085] In addition, the functional modules in each embodiment of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0086] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any actual relationship or order between these entities or operations.

[0087] The above description is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, various modifications and variations of the present application are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A driving feedback optimization control method for a pure electric sludge transport vehicle, characterized in that: The driving feedback optimization and control method of the pure electric sludge transport vehicle comprises the following steps: S1. Obtaining driver operation information, actual dynamic response information, current speed information, and vehicle gross mass information of the pure electric sludge transport vehicle; S2. Obtaining expected dynamic response information of the pure electric sludge transport vehicle in the absence of sludge disturbance based on the driver operation information, the current speed information, and the vehicle gross mass information; S3. When the expected dynamic response information is different from the actual dynamic response information, evaluating the degree of dynamic disturbance caused by sludge sloshing according to the dynamic characteristics of the deviation between the actual dynamic response information and the expected dynamic response information over time, so as to obtain a sludge disturbance assessment result; S4. determining a target control strategy based on the sludge disturbance assessment result and the vehicle gross mass information, and then controlling the pure electric sludge transport vehicle according to the target control strategy; Step S3 includes: S31. When the expected dynamic response information is different from the actual dynamic response information, evaluating the degree of dynamic disturbance caused by sludge sloshing according to the dynamic characteristics of the deviation between the actual dynamic response information and the expected dynamic response information over time, to obtain a first preliminary disturbance assessment result. S32. Obtaining preset sludge characteristic information, transportation condition information, and transportation duration information, wherein the preset sludge characteristic information is information obtained by measuring the characteristics of the sludge loaded on the pure electric sludge transport vehicle before starting transportation; S33, analyzing and obtaining current sludge characteristic information based on the preset sludge characteristic information, transportation condition information, and transportation duration information; S34. Correcting the first preliminary disturbance assessment result according to the current sludge characteristic information to obtain a sludge disturbance assessment result; Step S34 includes: S341. Correcting the first preliminary disturbance assessment result according to the current sludge characteristic information to obtain a second preliminary disturbance assessment result. S342: Acquire preset internal state information of the tank, wherein the preset internal state information of the tank is information obtained by detecting the state of the interior of the tank of the pure electric sludge transport vehicle before loading the sludge; S343: Correct the second preliminary disturbance assessment result according to the preset tank internal state information to obtain a sludge disturbance assessment result.

2. The driving feedback optimization control method of a pure electric sludge transport vehicle according to claim 1 is characterized in that: Step S343 includes: A1. Correcting the second preliminary disturbance assessment result according to the preset tank internal state information to obtain a third preliminary disturbance assessment result; A2. Obtain tank loading status; A3. Correct the third preliminary disturbance assessment result according to the tank loading condition to obtain a sludge disturbance assessment result.

3. The driving feedback optimization control method of a pure electric sludge transport vehicle according to claim 1 is characterized in that: The preset tank internal state information includes attachment distribution information and thickness and size of each attachment, and the current sludge characteristic information includes current sludge density, current sludge viscosity and current sludge solid content.

4. The driving feedback optimization control method of a pure electric sludge transport vehicle according to claim 1 is characterized in that: Step S4 includes: S41, determining a preliminary control strategy based on the sludge disturbance assessment result and the vehicle gross mass information; S42, obtaining road condition information of the current driving section of the pure electric sludge transport vehicle; S43, adjusting the preliminary control strategy according to the road condition information to obtain a target control strategy; S44. Control the pure electric sludge transport vehicle according to the target control strategy.

5. The driving feedback optimization control method of a pure electric sludge transport vehicle according to claim 1 is characterized in that: Step S2 includes: S21, obtaining road condition information of the current driving section of the suspension system performance of the pure electric sludge transport vehicle; S22. Obtaining expected dynamic response information of the pure electric sludge transport vehicle in the absence of sludge disturbance based on the driver operation information, the current speed information, the vehicle gross mass information, the suspension system performance, and the road condition information.

6. The driving feedback optimization control method of a pure electric sludge transport vehicle according to claim 1 is characterized in that: The driver operation information includes an accelerator pedal opening, a brake pedal opening, and a steering wheel angle, and the actual dynamic response information includes longitudinal acceleration, lateral acceleration, and yaw angular velocity.

7. The driving feedback optimization control method of a pure electric sludge transport vehicle according to claim 1 is characterized in that: The sludge disturbance assessment results include the sludge sloshing disturbance degree and the sludge sloshing mode.

8. A pure electric sludge transport vehicle driving feedback optimization control system, characterized in that: The pure electric sludge transport vehicle driving feedback optimization control system includes: An information acquisition module is used to obtain driver operation information, actual dynamic response information, current speed information and vehicle gross mass information of the pure electric sludge transport vehicle; an expected dynamic response acquisition module, configured to acquire expected dynamic response information of the pure electric sludge transport vehicle in the absence of sludge disturbance based on the driver operation information, the current speed information, and the vehicle gross mass information; a disturbance assessment module, configured to assess the degree of dynamic disturbance caused by sludge sloshing according to the dynamic characteristics of the deviation between the actual dynamic response information and the expected dynamic response information over time when the expected dynamic response information is different from the actual dynamic response information, so as to obtain a sludge disturbance assessment result; a vehicle control module, configured to determine a target control strategy based on the sludge disturbance assessment result and the vehicle gross mass information, and then control the pure electric sludge transport vehicle according to the target control strategy; When the expected dynamic response information is different from the actual dynamic response information, the step of evaluating the degree of dynamic disturbance caused by sludge sloshing according to the dynamic characteristics of the deviation between the actual dynamic response information and the expected dynamic response information over time to obtain a sludge disturbance evaluation result includes: S31. When the expected dynamic response information is different from the actual dynamic response information, evaluating the degree of dynamic disturbance caused by sludge sloshing according to the dynamic characteristics of the deviation between the actual dynamic response information and the expected dynamic response information over time, to obtain a first preliminary disturbance assessment result. S32. Obtaining preset sludge characteristic information, transportation condition information, and transportation duration information, wherein the preset sludge characteristic information is information obtained by measuring the characteristics of the sludge loaded on the pure electric sludge transport vehicle before starting transportation; S33, analyzing and obtaining current sludge characteristic information based on the preset sludge characteristic information, transportation condition information, and transportation duration information; S34. Correcting the first preliminary disturbance assessment result according to the current sludge characteristic information to obtain a sludge disturbance assessment result; Step S34 includes: S341. Correcting the first preliminary disturbance assessment result according to the current sludge characteristic information to obtain a second preliminary disturbance assessment result. S342: Acquire preset internal state information of the tank, wherein the preset internal state information of the tank is information obtained by detecting the state of the interior of the tank of the pure electric sludge transport vehicle before loading the sludge; S343. Correct the second preliminary disturbance assessment result according to the preset tank internal state information to obtain a sludge disturbance assessment result.

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