An intelligent sensing-based monitoring method and system for automotive emergency starting power supplies

Abstract

The present invention relates to the field of automotive electronics technology, and discloses a method and system for monitoring an automotive emergency starting power supply based on intelligent sensing, including: constructing a contact PT100 sensor and a non-contact infrared thermal imager for the automotive emergency starting power supply to collect the PT100 signal and infrared image of the automotive emergency starting power supply; performing dual-modal fusion on the PT100 signal and the infrared image to obtain a three-dimensional temperature field distribution and analyze the local overheating points of the automotive emergency starting power supply; using a preset digital direct frequency synthesis algorithm to synthesize a swept-frequency excitation signal for the automotive emergency starting power supply, analyzing the complex impedance spectrum of the automotive emergency starting power supply, and using a pre-trained optimized Cole-Cole model to extract the charge transfer resistance Rct and double-layer capacitance Cdl of the automotive emergency starting power supply; determining an early warning mechanism for the automotive emergency starting power supply, and performing effective monitoring of the automotive emergency starting power supply based on the early warning mechanism. The present invention can improve the reliability and safety of vehicle starting.

Description

Technical Field

[0001] The present invention relates to a method and system for monitoring an emergency starting power supply of an automobile based on intelligent sensing, and belongs to the field of automotive electronics technology. Background Art

[0002] Monitoring of an emergency starting power supply of an automobile refers to the process of detecting and evaluating the working state, performance parameters and health status of the emergency starting power supply of an automobile (usually referring to a portable or in-vehicle 12V or 24V starting power supply) in real time or regularly. The purpose of this monitoring is to ensure that when the automobile battery fails or has insufficient power, the emergency starting power supply can reliably start the automobile engine and avoid the vehicle being unable to start due to power problems.

[0003] Traditional monitoring of an emergency starting power supply of an automobile usually relies on simple voltmeters and ammeters to manually check the output voltage and current of the power supply. This method can often only provide basic power information and lacks in-depth analysis of the internal state and potential faults of the battery. Therefore, it cannot provide comprehensive and efficient battery health management, and is prone to overcharging, over-discharging or accidental failure of the battery, affecting the reliability and safety of vehicle starting. Summary of the Invention

[0004] The present invention provides a method and system for monitoring an emergency starting power supply of an automobile based on intelligent sensing, and its main purpose is to improve the reliability and safety of vehicle starting.

[0005] To achieve the above object, a method for monitoring an emergency starting power supply of an automobile based on intelligent sensing provided by the present invention includes:

[0006] Construct a multi-source sensor array of the emergency starting power supply of the automobile, and collect voltage signals, current waveforms and vibration spectrum data of the emergency starting power supply based on the multi-source sensor array;

[0007] Construct a contact PT100 sensor and a non-contact infrared thermal imager of the emergency starting power supply of the automobile, and collect PT100 signals and infrared images of the emergency starting power supply of the automobile based on the contact PT100 sensor and the non-contact infrared thermal imager;

[0008] Perform dual-modal fusion on the PT100 signal and the infrared image to obtain a three-dimensional temperature field distribution, and analyze local overheating points of the emergency starting power supply of the automobile according to the three-dimensional temperature field distribution;

[0009] According to the local overheating point, a swept-frequency excitation signal of the automotive emergency starting power supply is synthesized by using a preset direct digital frequency synthesis algorithm. Based on the swept-frequency excitation signal, the complex impedance spectrum of the automotive emergency starting power supply is analyzed. According to the complex impedance spectrum, the charge transfer resistance Rct and the double-layer capacitance Cdl of the automotive emergency starting power supply are extracted by using a pre-trained optimized Cole-Cole model;

[0010] Based on the charge transfer resistance Rct, the double-layer capacitance Cdl, the voltage signal, the current waveform, and the vibration spectrum data, a warning mechanism of the automotive emergency starting power supply is determined, and effective monitoring of the automotive emergency starting power supply is performed based on the warning mechanism.

[0011] Optionally, the collecting the voltage signal, the current waveform, and the vibration spectrum data of the emergency starting power supply based on the multi-source sensor array includes:

[0012] Configuring the acquisition parameters of the multi-source sensor array corresponding to the DAQ acquisition unit;

[0013] According to the acquisition parameters, the output voltage, the output current, and the vibration data of the emergency starting power supply are acquired through the DAQ acquisition unit;

[0014] Converting the output voltage, the output current, and the vibration data into electrical signals to obtain a voltage signal, a current signal, and a vibration signal;

[0015] According to the current signal, the current waveform of the emergency starting power supply is analyzed;

[0016] Through the vibration signal, the vibration spectrum data of the emergency starting power supply is analyzed.

[0017] Optionally, the collecting the PT100 signal and the infrared image of the automotive emergency starting power supply based on the contact PT100 sensor and the non-contact infrared thermal imager includes:

[0018] Analyzing the thermally sensitive area of the automotive emergency starting power supply;

[0019] Integrating the contact PT100 sensor into the thermally sensitive area and calibrating the contact PT100 sensor to obtain a calibrated PT100 sensor;

[0020] Collecting the PT100 signal of the automotive emergency starting power supply based on the calibrated PT100 sensor;

[0021] Determining the coordinate position of the non-contact infrared thermal imager;

[0022] Analyze the imager field of view of the non-contact infrared thermal imager according to the coordinate position;

[0023] Define the imager parameters of the non-contact infrared thermal imager according to the imager field of view;

[0024] Based on the imager parameters, use the non-contact infrared thermal imager to collect the infrared image of the automotive emergency starting power supply.

[0025] Optionally, the analysis of the heat-sensitive area of the automotive emergency starting power supply includes:

[0026] Obtain the heat test data of the automotive emergency starting power supply;

[0027] Determine the heat source of the automotive emergency starting power supply;

[0028] Grid the automotive emergency starting power supply to obtain power grid units;

[0029] Analyze the unit hot spot temperature and power change rate of the power grid unit;

[0030] Based on the heat source, the unit hot spot temperature, and the power change rate, calculate the transient thermal resistance of the power grid unit using the following formula:

[0031] ;

[0032] Where, represents the transient thermal resistance of the power grid unit at time, represents the unit hot spot temperature of the power grid unit at time, represents the power of the cth heat source of the power grid unit at time, represents the number of heat sources in the power grid unit, represents the ambient temperature corresponding to the power grid unit, represents the material thermal inertia coefficient, represents the power change rate of the power grid unit at time;

[0033] Based on the transient thermal resistance, determine the heat-sensitive area of the automotive emergency starting power supply.

[0034] Optionally, the dual-modal fusion of the PT100 signal and the infrared image to obtain a three-dimensional temperature field distribution includes:

[0035] Preprocess the PT100 signal and the infrared image to obtain a processed PT100 signal and a processed infrared image;

[0036] Perform spatial registration on the processed PT100 signal and the processed infrared image to obtain a registered PT100 signal and a registered infrared image;

[0037] Fuse the registered PT100 signal and the registered infrared image to obtain fused bimodal data;

[0038] Construct a three-dimensional power model of the automotive emergency starting power supply corresponding to the PT100 signal;

[0039] Map the fused bimodal data into the three-dimensional power model to obtain the three-dimensional temperature field distribution.

[0040] Optionally, the synthesizing the swept-frequency excitation signal of the automotive emergency starting power supply using a preset digital direct frequency synthesis algorithm according to the local overheating point includes:

[0041] Determine the component to be excited of the automotive emergency starting power supply according to the local overheating point;

[0042] Define the excitation signal requirements for the component to be excited;

[0043] Determine the synthesis parameters of the digital direct frequency synthesis algorithm according to the excitation signal requirements;

[0044] Synthesize the swept-frequency excitation signal of the automotive emergency starting power supply using the digital direct frequency synthesis algorithm through the synthesis parameters.

[0045] Optionally, the analyzing the complex impedance spectrum of the automotive emergency starting power supply based on the swept-frequency excitation signal includes:

[0046] Analyze the frequency range of the swept-frequency excitation signal;

[0047] When the frequency range meets a preset frequency range threshold, obtain the response data of the automotive emergency starting power supply under the swept-frequency excitation signal, where the response data includes voltage response data and current response data;

[0048] Calculate the complex impedance of the automotive emergency starting power supply according to the voltage response data and the current response data;

[0049] Construct the complex impedance spectrum of the automotive emergency starting power supply according to the complex impedance.

[0050] Optionally, the calculating the complex impedance of the automotive emergency starting power supply according to the voltage response data and the current response data includes:

[0051] Determine the voltage amplitude and voltage phase angle of the automotive emergency starting power supply according to the voltage response data;

[0052] Determine the current amplitude and current phase angle of the automotive emergency starting power supply based on the current response data;

[0053] Based on the voltage amplitude, the voltage phase angle, the current amplitude, and the current phase angle, calculate the complex impedance of the automotive emergency starting power supply using the following formula:

[0054] ;

[0055] where, represents the complex impedance of the automotive emergency starting power supply, represents the voltage amplitude, represents the current amplitude, represents the voltage phase angle, represents the current phase angle, represents the cosine function, represents the sine function, represents the imaginary unit.

[0056] Optionally, extracting the charge transfer resistance Rct and the double-layer capacitance Cdl of the automotive emergency starting power supply according to the complex impedance spectrum using a pre-trained optimized Cole-Cole model includes:

[0057] Define the initialization parameters of the optimized Cole-Cole model;

[0058] According to the complex impedance spectrum and the initialization parameters, fit the optimized Cole-Cole model to obtain a fitted Cole-Cole model;

[0059] Construct a fitting curve of the fitted Cole-Cole model;

[0060] Analyze the convergence coefficient of the fitting curve;

[0061] According to the convergence coefficient, extract the charge transfer resistance Rct and the double-layer capacitance Cdl in the fitted Cole-Cole model.

[0062] To solve the above problems, the present invention also provides a monitoring system for an automotive emergency starting power supply based on intelligent sensing, and the system includes:

[0063] A multi-source data acquisition module for constructing a multi-source sensor array of the automotive emergency starting power supply and collecting voltage signals, current waveforms, and vibration spectrum data of the emergency starting power supply based on the multi-source sensor array;

[0064] A temperature sensing device configuration module, configured to construct a contact PT100 sensor and a non-contact infrared thermal imager for the automotive emergency starting power supply, and collect the PT100 signal and infrared image of the automotive emergency starting power supply based on the contact PT100 sensor and the non-contact infrared thermal imager;

[0065] A local overheating point analysis module, configured to perform dual-modal fusion on the PT100 signal and the infrared image to obtain a three-dimensional temperature field distribution, and analyze the local overheating point of the automotive emergency starting power supply according to the three-dimensional temperature field distribution;

[0066] A complex impedance spectrum analysis module, configured to synthesize a swept-frequency excitation signal of the automotive emergency starting power supply by using a preset digital direct frequency synthesis algorithm according to the local overheating point, analyze the complex impedance spectrum of the automotive emergency starting power supply based on the swept-frequency excitation signal, and extract the charge transfer resistance Rct and the double-layer capacitance Cdl of the automotive emergency starting power supply by using a pre-trained optimized Cole-Cole model according to the complex impedance spectrum;

[0067] A starting power supply detection module, configured to determine an early warning mechanism for the automotive emergency starting power supply based on the charge transfer resistance Rct, the double-layer capacitance Cdl, the voltage signal, the current waveform, and the vibration spectrum data, and perform effective monitoring of the automotive emergency starting power supply based on the early warning mechanism.

[0068] Compared with the problems in the background art, firstly, the introduction of the multi-source sensor array ensures the synchronous acquisition of voltage signals, current waveforms, and vibration spectrum data, providing rich data support for real-time monitoring of power supply performance. This multi-dimensional data acquisition not only improves the accuracy of fault detection but also helps to detect potential overheating or electrical problems in advance. Secondly, through the dual-modal fusion technology, the PT100 signal is combined with the infrared image to obtain an accurate three-dimensional temperature field distribution, making the positioning of local overheating points more accurate, thus providing an important basis for the thermal management of the power supply. Thirdly, the swept-frequency excitation signal synthesized by using the digital direct frequency synthesis algorithm, combined with the optimized Cole-Cole model, effectively extracts the charge transfer resistance Rct and the double-layer capacitance Cdl. The accurate measurement of these parameters provides a scientific basis for evaluating the health status of the battery and predicting its remaining service life. Finally, the early warning mechanism constructed based on these parameters realizes effective monitoring of the automotive emergency starting power supply. This early warning mechanism can issue alarms in a timely manner to guide users and maintenance personnel to take corresponding measures, thus significantly reducing the risk of power supply failure, extending the service life of the power supply, and ensuring the safe operation of the vehicle. Therefore, the present invention improves the reliability and safety of vehicle starting. Description of the Drawings

[0069] Figure 1 Schematic flowchart of a method for monitoring an emergency starting power supply of an automobile based on intelligent sensing provided by an embodiment of the present invention;

[0070] Figure 2 Schematic diagram of a module for implementing the method for monitoring an emergency starting power supply of an automobile based on intelligent sensing provided by an embodiment of the present invention.

[0071] The implementation, functional features and advantages of the present invention will be further described with reference to the embodiments and the accompanying drawings. Specific embodiments

[0072] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0073] An embodiment of the present application provides a method for monitoring an emergency starting power supply of an automobile based on intelligent sensing. The execution subject of the method for monitoring an emergency starting power supply of an automobile based on intelligent sensing includes, but is not limited to, at least one of electronic devices such as a server, a terminal, etc. that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for monitoring an emergency starting power supply of an automobile based on intelligent sensing can be executed by software or hardware installed on a terminal device or a server device. The server includes, but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc.

[0074] Embodiment 1:

[0075] Refer to Figure 1 As shown, it is a schematic flowchart of a method for monitoring an emergency starting power supply of an automobile based on intelligent sensing provided by an embodiment of the present invention. In this embodiment, the method for monitoring an emergency starting power supply of an automobile based on intelligent sensing includes:

[0076] S1. Construct a multi-source sensor array for the emergency starting power supply of the automobile, and collect voltage signals, current waveforms and vibration spectrum data of the emergency starting power supply based on the multi-source sensor array.

[0077] The construction of the multi-source sensor array for the emergency starting power supply of the automobile in the present invention can provide support for multi-source collection of data of the emergency starting power supply of the automobile. Among them, the multi-source sensor array refers to an array constructed by devices for collecting data of the emergency starting power supply of the automobile.

[0078] Collecting the voltage signals, current waveforms and vibration spectrum data of the emergency starting power supply based on the multi-source sensor array in the present invention can realize comprehensive monitoring of the emergency starting power supply of the automobile and provide a basis for subsequent analysis of the emergency starting power supply.

[0079] Specifically, collecting the voltage signal, current waveform, and vibration spectrum data of the emergency starting power supply based on the multi-source sensor array includes:

[0080] Configuring the acquisition parameters of the multi-source sensor array corresponding to the DAQ acquisition unit;

[0081] According to the acquisition parameters, collecting the output voltage, output current, and vibration data of the emergency starting power supply through the DAQ acquisition unit;

[0082] Converting the output voltage, output current, and vibration data into electrical signals to obtain a voltage signal, a current signal, and a vibration signal;

[0083] Analyzing the current waveform of the emergency starting power supply according to the current signal;

[0084] Analyzing the vibration spectrum data of the emergency starting power supply through the vibration signal.

[0085] Among them, the DAQ acquisition unit refers to an electronic device used to collect data from various sensors or signal sources. The acquisition parameters refer to the parameters set on the DAQ acquisition unit, which are used to define the data acquisition process, such as sampling rate, sampling time, resolution, and other parameters. The output voltage refers to the voltage provided by the emergency starting power supply to the load under normal working conditions. The output current refers to the current provided by the emergency starting power supply to the load under normal working conditions. The vibration data refers to the data reflecting the mechanical vibration situation generated by the power supply during operation. The voltage signal refers to the electrical signal converted by the voltage sensor. The current signal refers to the electrical signal converted by the current sensor. The vibration signal refers to the electrical signal converted by the vibration sensor. The current waveform refers to the graphical representation obtained by analyzing the current signal. The vibration spectrum data refers to the data showing the frequency components of the vibration signal.

[0086] S2. Constructing the contact PT100 sensor and non-contact infrared thermal imager of the automotive emergency starting power supply, and collecting the PT100 signal and infrared image of the automotive emergency starting power supply based on the contact PT100 sensor and non-contact infrared thermal imager.

[0087] It should be explained that the contact PT100 sensor refers to a temperature sensor based on the properties of a platinum resistance temperature detector (RTD), and the non-contact infrared thermal imager refers to a device that uses the infrared radiation emitted by an object to measure its surface temperature.

[0088] Based on the PT100 signal and infrared image of the automotive emergency starting power supply collected by the contact PT100 sensor and the non-contact infrared thermal imager, the temperature data of the automotive emergency starting power supply can be obtained, providing a data basis for subsequent heat analysis.

[0089] Specifically, the collection of the PT100 signal and infrared image of the automotive emergency starting power supply based on the contact PT100 sensor and the non-contact infrared thermal imager includes:

[0090] Analyze the heat-sensitive areas of the automotive emergency starting power supply;

[0091] Integrate the contact PT100 sensor into the heat-sensitive area and calibrate the contact PT100 sensor to obtain a calibrated PT100 sensor;

[0092] Collect the PT100 signal of the automotive emergency starting power supply based on the calibrated PT100 sensor;

[0093] Determine the coordinate position of the non-contact infrared thermal imager;

[0094] According to the coordinate position, analyze the imager field of view of the non-contact infrared thermal imager;

[0095] According to the imager field of view, define the imager parameters of the non-contact infrared thermal imager;

[0096] Based on the imager parameters, use the non-contact infrared thermal imager to collect the infrared image of the automotive emergency starting power supply.

[0097] Among them, the heat-sensitive area refers to the parts of the automotive emergency starting power supply that are particularly sensitive to temperature changes. The heat-sensitive areas include battery units, electronic control units, radiators, connectors, etc. The calibrated PT100 sensor refers to a PT100 sensor that has undergone a calibration process to ensure that its measurement accuracy meets specific standards. The PT100 signal refers to the electrical signal output by the PT100 sensor. The coordinate position refers to the specific position of the non-contact infrared thermal imager in space. The imager field of view refers to the scene range that the infrared thermal imager can capture under the current settings. The imager parameters refer to various parameters required for the infrared thermal imager to collect images, including temperature range, resolution, emissivity, ambient temperature, humidity, distance, etc. The infrared image refers to the image that shows the surface temperature distribution of an object captured by the non-contact infrared thermal imager.

[0098] Further, the analysis of the heat-sensitive areas of the automotive emergency starting power supply includes:

[0099] Obtain the thermal test data of the automotive emergency starting power supply;

[0100] Determine the heat source of the automotive emergency starting power supply;

[0101] Grid the automotive emergency starting power supply to obtain power grid units;

[0102] Analyze the unit hot spot temperature and power change rate of the power grid unit;

[0103] Based on the heat source, the unit hot spot temperature, and the power change rate, calculate the transient thermal resistance of the power grid unit using the following formula:

[0104] ;

[0105] Wherein, represents the transient thermal resistance of the power grid unit at time , represents the unit hot spot temperature of the power grid unit at time , represents the power of the c-th heat source of the power grid unit at time , represents the number of heat sources in the power grid unit, represents the ambient temperature corresponding to the power grid unit, represents the material thermal inertia coefficient, represents the power change rate of the power grid unit at time ;

[0106] Based on the transient thermal resistance, determine the thermally sensitive area of the automotive emergency starting power supply.

[0107] Wherein, the thermal test data refers to the temperature detection data used to analyze the thermally sensitive area of the automotive emergency starting power supply, the heat source refers to the physical process that generates heat inside the power supply, the power grid unit refers to the discretized calculation unit obtained by dividing the power supply in three-dimensional space (typical size 5×5×5mm), the unit hot spot temperature refers to the highest temperature value within a single grid unit, the power change rate refers to the change amount of the heat source power per unit time, the transient thermal resistance refers to the parameter characterizing the instantaneous heat dissipation ability of the unit, the material thermal inertia coefficient refers to the characteristic parameter reflecting the response delay of the material to power change, and the ambient temperature refers to the ambient air temperature 50 cm away from the power supply surface.

[0108] It should be noted that in this application, the transient thermal resistance calculated by the above formula can analyze the thermal sensitivity of the automotive emergency starting power supply grid unit, thereby improving the reliability of the contact PT100 sensor data acquisition. Wherein, Based on Fourier's law of heat conduction, the steady-state temperature rise under unit power is described. Based on the heat capacity effect, the transient thermal lag during rapid power change is characterized.

[0109] S3. Perform dual-modal fusion on the PT100 signal and the infrared image to obtain a three-dimensional temperature field distribution, and analyze the local overheating points of the automotive emergency starting power supply according to the three-dimensional temperature field distribution.

[0110] In the present invention, dual-modal fusion is performed on the PT100 signal and the infrared image to obtain a three-dimensional temperature field distribution, and the three-dimensional temperature field distribution of the automotive emergency starting power supply can be obtained, so as to more deeply understand its thermal behavior.

[0111] Specifically, the performing dual-modal fusion on the PT100 signal and the infrared image to obtain a three-dimensional temperature field distribution includes:

[0112] Preprocess the PT100 signal and the infrared image to obtain a processed PT100 signal and a processed infrared image;

[0113] Perform spatial registration on the processed PT100 signal and the processed infrared image to obtain a registered PT100 signal and a registered infrared image;

[0114] Fuse the registered PT100 signal and the registered infrared image to obtain fused dual-modal data;

[0115] Construct a three-dimensional power model of the automotive emergency starting power supply corresponding to the PT100 signal;

[0116] Map the fused dual-modal data into the three-dimensional power model to obtain the three-dimensional temperature field distribution.

[0117] Among them, the processing of the PT100 signal refers to the temperature data collected by the PT100 sensor after a series of preprocessing steps, and the preprocessing steps include signal cleaning (removing noise and outliers), temperature conversion (converting the resistance value to a temperature value), time synchronization (ensuring the consistency of data collection time), and calibration (ensuring the accuracy of data). The processing of the infrared image refers to the image data collected by the preprocessed infrared thermal imager. The preprocessing steps include image correction (such as lens distortion correction, emissivity correction), image enhancement (improving image contrast and clarity), cropping and scaling (to meet the analysis requirements), and time marking (ensuring the time synchronization of the image with the PT100 signal). The registration of the PT100 signal refers to the result after the process of spatially aligning the PT100 signal with the infrared image. The registered infrared image refers to the infrared image after spatial registration. The fusion of the dual-modal data is the result of combining the registered PT100 signal and infrared image data. The three-dimensional power model refers to the three-dimensional geometric model of the automotive emergency starting power supply. The three-dimensional temperature field distribution refers to the temperature distribution obtained by fusing the dual-modal data in the three-dimensional power model.

[0118] Optionally, the fusion of the registered PT100 signal and the registered infrared image to obtain the fused dual-modal data can apply multi-sensor data fusion algorithms, such as Kalman filtering, particle filtering, or deep learning methods, to map the temperature information of the PT100 to the corresponding infrared image area.

[0119] According to the three-dimensional temperature field distribution of the present invention, analyzing the local overheating points of the automotive emergency starting power supply can effectively analyze the local overheating points of the automotive emergency starting power supply, thereby improving the reliability and safety of the power supply. Among them, the local overheating point refers to one or several areas in the automotive emergency starting power supply where the temperature is significantly higher than other surrounding areas. Specifically, the local overheating point can be determined according to the design specifications and material characteristics of the power supply to determine the temperature threshold of local overheating.

[0120] S4. According to the local overheating point, use the preset direct digital frequency synthesis algorithm to synthesize the swept-frequency excitation signal of the automotive emergency starting power supply. Based on the swept-frequency excitation signal, analyze the complex impedance spectrum of the automotive emergency starting power supply. According to the complex impedance spectrum, use the pre-trained optimized Cole-Cole model to extract the charge transfer resistance Rct and the double-layer capacitance Cdl of the automotive emergency starting power supply.

[0121] According to the local overheating point of the present invention, using the preset direct digital frequency synthesis algorithm to synthesize the swept-frequency excitation signal of the automotive emergency starting power supply provides a basis for the later complex impedance spectrum analysis.

[0122] Specifically, synthesizing the swept-frequency excitation signal of the automotive emergency starting power supply according to the local overheating point by using a preset digital direct frequency synthesis algorithm includes:

[0123] Determining the component to be excited of the automotive emergency starting power supply according to the local overheating point;

[0124] Determining the excitation signal requirements for the component to be excited;

[0125] Determining the synthesis parameters of the digital direct frequency synthesis algorithm according to the excitation signal requirements;

[0126] Synthesizing the swept-frequency excitation signal of the automotive emergency starting power supply by using the digital direct frequency synthesis algorithm with the synthesis parameters.

[0127] Wherein, the component to be excited refers to a specific part or component in the automotive emergency starting power supply that is identified and requires an excitation signal to be applied for analysis or testing. The excitation signal requirements refer to a series of technical requirements that the excitation signal applied to the component to be excited should meet in order to achieve specific testing or analysis purposes, including the frequency range, amplitude, waveform, duration, sweep rate, etc. of the signal. The digital direct frequency synthesis algorithm refers to a signal synthesis method that uses digital technology to generate signals with arbitrary waveforms and frequencies. The synthesis parameters refer to a set of parameters used to configure the digital direct frequency synthesis algorithm, including the initial frequency, frequency step, frequency upper limit, amplitude, phase offset, sampling rate, etc. The swept-frequency excitation signal refers to a signal whose frequency changes linearly or non-linearly with time and is used to excite the component to be excited during the test to observe its response at different frequencies.

[0128] Based on the swept-frequency excitation signal, the present invention analyzes the complex impedance spectrum of the automotive emergency starting power supply to conduct an in-depth analysis of the performance and health status of the power supply.

[0129] Specifically, analyzing the complex impedance spectrum of the automotive emergency starting power supply based on the swept-frequency excitation signal includes:

[0130] Analyzing the frequency range of the swept-frequency excitation signal;

[0131] When the frequency range meets the preset frequency range threshold, obtaining the response data of the automotive emergency starting power supply under the swept-frequency excitation signal, where the response data includes voltage response data and current response data;

[0132] Calculating the complex impedance of the automotive emergency starting power supply according to the voltage response data and the current response data;

[0133] Constructing the complex impedance spectrum of the automotive emergency starting power supply according to the complex impedance.

[0134] Wherein, the frequency range refers to the frequency interval covered by the swept-frequency excitation signal, the frequency range threshold refers to a preset set of frequency boundaries for determining whether the frequency range of the actual swept-frequency excitation signal is suitable for subsequent analysis, the voltage response data refers to the data of the voltage at the output terminal of the automotive emergency starting power supply or a specific test point changing with time or frequency after the application of the swept-frequency excitation signal, the current response data refers to the data of the current flowing through the automotive emergency starting power supply changing with time or frequency after the application of the swept-frequency excitation signal, the complex impedance refers to the impedance characteristics of the circuit under the action of an alternating current signal, and the complex impedance spectrum refers to a graph of the complex impedance changing with frequency, which shows the impedance characteristics of the power supply at different frequencies.

[0135] Optionally, to construct the complex impedance spectrum of the automotive emergency starting power supply according to the complex impedance, data analysis and plotting software can be used, with the frequency as the abscissa and the modulus and phase of the complex impedance as the ordinates to plot the complex impedance spectrum graph.

[0136] Further, calculating the complex impedance of the automotive emergency starting power supply according to the voltage response data and the current response data includes:

[0137] Determining the voltage amplitude and voltage phase angle of the automotive emergency starting power supply according to the voltage response data;

[0138] Determining the current amplitude and current phase angle of the automotive emergency starting power supply through the current response data;

[0139] Based on the voltage amplitude, the voltage phase angle, the current amplitude, and the current phase angle, use the following formula to calculate the complex impedance of the automotive emergency starting power supply:

[0140] ;

[0141] Wherein, represents the complex impedance of the automotive emergency starting power supply, represents the voltage amplitude, represents the current amplitude, represents the voltage phase angle, represents the current phase angle, represents the cosine function, represents the sine function, represents the imaginary unit.

[0142] Among them, the voltage amplitude refers to the maximum value of the voltage signal, the voltage phase angle refers to the phase shift of the voltage waveform relative to a reference point (usually the starting point of the current waveform or other signals), the current amplitude refers to the maximum value of the current signal, the current phase angle refers to the phase shift of the current waveform relative to a reference point (usually the starting point of the voltage waveform or other signals), and the imaginary unit refers to a special symbol used in complex number operations, which is .

[0143] According to the complex impedance spectrum, the present invention can effectively extract the charge transfer resistance Rct and the double-layer capacitance Cdl of the automotive emergency starting power supply by using the pre-trained optimized Cole-Cole model, so as to deeply analyze the electrochemical performance of the power supply.

[0144] Specifically, extracting the charge transfer resistance Rct and the double-layer capacitance Cdl of the automotive emergency starting power supply by using the pre-trained optimized Cole-Cole model according to the complex impedance spectrum includes:

[0145] Defining the initial parameters of the optimized Cole-Cole model;

[0146] Fitting the optimized Cole-Cole model according to the complex impedance spectrum and the initial parameters to obtain a fitted Cole-Cole model;

[0147] Constructing a fitted curve of the fitted Cole-Cole model;

[0148] Analyzing the convergence coefficient of the fitted curve;

[0149] Extracting the charge transfer resistance Rct and the double-layer capacitance Cdl in the fitted Cole-Cole model according to the convergence coefficient.

[0150] Among them, the initial parameters refer to the initial values set for the model parameters before fitting the optimized Cole-Cole model. These parameters include the relaxation time constant (τ), the relaxation distribution coefficient (α), the resistance (R), Rct, Cdl, etc. The fitted Cole-Cole model refers to the Cole-Cole model adjusted through the optimization process, and its parameters can best describe the complex impedance spectrum data obtained from experiments. The fitted curve refers to the curve generated according to the fitted Cole-Cole model. The convergence coefficient refers to an index measuring the convergence degree of the fitting algorithm during the iteration process. The charge transfer resistance Rct refers to the resistance of the charge transfer process in the electrochemical reaction, and the double-layer capacitance Cdl refers to the ability of the double layer on the electrochemical interface to store charges.

[0151] Specifically, the optimized Cole-Cole model refers to a model used to describe the impedance characteristics of the electrode reaction in an automotive emergency starting power supply. The optimized Cole-Cole model can better fit the experimental data, thereby more accurately reflecting the electrochemical behavior of the system.

[0152] S5. Based on the charge transfer resistance Rct, the double-layer capacitance Cdl, the voltage signal, the current waveform, and the vibration spectrum data, determine the warning mechanism of the automotive emergency starting power supply, and perform effective monitoring of the automotive emergency starting power supply based on the warning mechanism.

[0153] Based on the charge transfer resistance Rct, the double-layer capacitance Cdl, the voltage signal, the current waveform, and the vibration spectrum data, the present invention determines the warning mechanism of the automotive emergency starting power supply, which can establish a warning system for the automotive emergency starting power supply based on multi-source data, thereby improving the safety and reliability of the battery. The warning mechanism refers to a set of systematic methods that use specific parameters and thresholds to monitor the state of the power supply and issue an alarm when a potential fault or performance degradation is detected. Exemplarily, a primary warning is triggered when it is detected that the double-layer capacitance Cdl drops by more than 15% of the reference value and the fluctuation coefficient of the charge transfer resistance Rct is greater than 20%; when the standard deviation of the voltage fluctuation at the end of charging exceeds 50 mV, it is upgraded to a secondary warning.

[0154] Compared with the problems described in the background art, first, the introduction of the multi-source sensor array ensures the synchronous acquisition of the voltage signal, current waveform, and vibration spectrum data, providing rich data support for real-time monitoring of the power supply performance. This multi-dimensional data acquisition not only improves the accuracy of fault detection but also helps to detect potential overheating or electrical problems in advance. Second, through the dual-modal fusion technology, the PT100 signal is combined with the infrared image to obtain an accurate three-dimensional temperature field distribution, making the positioning of local overheating points more accurate, thereby providing an important basis for the thermal management of the power supply. Third, the swept-frequency excitation signal synthesized by the digital direct frequency synthesis algorithm, combined with the optimized Cole-Cole model, effectively extracts the charge transfer resistance Rct and the double-layer capacitance Cdl. The accurate measurement of these parameters provides a scientific basis for evaluating the health state of the battery and predicting its remaining service life. Finally, the warning mechanism constructed based on these parameters realizes effective monitoring of the automotive emergency starting power supply. This warning mechanism can issue an alarm in a timely manner, guiding users and maintenance personnel to take corresponding measures, thereby significantly reducing the risk of power supply failure, extending the service life of the power supply, and ensuring the safe operation of the vehicle. Therefore, the present invention improves the reliability and safety of vehicle starting.

[0155] Embodiment 2:

[0156] As Figure 2As shown, it is a functional module diagram of an emergency starting power supply monitoring system for automobiles based on intelligent sensing according to the present invention.

[0157] The emergency starting power supply monitoring system 200 for automobiles based on intelligent sensing according to the present invention can be installed in an electronic device. According to the functions achieved, the emergency starting power supply monitoring system based on intelligent sensing may include a multi-source data acquisition module 201, a temperature sensing device configuration module 202, a local overheating point analysis module 203, a complex impedance spectrum analysis module 204, and a starting power supply detection module 205. The modules in the present invention can also be referred to as units, which refer to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, and are stored in the memory of the electronic device.

[0158] In the embodiments of the present invention, the functions of each module / unit are as follows:

[0159] The multi-source data acquisition module 201 is used to construct a multi-source sensor array for the emergency starting power supply of the automobile, and collect voltage signals, current waveforms, and vibration spectrum data of the emergency starting power supply based on the multi-source sensor array;

[0160] The temperature sensing device configuration module 202 is used to construct a contact PT100 sensor and a non-contact infrared thermal imager for the emergency starting power supply of the automobile, and collect PT100 signals and infrared images of the emergency starting power supply of the automobile based on the contact PT100 sensor and the non-contact infrared thermal imager;

[0161] The local overheating point analysis module 203 is used to perform dual-modal fusion on the PT100 signal and the infrared image to obtain a three-dimensional temperature field distribution, and analyze the local overheating points of the emergency starting power supply of the automobile according to the three-dimensional temperature field distribution;

[0162] The complex impedance spectrum analysis module 204 is used to synthesize a swept-frequency excitation signal for the emergency starting power supply of the automobile by using a preset digital direct frequency synthesis algorithm according to the local overheating point, analyze the complex impedance spectrum of the emergency starting power supply of the automobile based on the swept-frequency excitation signal, and extract the charge transfer resistance Rct and the double-layer capacitance Cdl of the emergency starting power supply of the automobile according to the complex impedance spectrum by using a pre-trained optimized Cole-Cole model;

[0163] The starting power supply detection module 205 is used to determine an early warning mechanism for the emergency starting power supply of the automobile based on the charge transfer resistance Rct, the double-layer capacitance Cdl, the voltage signal, the current waveform, and the vibration spectrum data, and perform effective monitoring of the emergency starting power supply of the automobile based on the early warning mechanism.

[0164] Specifically, when the modules in the vehicle emergency starting power supply monitoring system 200 based on intelligent sensing in the embodiments of the present invention are used, they adopt the same technical means as those in the Figure 1 vehicle emergency starting power supply monitoring method based on intelligent sensing described above, and can produce the same technical effects, which will not be elaborated here.

[0165] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and without departing from the spirit or basic characteristics of the present invention, the present invention can be implemented in other specific forms.

[0166] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not restrictive. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A monitoring method for an emergency starting power supply of an automobile based on intelligent sensing, characterized in that, The method includes: Construct a multi-source sensor array for the automotive emergency starting power supply, and collect the voltage signal, current waveform, and vibration spectrum data of the emergency starting power supply based on the multi-source sensor array; Construct a contact PT100 sensor and a non-contact infrared thermal imager for the automotive emergency starting power supply, and collect the PT100 signal and infrared image of the automotive emergency starting power supply based on the contact PT100 sensor and the non-contact infrared thermal imager; Perform dual-modal fusion on the PT100 signal and the infrared image to obtain a three-dimensional temperature field distribution, and analyze the local overheating points of the automotive emergency starting power supply according to the three-dimensional temperature field distribution; According to the local overheating points, synthesize a swept-frequency excitation signal for the automotive emergency starting power supply by using a preset digital direct frequency synthesis algorithm, analyze the complex impedance spectrum of the automotive emergency starting power supply based on the swept-frequency excitation signal, and extract the charge transfer resistance Rct and double-layer capacitance Cdl of the automotive emergency starting power supply according to the complex impedance spectrum by using a pre-trained optimized Cole-Cole model, where the optimized Cole-Cole model is a model used to describe the impedance characteristics of the electrode reaction in the automotive emergency starting power supply; Based on the charge transfer resistance Rct, the double-layer capacitance Cdl, the voltage signal, the current waveform, and the vibration spectrum data, determine the warning mechanism of the automotive emergency starting power supply, and perform effective monitoring of the automotive emergency starting power supply based on the warning mechanism.

2. The method for monitoring an emergency starting power supply of an automobile based on intelligent sensing according to claim 1, wherein, The collecting the voltage signal, current waveform, and vibration spectrum data of the emergency starting power supply based on the multi-source sensor array includes: Configure the acquisition parameters of the multi-source sensor array corresponding to the DAQ acquisition unit; According to the acquisition parameters, collect the output voltage, output current, and vibration data of the emergency starting power supply through the DAQ acquisition unit; Convert the output voltage, output current, and vibration data into electrical signals to obtain a voltage signal, a current signal, and a vibration signal; Analyze the current waveform of the emergency starting power supply according to the current signal; Analyze the vibration spectrum data of the emergency starting power supply through the vibration signal.

3. The method for monitoring an emergency starting power supply of an automobile based on intelligent sensing according to claim 2, wherein The collecting the PT100 signal and infrared image of the automotive emergency starting power supply based on the contact PT100 sensor and the non-contact infrared thermal imager includes: Analyze the heat-sensitive area of the automotive emergency starting power supply; Integrate the contact PT100 sensor into the heat-sensitive area, and calibrate the contact PT100 sensor to obtain a calibrated PT100 sensor; Collect the PT100 signal of the automotive emergency starting power supply based on the calibrated PT100 sensor; Determine the coordinate position of the non-contact infrared thermal imager; Analyze the imager field of view of the non-contact infrared thermal imager according to the coordinate position; Define the imager parameters of the non-contact infrared thermal imager according to the imager field of view; Collect the infrared image of the automotive emergency starting power supply by using the non-contact infrared thermal imager based on the imager parameters.

4. The method for monitoring an emergency starting power supply of an automobile based on intelligent sensing according to claim 3, wherein Analyzing the heat-sensitive area of the automotive emergency starting power supply includes: Obtaining the thermal test data of the automotive emergency starting power supply; Determining the heat source of the automotive emergency starting power supply; Meshing the automotive emergency starting power supply to obtain power grid units; Analyzing the unit hot spot temperature and power change rate of the power grid units; Based on the heat source, the unit hot spot temperature, and the power change rate, calculating the transient thermal resistance of the power grid units using the following formula: ； Among them, represents the transient thermal resistance of the power grid cell at moment, represents the hot spot temperature of the cell of the power grid cell at moment, represents the power of the c-th heat source of the power grid cell at moment, represents the number of heat sources in the power grid cell, represents the ambient temperature corresponding to the power grid cell, represents the material thermal inertia coefficient, represents the power change rate of the power grid cell at moment; Based on the transient thermal resistance, determining the heat-sensitive area of the automotive emergency starting power supply.

5. The method for monitoring an emergency starting power supply of an automobile based on intelligent sensing according to claim 4, characterized in that, The dual-modal fusion of the PT100 signal and the infrared image to obtain a three-dimensional temperature field distribution includes: Preprocessing the PT100 signal and the infrared image to obtain a processed PT100 signal and a processed infrared image; Performing spatial registration on the processed PT100 signal and the processed infrared image to obtain a registered PT100 signal and a registered infrared image; Fusing the registered PT100 signal and the registered infrared image to obtain fused dual-modal data; Constructing a three-dimensional power model of the automotive emergency starting power supply corresponding to the PT100 signal; Mapping the fused dual-modal data into the three-dimensional power model to obtain the three-dimensional temperature field distribution.

6. The method for monitoring an emergency starting power supply of an automobile based on intelligent sensing according to claim 5, wherein, According to the local overheating point, synthesizing a swept-frequency excitation signal of the automotive emergency starting power supply using a preset direct digital frequency synthesis algorithm, including: Determining the components to be excited of the automotive emergency starting power supply according to the local overheating point; Determining the excitation signal requirements of the components to be excited; Determining the synthesis parameters of the direct digital frequency synthesis algorithm according to the excitation signal requirements; Using the synthesis parameters, synthesizing the swept-frequency excitation signal of the automotive emergency starting power supply using the direct digital frequency synthesis algorithm.

7. The method for monitoring an emergency starting power supply of an automobile based on intelligent sensing according to claim 6, wherein Based on the swept-frequency excitation signal, analyzing the complex impedance spectrum of the automotive emergency starting power supply, including: Analyzing the frequency range of the swept-frequency excitation signal; When the frequency range meets a preset frequency range threshold, obtaining the response data of the automotive emergency starting power supply under the swept-frequency excitation signal, where the response data includes voltage response data and current response data; Calculating the complex impedance of the automotive emergency starting power supply according to the voltage response data and the current response data; Constructing the complex impedance spectrum of the automotive emergency starting power supply according to the complex impedance.

8. The method for monitoring an emergency starting power supply of an automobile based on intelligent sensing according to claim 7, characterized in that, Calculating the complex impedance of the automotive emergency starting power supply according to the voltage response data and the current response data, including: Determining the voltage amplitude and voltage phase angle of the automotive emergency starting power supply according to the voltage response data; Determining the current amplitude and current phase angle of the automotive emergency starting power supply through the current response data; Based on the voltage amplitude, the voltage phase angle, the current amplitude, and the current phase angle, calculating the complex impedance of the automotive emergency starting power supply using the following formula: ； Among them, represents the complex impedance of the automotive emergency starting power supply, represents the voltage amplitude, represents the current amplitude, represents the voltage phase angle, represents the current phase angle, represents the cosine function, represents the sine function, represents the imaginary unit.

9. The method for monitoring an emergency starting power supply of an automobile based on intelligent sensing according to claim 8, wherein According to the complex impedance spectrum, using a pre-trained optimized Cole-Cole model to extract the charge transfer resistance Rct and the double-layer capacitance Cdl of the automotive emergency starting power supply, including: Define the initialization parameters of the optimized Cole-Cole model; According to the complex impedance spectrum and the initialization parameters, fit the optimized Cole-Cole model to obtain a fitted Cole-Cole model; Construct a fitting curve of the fitted Cole-Cole model; Analyze the convergence coefficient of the fitting curve; According to the convergence coefficient, extract the charge transfer resistance Rct and double-layer capacitance Cdl in the fitted Cole-Cole model.

10. An emergency start power supply monitoring system for vehicles based on intelligent sensing, characterized in that, The system includes: A multi-source data acquisition module, configured to construct a multi-source sensor array of an automotive emergency starting power supply, and collect voltage signals, current waveforms, and vibration spectrum data of the emergency starting power supply based on the multi-source sensor array; A temperature sensing device configuration module, configured to construct a contact PT100 sensor and a non-contact infrared thermal imager of the automotive emergency starting power supply, and collect PT100 signals and infrared images of the automotive emergency starting power supply based on the contact PT100 sensor and the non-contact infrared thermal imager; A local overheating point analysis module, configured to perform dual-modal fusion on the PT100 signal and the infrared image to obtain a three-dimensional temperature field distribution, and analyze local overheating points of the automotive emergency starting power supply according to the three-dimensional temperature field distribution; A complex impedance spectrum analysis module, configured to synthesize a swept-frequency excitation signal of the automotive emergency starting power supply by using a preset digital direct frequency synthesis algorithm according to the local overheating point, analyze the complex impedance spectrum of the automotive emergency starting power supply based on the swept-frequency excitation signal, and extract the charge transfer resistance Rct and double-layer capacitance Cdl of the automotive emergency starting power supply according to the complex impedance spectrum by using a pre-trained optimized Cole-Cole model, where the optimized Cole-Cole model is a model used to describe the impedance characteristics of electrode reactions in the automotive emergency starting power supply; A starting power supply detection module, configured to determine an early warning mechanism of the automotive emergency starting power supply based on the charge transfer resistance Rct, the double-layer capacitance Cdl, the voltage signal, the current waveform, and the vibration spectrum data, and perform effective monitoring of the automotive emergency starting power supply based on the early warning mechanism.

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