Automobile emergency starting power supply adaptive to different loads

Abstract

The invention discloses an intelligent automobile emergency starting power supply. The power supply comprises an internal energy storage module, an output interface, a main power switch unit, a driving unit, a voltage detection unit, a current detection unit and a microcontroller. The microcontroller can intelligently identify the type of the load and automatically select a starting mode or an auxiliary supply mode. In an automobile starting mode, the power supply temporarily disconnects the main power switch unit, sends out a diagnosis signal, collects a response, and evaluates the health state of an automobile electrical system. Based on this evaluation, the system dynamically adjusts the boot strategy. In the auxiliary supply mode, the power supply provides stable constant-voltage and constant-current output. According to the invention, blind starting and efficiency problems of a traditional emergency starting power supply are effectively solved, and the safety and the intelligent level are obviously improved.

Description

Technical Field

[0001] The present application relates to the field of power supply technology, and specifically to an automobile emergency starting power supply that can intelligently adapt to different load types, perform health diagnosis on the vehicle electrical system, and dynamically adjust the starting strategy. Background Art

[0002] With the increasing popularity of automobiles, jump-start power supplies have become a common auxiliary tool for car owners. Traditional jump-start power supplies typically provide high starting current to help the vehicle start, or provide a stable DC power supply to power onboard electrical appliances. However, existing technologies have the following problems:

[0003] 1. When starting a vehicle, traditional jump-start power supplies are usually unable to sense the actual status of the vehicle's electrical system (e.g., whether the battery is severely discharged, whether the cable has poor contact, whether the starter motor is faulty, etc.). Blindly applying large current may cause overcurrent shock, causing secondary damage to the vehicle's battery, starter motor, wiring harness, and even the vehicle's ECU, and even posing a safety hazard.

[0004] 2. Using a single starting strategy for vehicles in different health states may result in inefficient starting. For example, a direct high-current shock to a severely depleted battery may not be effective and may require multiple attempts.

[0005] 3. Most emergency starting power supplies lack intelligent management of the power supply for vehicle electrical appliances, and may not be able to provide stable constant voltage and constant current output, or lack the necessary protection mechanism;

[0006] 4. Users are unable to know the true cause of vehicle failure, resulting in repair difficulties or unnecessary waste of repair costs.

[0007] Therefore, the existing technology urgently needs an automobile emergency starting power supply that can intelligently diagnose, dynamically optimize the starting process, and provide safe and stable power supply. Summary of the Invention

[0008] The present invention aims to solve the problems of blind starting, low efficiency, single function and possible secondary damage in the existing automobile emergency starting power supply. It provides an automobile emergency starting power supply that is adaptable to different loads, can perform health diagnosis of the vehicle electrical system, dynamically adjust the starting strategy according to the diagnosis results, and at the same time provide stable power supply for the vehicle's electrical appliances.

[0009] To achieve the above objectives, the present invention provides an automobile emergency starting power supply adapted to different loads, comprising:

[0010] Internal energy storage module for storing electrical energy;

[0011] Output interface, used to connect to car batteries or on-board electrical appliances;

[0012] A main power switch unit is arranged in series between the internal energy storage module and the output interface;

[0013] A driving unit, connected to the main power switch unit, for controlling the main power switch unit to be turned on or off;

[0014] A voltage detection unit, used for detecting the voltage of the output interface in real time;

[0015] A current detection unit, configured to detect the current flowing through the output interface in real time;

[0016] A microcontroller is connected to the driving unit, the voltage detection unit, and the current detection unit, respectively, and is configured to implement the following functions:

[0017] (a) when it is detected that the output interface is connected to a load, identifying the load type as a car battery or a vehicle-mounted electrical appliance based on initial detection values ​​of the voltage detection unit and / or the current detection unit;

[0018] (b) Select vehicle starting mode or auxiliary supply mode according to the identified load type;

[0019] (c) when the load is a car battery and the car starting mode is selected, controlling the drive unit to temporarily disconnect the main power switch unit, outputting a diagnostic excitation signal to the output interface through a preset signal path, and collecting response data of the diagnostic excitation signal using the voltage detection unit and the current detection unit;

[0020] (d) analyzing the impedance characteristics and current response of the vehicle electrical system based on the response data to assess the health status of the vehicle electrical system;

[0021] (e) dynamically selecting or adjusting a vehicle startup strategy based on the health status;

[0022] (f) In the auxiliary supply mode, the main power switch unit is controlled to remain in the on state, and the output power is stably adjusted based on the feedback of the voltage detection unit and the current detection unit to provide a constant voltage and constant current output for the connected vehicle electrical appliances.

[0023] Preferably, the diagnostic excitation signal is a sinusoidal sweep signal output sequentially in multiple frequency bands, or a pulse code sequence formed by multiple different duty cycle and frequency combinations; and the diagnostic excitation signal is used to identify contact resistance anomalies, battery internal resistance anomalies or ground faults in the vehicle electrical system.

[0024] Preferably, the microcontroller performs modeling analysis on the diagnostic response data obtained by the voltage detection unit and the current detection unit to evaluate the health status of the vehicle electrical system. The modeling analysis includes: judging at least one of the battery static dark current, cable impedance, and the initial current fluctuation amplitude of the starter motor, and determining whether there is an abnormality in combination with a preset threshold decision strategy.

[0025] Preferably, the modeling analysis includes:

[0026] performing frequency domain analysis and / or time domain feature extraction on the diagnostic response data;

[0027] The frequency domain analysis includes performing Fourier transform or wavelet transform on the diagnostic response data to identify impedance spectrum characteristics of the vehicle electrical system at different frequencies, thereby determining whether the contact resistance is abnormal or the battery internal resistance is abnormal;

[0028] Furthermore, the time domain feature extraction includes analyzing the transient response waveform, attenuation characteristics or ripple characteristics of the diagnostic response data to evaluate the cable impedance, the initial current fluctuation amplitude of the starter motor and whether a ground fault exists.

[0029] Preferably, the microcontroller dynamically selects or adjusts the vehicle startup strategy according to the health status through a three-stage control process:

[0030] The first stage: output trickle current to activate the battery;

[0031] The second stage: output limited current before starting to reduce the impact;

[0032] The third stage: During the startup process, the duty cycle of the main power switch unit is dynamically adjusted so that the output current increases during the compression phase of the engine and decreases during the burst phase, thereby forming a valley-filling coordinated output waveform.

[0033] Preferably, the microcontroller monitors the voltage and current of the output interface in real time during the three-stage control process, and dynamically adjusts the duty cycle of the main power switch unit and / or the output strategy of the internal energy storage module based on the monitoring results.

[0034] Preferably, the voltage detection unit includes a first signal conditioning module, a reference power supply, a resistor R1, a resistor R2 and a resistor R3, one end of the resistor R1 and one end of the resistor R2 are respectively connected to the positive electrode of the output interface, the other end of the resistor R1 is connected to the output end of the reference power supply, the other end of the resistor R2 is connected to one end of the resistor R3, and the other end of the resistor R3 is grounded, the input end of the first signal conditioning module is connected between the resistor R2 and the resistor R3, and the output end of the first signal conditioning module is connected to the input end of the microcontroller;

[0035] The current detection unit includes a second signal conditioning module and a resistor R4, the resistor R4 is connected in series between the negative pole of the output interface and the negative pole of the internal energy storage module, the input end of the second signal conditioning module is connected between the negative pole of the output interface and the resistor R4, and the output end of the second signal conditioning module is connected to the input end of the microcontroller.

[0036] Preferably, when the microcontroller identifies that the load type is a car battery, it further determines the initial voltage state of the battery based on the battery voltage detected by the voltage detection unit, and adjusts the output parameters of the diagnostic excitation signal according to the initial voltage state.

[0037] Preferably, the preset signal path includes: when the main power switch unit is disconnected, connecting the diagnostic signal output end of the microcontroller to the output interface through a signal isolation circuit.

[0038] Preferably, the microcontroller is further configured to:

[0039] Build a specialized adaptive prediction model for vehicle emergency start scenarios;

[0040] The model is learned through multi-source heterogeneous data, wherein the multi-source heterogeneous data includes: historical or multiple collected diagnostic response data, actual result data corresponding to the vehicle startup process, and real-time or historical external environmental parameters;

[0041] The specialized adaptive prediction model is used to identify and predict potential startup risk patterns and optimal startup energy requirements of the vehicle electrical system under specific vehicle and specific environmental conditions;

[0042] Furthermore, based on the predictive evaluation results of the specialized adaptive prediction model, the microcontroller actively adjusts the output parameters of the diagnostic excitation signal and / or proactively optimizes the parameters of the vehicle startup strategy in the vehicle startup mode to maximize the startup success rate and minimize the impact on the vehicle electrical system.

[0043] One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

[0044] 1. By diagnosing the electrical system before starting and dynamically adjusting the starting strategy based on the health status, it effectively avoids secondary damage to the vehicle's electrical system (battery, starter motor, wiring harness, ECU) caused by blind high current shocks, greatly improving operating safety;

[0045] 2. The system can intelligently identify, predict, and dynamically optimize startup strategies (such as three-stage control and valley-filling coordinated output waveforms) for different vehicles, faults, and environmental conditions, greatly improving the vehicle's startup success rate and efficiency.

[0046] 3. The introduction of an adaptive predictive model enables the starting power supply to "learn" vehicle characteristics, achieve predictive optimization, provide more accurate diagnostic results and a better starting experience, and go beyond the simple power supply function of traditional power supplies;

[0047] 4. It can not only start the car intelligently, but also provide a stable power supply with constant voltage and current and protection for the on-board electrical appliances. It is a multi-purpose machine, convenient and practical;

[0048] 5. The diagnostic function can help users preliminarily determine the possible fault types in the vehicle's electrical system (such as abnormal battery internal resistance, poor cable contact), and provide guidance for subsequent maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 Schematic diagram of the circuit structure of the present invention.

[0050] Explanation of the accompanying drawings: 10, internal energy storage module; 20, output interface; 30, main power switch unit; 40, drive unit; 50, voltage detection unit; 60, current detection unit; 70, microcontroller; 80, signal isolation circuit. DETAILED DESCRIPTION

[0051] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0052] like Figure 1 As shown, the automotive emergency starting power supply of this embodiment mainly comprises an internal energy storage module 10, an output interface 20, a main power switch unit 30, a drive unit 40, a voltage detection unit 50, a current detection unit 60, and a microcontroller 70. The modules are electrically or signal-connected to each other to jointly implement the emergency starting and auxiliary power supply functions.

[0053] The internal energy storage module 10 is usually composed of a high-energy-density, high-power-output battery pack, such as a lithium-ion battery pack, a lithium iron phosphate battery pack, or a supercapacitor pack. In a typical vehicle emergency start scenario, in order to meet the instantaneous high-current discharge requirements, the internal energy storage module 10 can use a lithium iron phosphate battery pack, whose nominal voltage is usually between 12.8V and 14.4V, and can provide a peak discharge current of 500A to 2000A or even higher (lasting about 3-5 seconds). The battery management system (BMS) integrated within the internal energy storage module 10 is responsible for the safe charge and discharge management of the battery, the balancing of the single cells, and the overcharge / over-discharge / over-temperature / short-circuit protection functions to ensure the stability and safety of the internal energy storage module 10 under extreme working conditions.

[0054] The output interface 20 provides a connection port for external devices, such as heavy-duty copper battery clamps for connecting to the positive and negative terminals of a car battery, or a plug for connecting to a car's cigarette lighter. To ensure minimal voltage drop and maximum safety during high-current startup, the connector and wires of the output interface 20 should have extremely low contact resistance and high current carrying capacity. For example, they should be designed to withstand instantaneous peak currents of 1000A to 3000A to fully utilize the discharge capacity of the internal energy storage module 10.

[0055] The main power switching unit 30 consists of one or more high-power MOSFETs or IGBTs connected in parallel. These switching devices serve as the current path for the main circuit and must be able to withstand the high currents of kiloamperes generated when starting the vehicle. MOSFETs with extremely low on-resistance are preferred. For example, the on-resistance of a single switching device can be as low as 0.5mΩ or even below 0.2mΩ to minimize conduction losses and heat generation. Connecting multiple switching devices in parallel effectively distributes current and heat, further improving reliability.

[0056] The driver unit 40 is responsible for converting low-level control signals from the microcontroller 70 into high-current, high-voltage (typically 10V-15V) gate drive signals sufficient to quickly and efficiently drive the main power switch unit 30 on and off. The driver unit 40 may include a dedicated gate driver chip with high current sink / source capabilities (e.g., over 2A) to ensure rapid charging and discharging of the MOSFET or IGBT within nanosecond switching times, reducing switching losses. The driver unit 40 also provides appropriate undervoltage lockout and overtemperature protection to protect itself and the main power switch.

[0057] The voltage detection unit 50 is used to accurately detect the voltage of the output interface 20 in real time. The voltage detection unit 50 generally includes a high-precision resistor divider network (for example, composed of R1, R2 and R3), which accurately divides the car battery voltage of up to 16V to 20V to the acceptable input range of the analog-to-digital converter of the microcontroller 70 (for example, 0V to 3.3V or 0V to 5V). For example, a proportional voltage divider of R1 = 100kΩ, R2 = 10kΩ, and R3 = 3.3kΩ can be selected to divide the 16V voltage into the readable range of the analog-to-digital converter. The divided signal will pass through the first signal conditioning module, which is usually a precision operational amplifier (such as a rail-to-rail input / output operational amplifier, such as the OPA340 series) to provide buffering, amplification, level conversion and low-pass filtering functions (for example, a cutoff frequency of 1kHz is achieved through an RC network) to filter out high-frequency noise and ensure the stability and accuracy of voltage sampling.

[0058] The current sensing unit 60 is used to accurately and in real time detect the high current flowing through the output interface 20. This current sensing unit 60 typically employs a low-resistance, high-precision, high-power sampling resistor R4, connected in series with the negative line of the main circuit (e.g., between the negative terminal of the output interface 20 and the negative terminal of the internal energy storage module 10). R4 has a very low resistance, typically between 0.01mΩ and 0.1mΩ, and an accuracy of 1% or even 0.5%, to minimize its own power consumption and heat generation. The inputs of a second signal conditioning module (typically a high-side current sensing amplifier, such as the INA240 series, or a high-precision differential amplifier) ​​are connected to both ends of R4. It amplifies the weak voltage drop generated across R4 (typically in the microvolt to millivolt range) and converts it into a voltage signal (e.g., 0V to 3.3V) that can be read by the analog-to-digital converter of the microcontroller 70. This second signal conditioning module must have a high common-mode rejection ratio (CMRR, e.g., greater than 90dB) to effectively suppress high-voltage common-mode noise.

[0059] The microcontroller 70 is the core control unit of the present invention and is typically a high-performance ARM Cortex-M series single-chip microcomputer (such as the STM32H7 series) or a dedicated DSP (digital signal processor). These controllers have powerful computing capabilities, a variety of communication interfaces (such as I2C, SPI, and UART), and high-precision ADC / DAC functions (for example, 12-bit or 16-bit ADCs with sampling rates of up to 100kHz to 1MHz), sufficient to support complex diagnostic algorithms, control logic, and data processing. It implements the following intelligent functions by running preset firmware programs.

[0060] The microcontroller 70 implements the following core functions by connecting with each detection unit and drive unit:

[0061] (a) Load identification function:

[0062] When the user connects the emergency starting power supply to an external device, the microcontroller 70 immediately obtains the voltage and current values ​​at the time of initial connection through the voltage detection unit 50 and the current detection unit 60;

[0063] By analyzing these initial values, the microcontroller determines the load type, for example:

[0064] If the initial voltage is between 10.0V and 13.5V and there is a static load current fluctuation of 10mA to 100mA, it is preliminarily determined that a car battery is connected;

[0065] If the initial voltage is lower than 8.0V (indicating a deep battery failure) and after applying a small test current (e.g., 1A) for a short time (e.g., 100ms), the load impedance calculated based on the voltage drop is far below the normal range (e.g., less than 50mΩ), then the battery is also determined to require priming.

[0066] If the initial voltage is stable around 5V or 12V and the current is small (e.g. 0.1A to 5A), it is determined that the vehicle electrical appliance is connected;

[0067] This process distinguishes load types by setting preset voltage and current thresholds as well as calculated load impedance thresholds, and may also incorporate short-circuit and open-circuit detection.

[0068] (b) Mode selection function:

[0069] Based on the load type identified in step (a), the microcontroller 70 automatically selects to enter the vehicle starting mode (for the vehicle battery) or the auxiliary power supply mode (for the vehicle electrical appliances). The system can also provide a manual button or display option to allow the user to override the automatic identification result and switch modes.

[0070] (c) Diagnostic stimulus and response acquisition function:

[0071] After the vehicle start mode is selected, in order to ensure the purity and safety of the diagnostic signal, the microcontroller 70 first controls the drive unit 40 to temporarily disconnect the main power switch unit 30;

[0072] Next, the microcontroller 70 outputs a diagnostic excitation signal to the output interface 20 via a preset signal path. This preset signal path connects the diagnostic signal output pin of the microcontroller 70 to the positive terminal of the output interface 20 via a signal isolation circuit 80. The signal isolation circuit 80 can be implemented using a high-speed optocoupler, a digital isolator (such as Analog Devices' ADuM series), or a small-signal transformer, providing electrical isolation exceeding 2500V RMS, effectively isolating the microcontroller from the vehicle's high-voltage environment while ensuring a nanosecond response time for the diagnostic signal.

[0073] The diagnostic excitation signal may be a sinusoidal swept frequency signal output sequentially within multiple frequency bands (e.g., from 1 Hz to 20 kHz, sweeping at a rate of 100 Hz / second, with a signal amplitude controllable between 0.1 V and 1 V peak-to-peak). Alternatively, it may be a pulse code sequence formed by combining multiple different duty cycles (e.g., 10% to 90%) and frequencies (e.g., 10 Hz to 1 kHz);

[0074] While the diagnostic excitation signal is being output, the microcontroller 70 uses the voltage detection unit 50 and the current detection unit 60 to synchronously collect diagnostic response data from the output interface 20. The data sampling frequency is typically set to at least twice the maximum frequency of the diagnostic excitation signal. For example, if the maximum frequency of the excitation signal is 20 kHz, the sampling frequency should be at least 40 kHz, or even higher, to 100 kHz-1 MHz, to ensure complete acquisition of waveform details.

[0075] (d) Vehicle electrical system health status assessment function:

[0076] The microcontroller 70 performs modeling analysis on the diagnostic response data obtained in step (c). The goal of the modeling analysis is to evaluate the health status of the vehicle electrical system and identify potential anomalies;

[0077] The modeling analysis includes judging at least one of the battery static dark current, cable impedance, and starter motor initial current fluctuation amplitude, and determining whether there is an abnormality in combination with a preset threshold decision strategy;

[0078] More specifically, the modeling analysis includes frequency domain analysis and / or time domain feature extraction;

[0079] Frequency domain analysis involves performing a fast Fourier transform or wavelet transform on diagnostic response data. By analyzing the impedance spectrum characteristics of the vehicle's electrical system at different frequencies (i.e., the curve of how the amplitude and phase of the complex impedance change with frequency), abnormal contact resistance and battery internal resistance can be accurately identified. Abnormal contact resistance, such as caused by aging wiring, loose connectors, or corrosion, may result in specific impedance peaks or abnormal phase shifts at higher frequencies (e.g., above 1kHz). These abnormalities can be identified by comparing them with the baseline of a normal impedance spectrum. Abnormal battery internal resistance is a key indicator of battery health. While the internal resistance of a normal battery varies relatively steadily with frequency, the internal resistance of an aged or sulfurized battery can increase abnormally or exhibit nonlinear characteristics within a specific frequency range (e.g., 1Hz-100Hz). Analyzing these characteristics allows the battery's capacity decay and charge-discharge performance to be assessed.

[0080] Time domain feature extraction involves analyzing the transient response waveform (e.g., response speed to diagnostic pulse signals, overshoot / undershoot amplitude, and setup time), attenuation characteristics (e.g., attenuation time constant of an RC charge-discharge loop), or ripple characteristics of the diagnostic response data. These characteristics are used to assess cable impedance, initial current fluctuation amplitude of the starter motor, and ground faults. Cable impedance measures the delay, attenuation, or reflection of a pulse signal propagating through the cable to assess the resistance, inductance, and capacitance of the cable, thereby determining whether the cable is too long, too thin, or damaged. Initial current fluctuation amplitude of the starter motor is determined by applying an excitation signal simulating a starting load and analyzing the smoothness of the current response, peak current, and fluctuation amplitude at the moment of startup. This can indirectly assess the mechanical and electrical condition of the starter motor, such as whether there is bearing wear or a partial winding short circuit. Ground faults are detected by detecting abnormal current loops or the presence of high-frequency, irregular noise ripples in the response signal, thereby determining whether there is a poor grounding or leakage current problem.

[0081] Through the above comprehensive analysis, the microcontroller 70 can generate a detailed vehicle electrical system health status assessment report and can intuitively display the diagnostic results to the user through the display screen, such as "battery life is low (80%)", "main power line contact is poor", "starter motor may have bearing wear", etc.

[0082] (e) Dynamically select or adjust the vehicle startup strategy:

[0083] Based on the health status of the vehicle electrical system assessed in step (d), the microcontroller 70 dynamically selects or adjusts the vehicle startup strategy that best suits the current vehicle condition. For example, for a battery with a low health score (e.g., below 60%) or a deeply discharged battery, the first-stage trickle activation time may be automatically extended (e.g., from the conventional 30 seconds to 2 minutes), or a softer current rise rate may be adopted in the second stage. For a vehicle in good health but with a possible minor fault (e.g., a slightly higher cable impedance), a more aggressive startup strategy may be adopted to overcome the additional resistance.

[0084] The dynamic adjustment is mainly achieved through a three-stage control process:

[0085] Phase 1 (Trickle Activation): The microcontroller 70 outputs a trickle current (e.g., 0.1A to 1A) by precisely controlling the PWM duty cycle of the main power switch unit 30 (e.g., 0.5% to 5%) or through an independent current limiting circuit (e.g., using a linear regulator or a low-power DC-DC converter). This phase, which can last from 30 seconds to 5 minutes, is intended to pre-charge and activate batteries that have been severely depleted or have been unused for a long time, reviving the chemical reactions within the battery, reducing internal resistance and improving its ability to handle high currents.

[0086] Phase 2 (Pre-start Limiting): Before the engine starts (for example, the user presses the start button, or the system detects a vehicle ignition signal), the microcontroller 70 controls the main power switch unit 30 to output a limited current (for example, 50A to 200A). This phase lasts for a short time (for example, 1 to 5 seconds) and is intended to provide a controlled current during the initial startup phase to prevent sudden high current shocks to the battery and starter motor, while also providing a smooth energy preparation for the starter motor. The current rise rate can be controlled by the PWM slope.

[0087] The third stage (dynamic valley-filling coordinated output): During the actual engine starting process, the microcontroller 70 monitors the voltage and current of the output interface 20 in real time at a high frequency (for example, a PWM frequency of 10kHz to 50kHz). Based on these monitoring results, the duty cycle of the main power switch unit 30 is dynamically adjusted through a feedback control algorithm (such as a PID controller, a fuzzy logic controller, or an adaptive controller). Its core strategy is to increase the output current during the engine compression phase (when the engine resistance is the largest, the maximum torque is required, and the output current can reach 500A to 1500A), and decrease it during the burst phase (the engine resistance is reduced, the current demand is reduced, and the current can be reduced to 100A to 300A). This "valley-filling" current output waveform can more efficiently match the engine's power cycle, achieve maximum energy utilization, and minimize the impact on the starter motor and battery, thereby achieving a smoother and faster start. At the same time, the microcontroller can also dynamically adjust the output strategy of the internal energy storage module 10 (for example, by adjusting the parameters of its internal DC-DC boost or buck converter so that its output voltage can be fine-tuned according to real-time load requirements) to better match the energy requirements of different startup stages.

[0088] (f) Auxiliary supply mode control function:

[0089] In auxiliary power supply mode, the microcontroller 70 controls the main power switch unit 30 to remain in the on state, serving as a stable power source for the vehicle electrical appliances;

[0090] The microcontroller 70 continuously receives feedback from the voltage detection unit 50 and the current detection unit 60 (typically with a sampling frequency of 1 kHz). Based on this feedback, it uses a closed-loop control algorithm (such as PID control of the voltage loop and the current loop) to stably adjust the output power. This ensures that a constant voltage output (e.g., 12V DC ± 0.1V or 5V DC ± 0.05V) and / or a constant current output (e.g., adjustable from 0.5A to 10A) is provided to the connected on-board electrical appliances.

[0091] In addition, in the auxiliary supply mode, the microcontroller 70 is also configured to automatically and quickly disconnect the main power switch unit 30 to protect the equipment and the connected electrical appliances when it detects that the current of the connected on-board electrical appliances increases abnormally (for example, exceeds 15A for 1 second, i.e., overcurrent protection) or the voltage decreases abnormally (for example, is lower than 10V for 500ms, i.e., undervoltage protection).

[0092] In order to further improve the intelligence and effectiveness of the startup, the microcontroller 70 is also configured to build a specialized adaptive prediction model for automobile emergency startup scenarios. The model can be initially trained with a large amount of real vehicle data before the product leaves the factory, and during actual user use, continuous online or offline fine-tuning (or incremental learning) can be performed by collecting new data to continuously improve the model performance.

[0093] The model is learned from heterogeneous data from multiple sources. This data is the basis for model learning and prediction, and its sources and types are as follows:

[0094] Historical or multiple acquisitions of the diagnostic response data: This includes frequency domain analysis results (such as the amplitude and phase curves of the impedance spectrum, impedance values ​​at specific frequencies) and / or time domain feature extraction results (such as transient response time to pulse excitation, decay time constant, specific current ripple characteristics) obtained during each diagnosis. This data is the digital fingerprint of the "intrinsic" health status of the vehicle electrical system;

[0095] Actual results data corresponding to the vehicle starting process: After each start attempt, the microcontroller 70 records a series of quantitative starting performance indicators as feedback for the model. This includes whether the start was successful (binary classification, success / failure), how long the start lasted (e.g., 1 to 10 seconds), the rate of recovery of the vehicle battery voltage after starting (e.g., the percentage of the voltage returning to the nominal voltage within 5 seconds after the start), and (if supported by the system) the initial engine starting speed (e.g., estimated by analyzing the periodicity of the starting current waveform). These data reflect the "actual starting effect";

[0096] Real-time or historical external environmental parameters: For example, ambient temperature data obtained by the built-in temperature sensor (accuracy ±1°C) and ambient humidity data obtained by the humidity sensor (accuracy ±5%RH). In addition, user-entered geographic altitude information can also be considered (altitude affects air density, which in turn affects engine starting resistance).

[0097] The specialized adaptive prediction model may be a support vector machine (SVM), a decision tree, a lightweight neural network (such as a single-layer perceptron or a small multi-layer perceptron), or an adaptive regression model based on Kalman filtering or recursive least squares.

[0098] By learning from this multi-source, heterogeneous data, the specialized adaptive prediction model can identify and predict potential startup risk patterns for a vehicle's electrical system under specific vehicle conditions (based on its historical diagnostic and startup performance). For example, the model might predict that in a current low temperature of -10°C, a specific brand or model of vehicle (based on its historical diagnostic data) may face the risk of insufficient starting current due to decreased battery activity and increased oil viscosity.

[0099] The specialized adaptive prediction model can also predict the optimal starting energy requirement by learning from these multi-source heterogeneous data. Based on the predicted risks and vehicle status, it accurately predicts the optimal current waveform (for example, the current peak and duration at different stages), voltage range, and overall energy output strategy required for this start.

[0100] Ultimately, the microcontroller 70 uses the predictive evaluation results of the specialized adaptive prediction model to proactively adjust the output parameters of the diagnostic excitation signal and / or proactively optimize the parameters of the vehicle startup strategy. For example, if the model predicts that a certain cable has a high risk of failure, the microcontroller will focus the frequency sweep range of the diagnostic excitation signal on the high frequency band to more accurately detect cable impedance anomalies. For another example, if the model predicts that the starting motor load may be too large under the current environment, the microcontroller 70 can adjust the initial value and rising slope of the PWM duty cycle based on the prediction before the start of the third stage, or pre-extend the trickle activation time of the first stage. This prediction and proactive optimization mechanism is designed to maximize the startup success rate and minimize the impact on the vehicle's electrical system, which is a significant advantage of the present invention over traditional passive diagnosis plus feedback control.

[0101] The voltage detection unit 50 includes a precision voltage divider network (R1, R2, R3), a reference power supply, and a first signal conditioning module. One end of resistor R1 and one end of resistor R2 are both connected to the positive terminal of the output interface 20. The other end of resistor R1 is connected to the output end of a high-precision 2.5V reference power supply (for example, ADR4525, with an accuracy better than 0.1%). The other end of resistor R2 is connected to one end of resistor R3, and the other end of resistor R3 is grounded. The input end of the first signal conditioning module is connected between resistors R2 and R3 (i.e., the middle point of the voltage divider network). The output end of the first signal conditioning module is connected to the input end of the microcontroller 70 (usually an ADC pin). By carefully selecting the resistance values ​​of R1, R2, and R3 (for example, R1 = 100kΩ, R2 = 10kΩ, R3 = 3.3kΩ), an input voltage of up to 20V can be accurately divided to the ADC input range of 0-3.3V. At the same time, the presence of R1 can accurately bias and temperature compensate the voltage divider network in some cases. The first signal conditioning block contains a precision operational amplifier (for example, TI's TLV9002) and an RC low-pass filter consisting of a 1kΩ resistor and a 100nF capacitor to ensure signal stability and noise suppression.

[0102] The current detection unit 60 includes a second signal conditioning module and a low-resistance, high-precision sampling resistor R4. Resistor R4 (for example, 0.05mΩ, rated power 5W, precision 0.5%) is connected in series between the negative electrode of the output interface 20 and the negative electrode of the internal energy storage module 10, and is used to convert a current of up to 2000A into a microvolt-level voltage signal. The input end of the second signal conditioning module is connected to both ends of the resistor R4. The second signal conditioning module generally uses a precision current detection amplifier with a high common-mode voltage (for example, Maxim Integrated's MAX40056 or Analog Devices' AD8210), which can withstand a common-mode voltage of up to 80V and amplify the tiny voltage drop generated on R4 into a voltage signal of 0V to 3.3V, which is output to the ADC pin of the microcontroller 70. The amplifier's gain can be configured based on the current range. For example, for a maximum current of 2000A, if R4 is 0.05mΩ, the maximum voltage drop is 100mV. The amplifier gain can be set to 33, converting 100mV to a 3.3V full-scale signal.

[0103] The automotive jump-start power supply described in this invention addresses the safety, efficiency, and intelligence shortcomings of existing jump-start power supplies by integrating intelligent diagnosis, adaptive control, and predictive optimization technologies. This design possesses significant industrial applicability. Its technical solution can be applied to various automotive jump-start power supply products, providing consumers with safer, more efficient, and intelligent automotive emergency rescue solutions, promising broad market prospects and economic benefits.

[0104] This specification and drawings are merely illustrative of the present application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, this application is intended to include such modifications and variations as fall within the scope of this application and its equivalents.

Claims

1. A car emergency starting power supply adapted to different loads, characterized in that: include: An internal energy storage module (10) for storing electrical energy; An output interface (20) for connecting to a car battery or a car electrical appliance; A main power switch unit (30) is arranged in series between the internal energy storage module (10) and the output interface (20); A driving unit (40) connected to the main power switch unit (30) and used to control the main power switch unit (30) to be turned on or off; A voltage detection unit (50) is used to detect the voltage of the output interface (20) in real time; a current detection unit (60), configured to detect in real time the current flowing through the output interface (20); The microcontroller (70) is connected to the driving unit (40), the voltage detection unit (50) and the current detection unit (60) respectively, and is configured to implement the following functions: (a) when it is detected that the output interface (20) is connected to a load, based on the initial detection values ​​of the voltage detection unit (50) and / or the current detection unit (60), identifying the load type as a car battery or a car electrical appliance; (b) Select vehicle starting mode or auxiliary supply mode according to the identified load type; (c) when the load is a car battery and the car start mode is selected, controlling the drive unit (40) to temporarily disconnect the main power switch unit (30), outputting a diagnostic excitation signal to the output interface (20) via a preset signal path, and collecting response data of the diagnostic excitation signal using the voltage detection unit (50) and the current detection unit (60); (d) analyzing the impedance characteristics and current response of the vehicle electrical system based on the response data to assess the health status of the vehicle electrical system; (e) dynamically selecting or adjusting a vehicle startup strategy based on the health status; (f) In the auxiliary supply mode, the main power switch unit (30) is controlled to maintain a conducting state, and based on the feedback of the voltage detection unit (50) and the current detection unit (60), the output power is stably adjusted to provide a constant voltage and constant current output for the connected on-board electrical appliances.

2. The automobile emergency starting power supply according to claim 1, characterized in that: The diagnostic excitation signal is a sinusoidal swept frequency signal output sequentially in multiple frequency bands, or a pulse code sequence formed by multiple different duty cycle and frequency combinations; and the diagnostic excitation signal is used to identify abnormal contact resistance, abnormal battery internal resistance or ground fault in the vehicle electrical system.

3. The automobile emergency starting power supply according to claim 1, characterized in that: The microcontroller (70) performs modeling analysis on the diagnostic response data acquired by the voltage detection unit (50) and the current detection unit (60) to evaluate the health status of the vehicle electrical system, wherein the modeling analysis includes: judging at least one of the battery static dark current, the cable impedance, and the starter motor initial current fluctuation amplitude, and determining whether an abnormality exists in combination with a preset threshold decision strategy.

4. The automobile emergency starting power supply according to claim 3, characterized in that: The modeling analysis includes: performing frequency domain analysis and / or time domain feature extraction on the diagnostic response data; The frequency domain analysis includes performing Fourier transform or wavelet transform on the diagnostic response data to identify impedance spectrum characteristics of the vehicle electrical system at different frequencies, thereby determining whether the contact resistance is abnormal or the battery internal resistance is abnormal; Furthermore, the time domain feature extraction includes analyzing the transient response waveform, attenuation characteristics or ripple characteristics of the diagnostic response data to evaluate the cable impedance, the initial current fluctuation amplitude of the starter motor and whether a ground fault exists.

5. The automobile emergency starting power supply according to claim 1, characterized in that: When the microcontroller (70) dynamically selects or adjusts the vehicle startup strategy according to the health status, it is achieved through a three-stage control process: The first stage: output trickle current to activate the battery; The second stage: output limited current before starting to reduce the impact; The third stage: dynamically adjusting the duty cycle of the main power switch unit (30) during the startup process so that the output current increases during the engine compression phase and decreases during the burst phase, thereby forming a valley-filling coordinated output waveform.

6. The automobile emergency starting power supply according to claim 5, characterized in that: The microcontroller (70) monitors the voltage and current of the output interface (20) in real time during the three-stage control process, and dynamically adjusts the duty cycle of the main power switch unit (30) and / or the output strategy of the internal energy storage module (10) based on the monitoring results.

7. The automobile emergency starting power supply according to claim 1, characterized in that: The voltage detection unit (50) includes a first signal conditioning module, a reference power supply, a resistor R1, a resistor R2, and a resistor R3, one end of the resistor R1 and one end of the resistor R2 are respectively connected to the positive electrode of the output interface (20), the other end of the resistor R1 is connected to the output end of the reference power supply, the other end of the resistor R2 is connected to one end of the resistor R3, and the other end of the resistor R3 is grounded, the input end of the first signal conditioning module is connected between the resistor R2 and the resistor R3, and the output end of the first signal conditioning module is connected to the input end of the microcontroller (70); The current detection unit (60) includes a second signal conditioning module and a resistor R4, wherein the resistor R4 is connected in series between the negative electrode of the output interface (20) and the negative electrode of the internal energy storage module (10), the input end of the second signal conditioning module is connected between the negative electrode of the output interface (20) and the resistor R4, and the output end of the second signal conditioning module is connected to the input end of the microcontroller (70).

8. The automobile emergency starting power supply according to claim 1, characterized in that: When the microcontroller (70) identifies that the load type is a car battery, it further determines the initial voltage state of the battery based on the battery voltage detected by the voltage detection unit (50), and adjusts the output parameters of the diagnostic excitation signal according to the initial voltage state.

9. The automobile emergency starting power supply according to claim 1, characterized in that: The preset signal path includes: when the main power switch unit (30) is disconnected, it is used to connect the diagnostic signal output end of the microcontroller (70) to the output interface (20) through a signal isolation circuit (80).

10. The automobile emergency starting power supply according to claim 1, characterized in that: The microcontroller (70) is further configured to: Build a specialized adaptive prediction model for vehicle emergency start scenarios; The model is learned through multi-source heterogeneous data, wherein the multi-source heterogeneous data includes: historical or multiple collected diagnostic response data, actual result data corresponding to the vehicle startup process, and real-time or historical external environmental parameters; The specialized adaptive prediction model is used to identify and predict potential startup risk patterns and optimal startup energy requirements of the vehicle electrical system under specific vehicle and specific environmental conditions; Furthermore, based on the predictive evaluation results of the specialized adaptive prediction model, the microcontroller (70) actively adjusts the output parameters of the diagnostic excitation signal and / or proactively optimizes the parameters of the vehicle startup strategy in the vehicle startup mode, so as to maximize the startup success rate and minimize the impact on the vehicle electrical system.

Images