Rapid measuring system for density of automotive urea

Abstract

The invention relates to the technical field of measurement of physical properties of chemical substances, and particularly discloses an automotive urea density rapid measurement system which comprises a vibration tube type density sensing unit, a multi-mode cooperative driving and signal processing unit, an embedded real-time calculation and compensation unit and a system control and communication interface unit. Wherein the multi-mode cooperative driving and signal processing unit excites a plurality of vibration modes at the same time based on a pre-stored resonance spectrum, and a density initial value is rapidly solved by analyzing frequency deviation of the vibration modes; and the embedded real-time calculation and compensation unit performs multi-physical field real-time compensation of temperature, viscosity and the like on the initial density value by using a neural network model. According to the invention, millisecond-level rapid density measurement and high-precision output are realized, and the real-time regulation and control requirements of the SCR system are met.

Description

Technical Field

[0001] This invention belongs to the field of chemical substance physical property measurement technology, specifically relating to a rapid density determination system for automotive urea. Background Technology

[0002] In the field of diesel engine exhaust aftertreatment, selective catalytic reduction (SCR) technology is the core means of reducing nitrogen oxide emissions, which relies on the precise injection and decomposition of automotive urea solution. The density of the urea solution is a key parameter characterizing its concentration and quality, directly affecting the accuracy of the reducing agent supply and the purification efficiency of the SCR system. Therefore, the rapid and accurate determination of the urea solution density has significant engineering application value.

[0003] Density sensors based on the vibrating tube principle are a common technical solution for online detection of urea solutions. This technology indirectly calculates the liquid density by measuring the change in the natural frequency of a vibrating tube filled with the liquid to be tested. Its basic principle is that there is a definite functional relationship between the vibration frequency and the mass of the medium inside the tube.

[0004] Traditional vibratory tube density sensors require a frequency search and locking process in their internal piezoelectric drive circuit when starting measurement or when operating conditions change, to match the drive signal with the mechanical resonant frequency of the vibratory tube in the current medium. This process typically requires several seconds of settling time, causing the sensor to be unable to provide instantaneous density readings. In the actual operating conditions of diesel engines, the SCR system's regulation of urea injection volume is on the order of milliseconds. The lag in sensor response severely restricts the real-time performance and accuracy of the closed-loop control system, potentially leading to excessive or insufficient urea injection, thereby affecting emission control performance and increasing operating costs. Therefore, significantly shortening the response time of the vibratory tube density sensor to meet the real-time, rapid regulation requirements of the SCR system has become a pressing technical challenge in this field. Summary of the Invention

[0005] The purpose of this invention is to provide a rapid urea density measurement system for vehicles, in order to solve the technical contradiction that existing density sensors based on the vibrating tube principle have excessively long response times due to the need to search for and lock the mechanical resonant frequency during startup or changes in operating conditions, thus failing to meet the millisecond-level real-time control requirements of SCR systems.

[0006] To achieve the above objectives, the present invention provides a rapid urea density determination system for vehicles, comprising: A vibrating tube density sensing unit is used to contain the automotive urea solution to be tested and generate a mechanical vibration signal related to the solution density. The multimodal collaborative drive and signal processing unit is used to generate drive signals to excite the vibrating tube and synchronously process the vibration pickup signals to extract frequency and amplitude information. An embedded real-time calculation and compensation unit is used to perform real-time compensation and correction on the initial density value output by the multi-modal collaborative driving and signal processing unit for multi-physical field coupling effects such as temperature, viscosity and tube stress, so as to output the final high-precision density value. The system control and communication interface unit is used to coordinate the working timing of various units within the system, process external commands, and output measurement results according to a preset protocol. The multimodal collaborative driving and signal processing unit integrates a high-precision direct digital frequency synthesizer, a programmable gain amplifier array, a high-speed analog-to-digital converter, and a digital signal processor. The workflow of the multimodal collaborative driving and signal processing unit is as follows: After the system is powered on or a measurement command is received, the digital signal processor retrieves the pre-stored reference resonance spectrum of the vibrating tube in the reference medium from the non-volatile memory. The reference resonance spectrum includes the resonant frequency values ​​of multiple order modes of the vibrating tube in the reference medium, the corresponding quality factors, and the frequency interval relationship between each mode. The direct digital frequency synthesizer generates two or more multi-frequency sinusoidal signals of different frequencies simultaneously based on the reference resonant spectrum. These frequencies correspond to the resonant frequency points of the first and second order bending modes predicted in the reference resonant spectrum, respectively. A driving piezoelectric ceramic sheet is attached to the vibrating tube. The multi-frequency sine wave signal is amplified by the programmable gain amplifier and then applied to the driving piezoelectric ceramic sheet. Meanwhile, the vibration response signal sensed by the driving piezoelectric ceramic sheet is initially conditioned by the programmable gain amplifier array and then synchronously sampled by the high-speed analog-to-digital converter. The digital signal processor performs a fast Fourier transform on the sampled time-domain signal to obtain the real-time vibration response spectrum; The digital signal processor compares and analyzes the real-time vibration response spectrum with the reference resonance spectrum, and calculates the relative change of the response amplitude near each excitation frequency point and the absolute offset of the resonant peak frequency of each mode. Based on the vibration beam theory, the digital signal processor constructs an overdetermined set of equations by synchronously monitoring the frequency offset of at least two modes, thereby quickly calculating the equivalent additional mass of the current urea solution acting on the vibration tube, and then deriving the initial density value. After calculating the initial density value, the digital signal processor synchronously starts the background refinement tracking thread. The refined tracking thread uses the calculated initial density value as a basis, combined with the real-time compensation temperature value obtained from the embedded real-time calculation and compensation unit, to back-calculate the accurate resonant frequency prediction value of the first-order main mode of the vibrating tube under the current working condition through the theoretical model. Subsequently, the multi-modal collaborative driving and signal processing unit smoothly transitions the driving mode from multi-frequency collaborative to a single-frequency phase-locked loop tracking mode centered on the precise resonant frequency. At the moment the system starts up, the embedded real-time calculation and compensation unit first reads the initial temperature value of the high-precision temperature sensor; The digital signal processor calculates the expected frequency drift of the current temperature relative to the reference calibration temperature based on the pre-stored thermal expansion coefficient and elastic modulus temperature coefficient of the vibrating tube material. The digital signal processor then adds this drift to the resonant frequency recorded in the reference resonant spectrum, which serves as the frequency setting value for the initial multi-frequency sine wave signal generated by the direct digital frequency synthesizer.

[0007] Preferably, the embedded real-time computing and compensation unit includes a microcontroller, a high-precision temperature sensor, and a data module storing a complete compensation algorithm model. The compensation process of the embedded real-time computing and compensation unit is as follows: The high-precision temperature sensor measures the temperature of the urea solution vibrating against the pipe wall or in close contact with the pipe wall in real time; the microcontroller receives the temperature data and the initial density value; the data module pre-stores a compensation model established through extensive experimental calibration. This compensation model is a multidimensional nonlinear function mapping relationship with the initial density value and temperature as input and the corrected density value as output. This multidimensional nonlinear function mapping relationship is implemented through a trained three-layer feedforward neural network, whose hidden layer contains 8 neurons and the activation function uses a modified linear unit; the microcontroller executes the neural network model to compensate the initial density value in real time and outputs the final calibrated urea solution density value.

[0008] Preferably, the system control and communication interface unit receives a measurement request signal from the vehicle SCR controller, triggers and synchronizes the startup of the multimodal collaborative drive and signal processing unit and the embedded real-time calculation and compensation unit. After completing a measurement cycle, the system control and communication interface unit encapsulates the final density value, solution temperature value and system status word into a data frame conforming to the controller LAN or vehicle Ethernet protocol, and sends it to the SCR controller through the physical layer interface.

[0009] Preferably, in the single-frequency phase-locked loop tracking mode, the direct digital frequency synthesizer generates a single-frequency sinusoidal drive signal with the predicted accurate resonant frequency as the center frequency; The digital signal processor internally employs a high-bandwidth digital phase-locked loop algorithm to continuously compare the phase difference between the drive signal and the pickup signal, and dynamically adjusts the output frequency of the direct digital frequency synthesizer so that the phase difference is always locked near the 90-degree resonant point.

[0010] Preferably, the method for obtaining and updating the reference resonance spectrum is as follows: Before the sensor leaves the factory or during periodic maintenance, the vibration tube cavity is filled with a standard reference medium, and a high-precision full-spectrum scanning calibration program is run at a standard temperature; the full-spectrum scanning calibration program controls the direct digital frequency synthesizer to scan in small steps within a wide frequency band, while recording the amplitude of the vibration pickup signal, thereby accurately plotting the complete resonance curve of the vibration tube under the reference medium, identifying and recording the accurate resonant frequencies and quality factors of the first three modes, and storing them as non-volatile reference data.

[0011] Preferably, the system further includes an online self-diagnosis and early warning unit; the online self-diagnosis and early warning unit continuously monitors the signal quality indicators output by the multimodal collaborative driving and signal processing unit, including the signal-to-noise ratio, harmonic distortion, and stability of the driving current of each mode; at the same time, it monitors the rationality of the input and output of the neural network model in the embedded real-time calculation and compensation unit.

[0012] Preferably, the online self-diagnosis and early warning unit is further configured to: determine that the sensor has a potential fault when the signal quality is continuously lower than a preset threshold, or the final density value after compensation exceeds the reasonable physical range of the urea solution; the online self-diagnosis and early warning unit then sends a specific fault code and early warning information to the SCR controller through the system control and communication interface unit.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention fundamentally changes the traditional operating mode of vibrating tube density sensors, which must undergo a time-consuming frequency search process, by employing a multi-mode cooperative driving strategy based on pre-stored resonance spectra. The system simultaneously excites and analyzes the frequency shifts of multiple modes, directly calculating the initial density value within milliseconds using overdetermined equations. This reduces the sensor's response time from startup to the first effective output from seconds to milliseconds, significantly improving dynamic response speed. This meets the stringent real-time requirements of SCR systems for urea solution density information, laying a crucial foundation for more precise closed-loop control of urea injection.

[0014] 2. This invention constructs a dual-layer measurement architecture combining rapid multimodal measurement with high-precision single-frequency tracking. The system achieves instantaneous response through multimodal collaboration upon startup, and seamlessly switches to phase-locked loop mode for continuous high-precision tracking after stabilization. This architecture addresses the dual requirements of rapid startup and long-term stable high-precision monitoring, enabling the system to not only quickly adapt to sudden changes in operating conditions but also provide measurement accuracy and stability superior to traditional methods in steady-state conditions, comprehensively improving the sensor's overall performance.

[0015] 3. This invention integrates an embedded real-time multiphysics compensation unit based on neural networks. This embedded real-time multiphysics compensation unit uses a pre-stored nonlinear compensation model trained with a large amount of experimental data to perform real-time, online comprehensive compensation for cross-sensitive factors such as temperature and viscosity. Compared to traditional piecewise linear or simple polynomial compensation methods, the neural network model can more accurately fit complex coupling effects and effectively isolate the influence of non-density factors on the measurement results, thus ensuring high accuracy and reliability of the final output density value across a wide temperature range and under different solution qualities.

[0016] 4. This invention introduces an initial frequency setting mechanism including temperature pre-compensation and an online self-diagnostic function. The temperature pre-compensation mechanism makes the system's initial drive frequency closer to actual operating conditions, further optimizing startup performance. The online self-diagnostic function continuously monitors the health status and output rationality of the sensor's core signal chain, enabling timely detection of potential faults such as crystallization and failure, and reporting them through the standard vehicle communication protocol. This enhances the system's reliability and maintainability, ensuring the long-term stable operation of the SCR aftertreatment system. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the overall technical architecture of the rapid urea density determination system for vehicles proposed in this invention. Figure 2 This is a schematic diagram of the core principle framework of the multi-modal collaborative driving strategy based on pre-stored resonance spectrum and real-time dynamic tracking in this invention; Figure 3 This is a logical flow diagram of the multimodal collaborative driving and signal processing unit in this invention; Figure 4 This is a schematic diagram of the multiphysics coupling effect compensation principle framework of the embedded real-time computing and compensation unit in this invention; Figure 5 This is a schematic diagram of the dual-layer measurement architecture that combines rapid startup with continuous high-precision monitoring in this invention. Detailed Implementation

[0018] This invention provides a rapid urea density determination system for vehicles; please refer to the appendix for its overall technical architecture. Figures 1 to 5 This system aims to address the core technical challenge of existing density sensors based on the vibrating tube principle, which suffer from excessively long response times due to the need to search for and lock the mechanical resonant frequency, thus failing to meet the millisecond-level real-time control requirements of selective catalytic reduction systems. Through an innovative multimodal collaborative driving and signal processing strategy, combined with embedded real-time multiphysics compensation, this system achieves millisecond-level rapid measurement and continuous high-precision monitoring of the density of automotive urea solution from startup to output.

[0019] The rapid density measurement system for automotive urea consists of four core functional units: a vibrating tube density sensing unit, a multimodal collaborative drive and signal processing unit, an embedded real-time calculation and compensation unit, and a system control and communication interface unit. These units interact through precise electrical connections and a data bus to form a complete closed-loop measurement and control system.

[0020] First, the specific implementation details of the vibrating tube density sensing unit are described. This vibrating tube density sensing unit is the core of the system's mechanical sensing, and its function is to contain the automotive urea solution to be tested and generate a mechanical vibration signal directly related to the solution's density. The main body of this vibrating tube density sensing unit is a hollow, thin-walled vibrating tube made of a specific elastic alloy material. This specific elastic alloy material is typically selected from those with high elastic modulus, low temperature coefficient, and excellent resistance to urea corrosion, such as nickel-based high-temperature alloys or titanium alloys with special surface treatments.

[0021] The vibratory tube's geometry is precisely designed, with its length, outer diameter, and wall thickness ratio meeting specific stiffness and mass distribution requirements to ensure clearly separated and stable first few bending vibration modes within the target frequency range, such as 100 Hz to 5000 Hz. Both ends of the vibratory tube are sealed and secured with high-strength, high-rigidity metal flanges, which are bolted to the inner wall of the sensor's stainless steel or engineering plastic housing. This installation method is mechanically equivalent to a beam structure fixed at both ends, providing well-defined boundary conditions for vibration.

[0022] Two sets of piezoelectric ceramic sheets are symmetrically attached to the outer wall of the vibrating tube at specific axial and circumferential positions using a high-precision patching process. One set of piezoelectric ceramic sheets serves as a driving element, responsible for converting electrical signals into mechanical force to excite the vibrating tube to vibrate; the other set serves as a vibration pickup element, responsible for converting the mechanical vibration of the vibrating tube into electrical signals.

[0023] The selection of piezoelectric ceramic plates requires high electromechanical coupling coefficients, low aging rates, and wide temperature range stability. Driving and pickup ceramic plates typically appear in pairs and are bonded to the antinodes of the vibrating tube corresponding to the maximum strain of a specific mode, maximizing excitation and detection efficiency. The entire vibrating tube assembly, piezoelectric ceramic plates, and sensor housing providing mechanical protection and environmental sealing together constitute a complete mechanical resonant cavity. The sensor housing is designed with inlet and outlet channels for urea solution. These channels typically incorporate rectification structures to reduce fluid flow interference with the vibrating tube and ensure that the urea solution can quickly and uniformly fill the internal cavity of the vibrating tube.

[0024] The following describes in detail the specific implementation of the multimodal cooperative driving and signal processing unit. Please refer to the appendix for its core principle framework. Figure 2 Please refer to the attached document for the logical flow framework. Figure 3The key innovation of this invention lies in the multimodal cooperative driving and signal processing unit. It abandons the single-frequency search and phase-locked loop locking mode used in traditional vibrating tube density sensors and instead implements a multimodal cooperative driving strategy based on pre-stored resonance spectrum and real-time dynamic tracking.

[0025] This multimodal collaborative drive and signal processing unit integrates a high-precision direct digital frequency synthesizer, a multi-channel programmable gain amplifier array, a synchronous sampling high-speed analog-to-digital converter, and a high-performance digital signal processor in hardware. These hardware components are interconnected with serial peripheral interfaces via an internal high-speed parallel bus.

[0026] The workflow of the multimodal collaborative drive and signal processing unit begins with system power-on initialization or receiving a measurement trigger command from an external source. The digital signal processor first retrieves a pre-stored reference resonance spectrum of the specific resonant tube in a reference medium from its internal or externally connected non-volatile memory. The reference medium is typically deionized water with known density and viscosity, or a standard concentration such as 32.5% automotive urea solution. The reference resonance spectrum is acquired on a high-precision calibration platform before the sensor leaves the factory or during periodic maintenance. The calibration process is as follows: the resonant tube cavity is filled with the reference medium and placed in a constant temperature environment, such as 25 degrees Celsius.

[0027] The system runs a full-spectrum scanning calibration program, which controls the direct digital frequency synthesizer to scan within a preset wide bandwidth, such as 100 Hz to 5000 Hz, in very small frequency steps, such as 0.1 Hz. At each frequency point, the direct digital frequency synthesizer outputs a sinusoidal drive signal with a fixed amplitude, while the high-speed analog-to-digital converter synchronously acquires the response signal output by the pickup element.

[0028] The digital signal processor performs amplitude calculations or fast Fourier transform analysis on the acquired time-domain signal, recording the vibration response amplitude corresponding to each frequency point. After scanning, a complete amplitude-frequency characteristic curve, i.e., the resonance curve, is obtained. From this resonance curve, the system automatically identifies and extracts the precise resonant frequency values ​​of the first few modes, usually the first three bending vibration modes, the quality factor corresponding to each resonance peak, the half-power bandwidth, and the frequency interval relationship between the resonant peaks of each mode.

[0029] After being formatted, this data is permanently stored as a reference data packet in non-volatile memory. Upon each power-up, the system executes a quick self-test procedure, verifying the integrity of the signal link by injecting a signal of known frequency and checking the response, but typically does not perform a full-spectrum rescan.

[0030] After accessing the reference spectrum, the digital signal processor immediately sends control commands to the direct digital frequency synthesizer (DDSP) based on the spectrum data. The DDSP then generates two or more sinusoidal signals of different frequencies simultaneously. In a typical implementation, this initial multi-frequency sinusoidal signal contains two frequency components, each precisely corresponding to the resonant frequency of the first bending mode recorded in the reference spectrum. The resonant frequency values ​​of the second bending mode .

[0031] The direct digital frequency synthesizer (DDS) is capable of simultaneously generating multiple independent frequency signals with a frequency resolution of up to 0.001 Hz and extremely low phase noise. This multi-frequency composite signal is fed into a programmable gain amplifier (PGA) for power amplification. The gain value of the PGA is preset by the digital signal processor based on the typical driving efficiency corresponding to each mode in the reference spectrum, ensuring that each frequency component can excite the resonant tube with appropriate energy. The amplified multi-frequency driving voltage is then applied to a driving piezoelectric ceramic plate attached to the resonant tube.

[0032] Simultaneously with the application of a drive, the vibration response signal sensed by the driving piezoelectric ceramic plate attached to the vibrating tube is a composite voltage signal containing multiple frequency components. This composite voltage signal first enters an independent conditioning channel in a programmable gain amplifier array. This independent conditioning channel typically includes an anti-aliasing low-pass filter and a programmable gain amplifier to adjust the signal amplitude to a suitable range for the analog-to-digital converter's input. The conditioned analog signal is then sent to a high-speed analog-to-digital converter for synchronous sampling.

[0033] The sampling rate of a high-speed analog-to-digital converter must satisfy the Nyquist sampling theorem and is typically set to at least four times the highest frequency of interest, such as 20 kHz. Its sampling clock is synchronized with the clock of the direct digital frequency synthesizer to ensure the coherence of signal processing.

[0034] A high-speed analog-to-digital converter (ADC) transmits the acquired time-domain voltage sequence to a digital signal processor (DSP). The DSP performs a fast Fourier transform on this time-domain data, converting it to the frequency domain to obtain the real-time vibration response spectrum of the vibrating tube under combined drive. This real-time vibration response spectrum includes the data at the drive frequency. and The nearby resonance peak is observed. The digital signal processor then executes the core comparison and analysis algorithm. This algorithm first compares and analyzes the real-time vibration response spectrum at a pre-stored reference frequency. and Centered on a narrow search window, for example ±10 Hz, locate the peak frequency of the current actual resonant peak. and And read its corresponding amplitude. and Simultaneously, the corresponding reference amplitude under the reference medium is read from the reference data. and .

[0035] Based on the theory of vibrating beams, for a beam structure fixed at both ends, its first... Resonant frequency of bending mode There is a definite functional relationship between the effective mass of the beam itself, including the mass of the tube and the additional mass of the medium inside the tube. When the density of the medium inside the tube changes, it is equivalent to adding additional mass to the vibrating tube, thereby causing the resonant frequency of all modes to decrease.

[0036] Different orders of modes have different sensitivities to added masses, with higher-order modes typically exhibiting higher sensitivity. Therefore, the... Frequency shift of first mode With medium density There is a correlation. By simultaneously monitoring the frequency shifts of at least two modes, a system of equations can be constructed. Assuming the vibrating tube is a uniform beam and the medium is uniformly attached, the relationship between its frequency and density can be approximately described by the following formula:

[0037] in, The currently measured number First-order modal frequency, Based on the first First-order modal frequency, Let the density of the urea solution be the unknown. For the first The sensitivity coefficient of the first mode is a constant related to the geometry, material properties and modal order of the vibrating tube, and is determined through calibration.

[0038] For 2 modes =1 and =2, we can obtain two equations. The digital signal processor uses the pre-stored calibration sensitivity coefficients C1 and C2 to measure the... and Substituting into the above formula, we can construct about The system consists of an overdetermined set of equations. Due to minute measurement errors, the system employs optimization algorithms such as the least squares method to solve for the optimal density value. .

[0039] this This means that the initial density value can be rapidly calculated in milliseconds, typically less than 10 milliseconds, using a multimodal collaborative driving strategy. This process completely avoids the time-consuming steps of slowly scanning or iteratively locking a single frequency in traditional methods, achieving instantaneous and rapid density determination.

[0040] Furthermore, in the multimodal collaborative driving strategy, the frequency setting of the initial multi-frequency sine wave signal can introduce a pre-offset based on temperature prediction to further optimize startup performance. Specifically, at the instant the system starts, the embedded real-time calculation and compensation unit first reads the initial temperature value from the high-precision temperature sensor. The digital signal processor uses the pre-stored coefficient of thermal expansion of the vibrating tube material. and temperature coefficient of elastic modulus Calculate the current temperature Relative to reference calibration temperature For example, the expected frequency drift scaling factor at 25 degrees Celsius.

[0041] For the The temperature drift of the frequency of the first mode can be approximated as: The digital signal processor uses this calculated frequency drift. Superimposed on the reference resonant frequency The frequency setpoint after temperature pre-compensation is obtained. Direct digital frequency synthesizers, on the other hand, rely on... This generates an initial multi-frequency sine wave signal. This makes the initial driving frequency closer to the actual resonant point of the vibrating tube at the current temperature at the moment of startup, effectively reducing the transient settling time from power-on to outputting a stable signal.

[0042] The specific implementation method of the embedded real-time computing and compensation unit is then described. Please refer to the appendix for the compensation principle framework. Figure 4 The core function of this embedded real-time computing and compensation unit is to calculate the initial density value output by the multimodal collaborative driving and signal processing unit. This system performs real-time compensation and correction for the coupling effects of multiple physical fields, such as temperature, viscosity, and pipe stress, ultimately outputting a high-precision urea solution density value. The embedded real-time calculation and compensation unit includes a microcontroller, or several high-precision temperature sensors, and a data module storing a complete compensation algorithm model. Data exchange between the microcontroller and the digital signal processor is achieved through a high-speed serial communication interface, such as a serial peripheral interface.

[0043] The high-precision temperature sensor is used to measure the temperature of the vibrating tube wall or the temperature of the urea solution flowing close to the tube wall in real time. The temperature sensor typically uses a platinum resistance thermometer or a high-precision negative temperature coefficient thermistor. Its probe achieves good thermal contact with the outer wall of the vibrating tube through thermally conductive silicone grease or mechanical clamping, ensuring real-time and accurate temperature measurement. The analog signal from the temperature sensor, after passing through a signal conditioning circuit, is sampled by an internal analog-to-digital converter (ADC) of the microcontroller or an external ADC and converted into a digital temperature value. .

[0044] The data module contains a pre-stored mathematical model for multiphysics field effect compensation, established through extensive experimental calibration. This mathematical model uses an initial density value... and real-time temperature value As input, the corrected final density value This represents the multidimensional nonlinear function mapping relationship for the output. Since temperature changes simultaneously cause volume expansion and density changes in the urea solution itself, alterations in the elastic modulus of the vibrating tube material affecting the resonant frequency, and changes in solution viscosity affecting vibration damping, these effects are interconnected. Traditional piecewise linear compensation or simple polynomial fitting is insufficient to achieve high accuracy. Therefore, in this embodiment, the mapping relationship is implemented using a specially trained three-layer feedforward artificial neural network.

[0045] The structure of a three-layer feedforward artificial neural network is as follows: The input layer contains two neurons, corresponding to the input parameters respectively. and The output layer contains one neuron, with corresponding output parameters. The hidden layer contains 8 neurons. The activation function for the neurons in the hidden layer uses a modified linear unit, and its mathematical expression is: The output layer neurons use a linear activation function.

[0046] The weight matrix and bias vector parameters of the three-layer feedforward artificial neural network were obtained through extensive experimental calibration data. The training dataset covered the full concentration range of automotive urea solution (e.g., 0% to 40%), the full operating temperature range (e.g., -30°C to 80°C), and the viscosity variations that may arise from different urea quality solutions. The training process employed backpropagation and gradient descent optimizers, aiming to minimize the mean square error between the predicted values ​​of the three-layer feedforward artificial neural network and the measurements from a high-precision reference densitometer. After training and validation, all weights and bias parameters of the three-layer feedforward artificial neural network were permanently stored in the read-only memory or flash memory of the data module.

[0047] In each measurement cycle, the microcontroller synchronously receives the initial density value from the digital signal processor. and real-time temperature values ​​from temperature sensors The microcontroller's firmware performs the forward propagation calculations of the three-layer feedforward artificial neural network. The specific calculation process is as follows: first, the input values ​​are normalized to ensure they fall within the range set during the training of the three-layer feedforward artificial neural network, for example, from 0 to 1.

[0048] The normalized input vector is then fed into the network. The weighted sum of each neuron in the hidden layer is calculated according to the formula, and a modified linear unit activation is applied. The outputs of the hidden layers are then weighted and summed to obtain the output layer value. Finally, the output value is denormalized to obtain the final compensation density value. The entire calculation process is highly optimized and can be completed on a microcontroller within a few hundred microseconds, meeting real-time requirements. Through compensation, the system can effectively isolate the influence of non-density factors such as temperature and viscosity on the measurement results, ensuring that the final output density value maintains high accuracy over a wide temperature range and in different solution conditions, with a typical accuracy better than ±0.0005 g / cm³.

[0049] Finally, the specific implementation of the system control and communication interface unit is described. This unit acts as the hub for interaction between the system and the external vehicle network, responsible for coordinating the timing of internal units, parsing external commands, and formatting the output of measurement results. The system control and communication interface unit is typically implemented using a microcontroller or field-programmable gate array (FPGA), and runs a real-time task scheduler internally.

[0050] The system's control and communication interface unit continuously monitors measurement request signals from the vehicle's selective catalytic reduction controller via isolated digital input channels. These measurement request signals are typically pulse-width modulated signals or specific controller area network (CLAN) remote frames.

[0051] Upon receiving a valid measurement request, the system control and communication interface unit immediately sends a hardware interrupt or command word to the digital signal processor of the multimodal collaborative drive and signal processing unit, triggering it to start a new measurement cycle. Simultaneously, it notifies the microcontroller of the embedded real-time calculation and compensation unit to prepare to receive data. The system control and communication interface unit internally maintains a precise timing state machine to ensure the orderly connection of each stage of driving, sampling, calculation, and compensation.

[0052] After a complete measurement cycle, the system control and communication interface unit reads the final compensation density value from the embedded real-time calculation and compensation unit. It also reads the current solution temperature T from the temperature sensor. Furthermore, it collects system status information from the multimodal collaborative drive and signal processing unit and the self-diagnostic unit, such as signal quality indicators and fault codes.

[0053] The system control and communication interface unit encapsulates this data into standard data frames according to a preset communication protocol. For automotive applications, the communication protocol is typically the CANopen device protocol or SAE J1939 protocol in the Controller Area Network (CAN) protocol, or the SOME / IP or DoIP protocol in the automotive Ethernet. The data frame contains at least the density value, temperature value, status word, and cyclic redundancy check (CRC) code.

[0054] After encapsulation, the system control and communication interface unit sends data frames to the vehicle network bus through its integrated Controller Area Network (CLAN) controller physical layer interface or Ethernet media access controller physical layer interface, so that the selective catalytic reduction (SCR) controller can receive them and use them for closed-loop calculation of urea injection quantity.

[0055] Furthermore, the digital signal processor rapidly calculates the initial density value through a multi-modal cooperative strategy. Afterwards, a background refinement tracing thread will be started simultaneously. Please refer to the attached diagram for its architecture. Figure 5 The purpose of this refined tracking thread is to seamlessly transition to a continuous monitoring mode with higher accuracy and a higher update rate after a quick start-up.

[0056] The specific implementation is as follows: The digital signal processor calculates... Based on the real-time compensated temperature T obtained from the microcontroller, and combined with the theoretical model and calibration parameters of the vibrating tube, the accurate resonant frequency prediction of the first principal mode of the vibrating tube under the current density and temperature conditions is calculated in reverse. The calculations utilized the aforementioned inverse function model of the frequency-density-temperature relationship. Once the calculations were completed... The digital signal processor sends a mode switching command to the multi-mode cooperative drive and signal processing unit. The direct digital frequency synthesizer stops outputting multi-frequency signals and instead generates signals in the form of... It is a single-frequency sine wave signal with a center frequency.

[0057] Meanwhile, the digital signal processor internally employs a high-bandwidth digital phase-locked loop (PLL) algorithm. This PLL algorithm continuously compares the phase difference between the drive signal and the pickup signal, and dynamically adjusts the output frequency of the direct digital frequency synthesizer to keep the phase difference locked near the 90-degree resonant point. The PLL boasts extremely high frequency tracking accuracy, typically better than 0.01 Hz, and extremely fast tracking speed, enabling it to track resonant frequency changes caused by minute density variations or temperature drifts in real time.

[0058] In this mode, the system uses a frequency locked by a phase-locked loop. As measured values, a high-update-rate density data stream is calculated by looking up tables or using a simplified single-mode density-frequency relationship model. This two-layer measurement architecture, combining rapid multimodal startup with high-precision single-mode tracking, balances the system's instantaneous response capability with steady-state measurement performance.

[0059] Furthermore, the system also includes an online self-diagnosis and early warning unit integrated into the system control and communication interface unit or operating as a separate coprocessor. This online self-diagnosis and early warning unit continuously monitors the health status of the entire signal chain through software algorithms. Its diagnostic content mainly includes the following aspects: First, monitor the real-time vibration response spectrum quality of the multi-modal collaborative drive and signal processing unit output, and calculate the signal-to-noise ratio, total harmonic distortion, and stability index of the drive current for each modal signal.

[0060] Second, monitor the basic noise level of the vibration pickup signal to determine whether signal attenuation is caused by the failure of the piezoelectric ceramic sheet or poor connection.

[0061] Third, monitor the rationality of the input and output of the neural network model in the embedded real-time computing and compensation unit, for example, check the initial density value of the input. Check whether the temperature T is within the valid range covered by the training dataset, and examine the final density value of the output. Whether it is within the reasonable physical density range of automotive urea solution, such as 1.0 to 1.2 grams per cubic centimeter.

[0062] Fourth, by combining temperature and density outputs and using a built-in urea solution characteristic model, the current solution concentration and freezing point are estimated and cross-validated with reasonable values. The self-diagnostic unit sets a series of dynamic or static thresholds for these monitoring indicators.

[0063] If any indicator consistently exceeds a threshold for a preset duration, such as a signal-to-noise ratio below 20 dB for five consecutive cycles, or an output density value exceeding 1.15 g / cm³ for three consecutive times, the self-diagnostic unit determines that the sensor has a potential fault. Possible fault types include internal crystallization blockage in the vibrating tube, delamination or aging of the piezoelectric ceramic sheet, and abnormal fluid medium (non-urea solution).

[0064] Once a fault is confirmed, the self-diagnostic unit generates a specific diagnostic fault code and encapsulates it into the status word of the output data frame according to the standard on-board diagnostic protocol via the system control and communication interface unit, or actively sends a controller area network error frame to issue a warning message to the selective catalytic reduction controller. The controller can then determine, based on the fault level, whether to activate the backup urea density estimation strategy, limit engine torque, or illuminate the fault indicator light on the driver's instrument panel, thereby ensuring the safe operation of the aftertreatment system and prompting maintenance requirements.

Claims

1. A rapid density determination system for automotive urea, characterized in that, include: A vibrating tube density sensing unit is used to contain the automotive urea solution to be tested and generate a mechanical vibration signal related to the solution density. The multimodal collaborative drive and signal processing unit is used to generate drive signals to excite the vibrating tube and synchronously process the vibration pickup signals to extract frequency and amplitude information. An embedded real-time calculation and compensation unit is used to perform real-time compensation and correction on the initial density value output by the multi-modal collaborative driving and signal processing unit for multi-physical field coupling effects such as temperature, viscosity and tube stress, so as to output the final high-precision density value. The system control and communication interface unit is used to coordinate the working timing of various units within the system, process external commands, and output measurement results according to a preset protocol. The multimodal collaborative driving and signal processing unit integrates a high-precision direct digital frequency synthesizer, a programmable gain amplifier array, a high-speed analog-to-digital converter, and a digital signal processor. The workflow of the multimodal collaborative driving and signal processing unit is as follows: After the system is powered on or a measurement command is received, the digital signal processor retrieves the pre-stored reference resonance spectrum of the vibrating tube in the reference medium from the non-volatile memory. The reference resonance spectrum includes the resonant frequency values ​​of multiple order modes of the vibrating tube in the reference medium, the corresponding quality factors, and the frequency interval relationship between each mode. The direct digital frequency synthesizer generates two or more multi-frequency sinusoidal signals of different frequencies simultaneously based on the reference resonant spectrum. These frequencies correspond to the resonant frequency points of the first and second order bending modes predicted in the reference resonant spectrum, respectively. A driving piezoelectric ceramic sheet is attached to the vibrating tube. The multi-frequency sine wave signal is amplified by the programmable gain amplifier and then applied to the driving piezoelectric ceramic sheet. Meanwhile, the vibration response signal sensed by the driving piezoelectric ceramic sheet is initially conditioned by the programmable gain amplifier array and then synchronously sampled by the high-speed analog-to-digital converter. The digital signal processor performs a fast Fourier transform on the sampled time-domain signal to obtain the real-time vibration response spectrum; The digital signal processor compares and analyzes the real-time vibration response spectrum with the reference resonance spectrum, and calculates the relative change of the response amplitude near each excitation frequency point and the absolute offset of the resonant peak frequency of each mode. Based on the vibration beam theory, the digital signal processor constructs an overdetermined set of equations by synchronously monitoring the frequency offset of at least two modes, thereby quickly calculating the equivalent additional mass of the current urea solution acting on the vibration tube, and then deriving the initial density value. After calculating the initial density value, the digital signal processor synchronously starts the background refinement tracking thread. The refined tracking thread uses the calculated initial density value as a basis, combined with the real-time compensation temperature value obtained from the embedded real-time calculation and compensation unit, to back-calculate the accurate resonant frequency prediction value of the first-order main mode of the vibrating tube under the current working condition through the theoretical model. Subsequently, the multi-modal collaborative driving and signal processing unit smoothly transitions the driving mode from multi-frequency collaborative to a single-frequency phase-locked loop tracking mode centered on the precise resonant frequency. At the moment the system starts up, the embedded real-time calculation and compensation unit first reads the initial temperature value of the high-precision temperature sensor; The digital signal processor calculates the expected frequency drift of the current temperature relative to the reference calibration temperature based on the pre-stored thermal expansion coefficient and elastic modulus temperature coefficient of the vibrating tube material. The digital signal processor then adds this drift to the resonant frequency recorded in the reference resonant spectrum, which serves as the frequency setting value for the initial multi-frequency sine wave signal generated by the direct digital frequency synthesizer.

2. The rapid density determination system for automotive urea according to claim 1, characterized in that, The embedded real-time computing and compensation unit includes a microcontroller, a high-precision temperature sensor, and a data module storing a complete compensation algorithm model. The compensation process of the embedded real-time computing and compensation unit is as follows: The high-precision temperature sensor measures the temperature of the urea solution vibrating against the pipe wall or in close contact with the pipe wall in real time; the microcontroller receives the temperature data and the initial density value; the data module pre-stores a compensation model established through extensive experimental calibration. This compensation model is a multidimensional nonlinear function mapping relationship with the initial density value and temperature as input and the corrected density value as output. This multidimensional nonlinear function mapping relationship is implemented through a trained three-layer feedforward neural network, whose hidden layer contains 8 neurons and the activation function uses a modified linear unit; the microcontroller executes the neural network model to compensate the initial density value in real time and outputs the final calibrated urea solution density value.

3. The rapid density determination system for automotive urea according to claim 2, characterized in that, The system control and communication interface unit receives a measurement request signal from the vehicle SCR controller, triggers and synchronizes the startup of the multimodal collaborative drive and signal processing unit and the embedded real-time calculation and compensation unit. After completing a measurement cycle, the system control and communication interface unit encapsulates the final density value, solution temperature value and system status word into a data frame conforming to the controller LAN or vehicle Ethernet protocol, and sends it to the SCR controller through the physical layer interface.

4. The rapid density determination system for automotive urea according to claim 3, characterized in that, In the single-frequency phase-locked loop tracking mode, the direct digital frequency synthesizer generates a single-frequency sinusoidal drive signal with the predicted accurate resonant frequency as the center frequency; The digital signal processor internally employs a high-bandwidth digital phase-locked loop algorithm to continuously compare the phase difference between the drive signal and the pickup signal, and dynamically adjusts the output frequency of the direct digital frequency synthesizer so that the phase difference is always locked near the 90-degree resonant point.

5. The rapid density determination system for automotive urea according to claim 4, characterized in that, The method for obtaining and updating the reference resonance spectrum is as follows: Before the sensor leaves the factory or during periodic maintenance, the vibration tube cavity is filled with a standard reference medium, and a high-precision full-spectrum scanning calibration program is run at a standard temperature; the full-spectrum scanning calibration program controls the direct digital frequency synthesizer to scan in small steps within a wide frequency band, while recording the amplitude of the vibration pickup signal, thereby accurately plotting the complete resonance curve of the vibration tube under the reference medium, identifying and recording the accurate resonant frequencies and quality factors of the first three modes, and storing them as non-volatile reference data.

6. The rapid density determination system for automotive urea according to claim 5, characterized in that, The system also includes an online self-diagnosis and early warning unit; the online self-diagnosis and early warning unit continuously monitors the signal quality indicators output by the multimodal collaborative driving and signal processing unit, including the signal-to-noise ratio, harmonic distortion, and stability of the driving current of each mode; at the same time, it monitors the rationality of the input and output of the neural network model in the embedded real-time calculation and compensation unit.

7. The rapid density determination system for automotive urea according to claim 6, characterized in that, The online self-diagnosis and early warning unit is also used to: determine that the sensor has a potential fault when the signal quality is continuously lower than a preset threshold, or the final density value after compensation exceeds the reasonable physical range of the urea solution; the online self-diagnosis and early warning unit then sends a specific fault code and early warning information to the SCR controller through the system control and communication interface unit.

Images