A cooperative control system for an onboard multi-functional electronic control unit

Abstract

This invention relates to the field of collaborative control technology for vehicle-mounted multi-functional electronic control units (ECUs), specifically a collaborative control system for such ECUs, comprising: a multi-modal signal acquisition module that inputs various signals from multiple physical interfaces; a collaborative control module that constructs dynamic load control weights, combines them with various signals for hierarchical decision-making, and outputs a decision control signal and a preparatory signal; a transactional instruction encapsulation module that maps the decision control signal to an operation identifier, and combines the operation identifier with the preparatory signal according to a bit-domain distribution diagram to construct a control data packet; and a closed-loop control execution module that sends the control data packet to initiate a predetermined operation sequence, and when execution timeout or error feedback signal is detected, sends a predetermined rollback sequence to restore the controlled unit to a preset safe state. This invention achieves intelligent decision-making and highly reliable execution of multi-channel, asynchronous control by constructing a collaborative control system that integrates the vehicle's spatial structure and power supply status.

Description

Technical Field

[0001] This invention relates to the field of collaborative control technology for vehicle-mounted multi-functional electronic control units, specifically to a collaborative control system for vehicle-mounted multi-functional electronic control units. Background Technology

[0002] In modified vehicles such as motorhomes, the complex electrical and water systems integrated inside place higher demands on the reliability and intelligence of the program control system. Traditional single control methods, such as mechanical switches or touch screens, are not reliable enough when faced with software failures or electromagnetic interference. Therefore, existing program control logic is mostly a simple superposition of functions and lacks a multi-channel intelligent collaborative framework.

[0003] Existing technical solutions have general limitations at the program control level. For example, the protection logic of the static hardware redundancy solution is passive and fixed, and cannot adapt to dynamically changing operating scenarios; the hardware function integration solution has a highly centralized program, which reduces the flexibility of modification and introduces the risk of single point of failure; and the physical bus bridging solution is limited by the passive parsing of data and cannot achieve active and global collaborative control.

[0004] Therefore, existing program control systems are fragmented and passive in architecture. How to develop a program control system that can achieve dynamic coordination and reliable fault tolerance among multiple control channels is a technical problem that urgently needs to be solved in this field.

[0005] Therefore, this invention proposes a collaborative control system for an on-board multi-functional electronic control unit. Summary of the Invention

[0006] The purpose of this invention is to provide a collaborative control system for an on-board multi-functional electronic control unit. By constructing a collaborative control system that integrates the vehicle's spatial structure and power supply status, intelligent decision-making and highly reliable execution of multi-channel, asynchronous control are achieved.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A collaborative control system for an onboard multi-functional electronic control unit includes:

[0009] The multimodal signal acquisition module receives touch signals, voice signals, mechanical switch signals, and status signals representing the current operating conditions of the double-floor structure motorhome from multiple physical interfaces in real time. The status signals include vehicle space and power supply mode data.

[0010] The collaborative control module constructs dynamic load control weights based on the vehicle space and power supply mode data in the status signals, and combines them with the touch signals, voice signals, and mechanical switch signals to make hierarchical decisions, and outputs decision control signals and backup power supply preparation signals.

[0011] The transactional instruction encapsulation module maps the decision control signal into an operation identifier, and packages the operation identifier together with the preparatory signal as an independent flag bit parameter according to the preset bit field distribution diagram to construct a control data packet adapted to single-frame transmission of CAN bus.

[0012] The closed-loop control execution module is connected to multiple controlled units via a bus, sends the control data packet to start a predetermined operation sequence, and automatically sends a predetermined rollback sequence to restore the multiple controlled units to a preset safe state when an execution timeout is detected or an error feedback signal is received from the controlled unit.

[0013] Preferably, the signals acquired by the multimodal signal acquisition module include:

[0014] The touch signal is a CAN bus data frame; the voice signal is a digital command output after processing by a local offline voice recognition chip; the mechanical switch signal is a continuous analog signal representing the physical travel position, acquired by an analog-to-digital converter.

[0015] The status signals include power supply condition signals characterizing the current power supply mode and spatial status signals related to the double-layer floor structure.

[0016] Preferably, the collaborative control module specifically includes:

[0017] The spatial layered load optimization unit establishes a vertical spatial partition weight library, defines the upper space of the RV as the comfort load zone, and the lower space as the functional load zone; receives the current power supply mode in the status signal, dynamically reconstructs the weight library according to the mode, and outputs the reconstructed weights.

[0018] The predictive power supply switching unit receives power quality precursor indicators from the status signal and outputs a backup power supply preparation signal when the indicators exceed a preset switching threshold.

[0019] The priority decision unit receives the reconstructed weights and the touch signal, voice signal, and mechanical switch signal, executes the preset priority selection logic, and outputs the decision control signal.

[0020] Preferably, the spatial hierarchical load optimization unit includes:

[0021] The vertical spatial partition weight library established by the spatial hierarchical load optimization unit pre-stores original weight values ​​that distinguish the comfort load of the upper space from the functional load of the lower space; the weight library is dynamically reconstructed according to the current power supply mode in the status signal, and the reconstruction rules include:

[0022] When the current power supply mode is detected to be mains power supply mode, the original weight value is retrieved from the weight library and directly output;

[0023] When the current power supply mode is detected to be generator power supply mode, the original weight value of the non-critical load in the comfort load zone is multiplied by a preset weight reduction coefficient, and the reconstructed weight is output.

[0024] When the current power supply mode is detected to be battery power mode, the weights of unnecessary loads in the comfort load zone and functional load zone are set to preset null values, and only the weights of necessary loads are retained as output.

[0025] Preferably, after outputting the backup power supply preparation signal, the predictive power supply switching unit further executes a software phase-locked loop algorithm:

[0026] The software phase-locked loop algorithm processes the voltage signals of a main power supply and a backup power supply in real time, calculates the phase synchronization point at which the voltage phases of the two power supplies are synchronized, and generates a switching control signal based on the phase synchronization point to control the switching action, ensuring that the voltage fluctuation during the switching process is less than a preset safety value.

[0027] Preferably, the priority decision-making unit further includes a health assessment unit:

[0028] The health assessment unit generates a quantified health score for each control channel based on the CAN bus communication packet loss rate of the touch signal, the local offline voice recognition continuous error rate of the voice signal, and the electrical on / off state of the mechanical switch signal. The priority decision unit executes a two-layer arbitration logic, selecting the corresponding signal when the health score of the mechanical switch signal exceeds a preset mandatory threshold, otherwise selecting the signal with the highest health score multiplied by the dynamic load control weight.

[0029] Preferably, the process of mapping the resolution control signal and the preparation signal to operation identifiers, and packaging the operation identifiers and operation parameters according to a preset bit field distribution diagram to construct a control data packet adapted for single-frame transmission on the CAN bus includes:

[0030] According to the resolution control signal, the corresponding operation identifier is retrieved from the preset mapping table. The retrieved operation identifier, the backup power preparation signal as a flag bit parameter, and the operation parameters extracted from the resolution control signal are filled into a specified bit field of a data frame of preset length through bit operations according to the preset bit field distribution diagram. Cyclic redundancy check calculation is performed on the data already filled in the data frame. The calculated check code is written into the reserved check bit field of the data frame to construct a single control data packet.

[0031] Preferably, the closed-loop control execution module specifically comprises:

[0032] The predetermined operation sequence is a queue of multiple control instructions arranged in a time sequence, pre-set to achieve different scenario functions. When executing the predetermined operation sequence, the closed-loop control execution module sequentially sends the control instructions in the queue to multiple controlled units, and after sending the instructions, it determines the execution status of the instructions by monitoring execution timeout and error feedback signals. When an instruction is confirmed to have been successfully executed, the module continues to send the next control instruction in the queue. If a fault is detected during the execution of any instruction, the subsequent execution of the predetermined operation sequence is immediately stopped, and the corresponding predetermined rollback sequence is automatically started. The predetermined rollback sequence is an independent set of instructions used to drive the relevant controlled units to perform reverse operations, which can restore the controlled units to a predetermined safe position.

[0033] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0034] 1. This invention encapsulates complex, multi-step operations into a single CAN bus data packet with transaction rollback capability through atomic instruction encapsulation and closed-loop execution mechanism, reducing the risk of vehicles entering uncertain and dangerous states due to communication errors or execution failures.

[0035] 2. This invention uses the vehicle's physical spatial structure (two-layer) and real-time operating conditions (power supply mode, mains power quality) as inputs to the control program, realizing a paradigm shift from passive, rule-based responses to proactive, scenario-based dynamic decision-making intelligent collaborative control, significantly improving energy efficiency and user experience.

[0036] 3. This invention performs real-time health assessment and dynamic priority arbitration on multiple control channels such as touch, voice, and mechanical switches. This ensures that even if the performance of any electronic control channel degrades or fails, the system can still autonomously select the most reliable channel for control and retains the highest mandatory takeover authority of the mechanical switch, thus providing a safety guarantee. Attached Figure Description

[0037] Figure 1This is a diagram illustrating the collaborative control system architecture of a vehicle-mounted multi-functional electronic control unit according to the present invention.

[0038] Figure 2 This is a schematic diagram of spatial load partitioning and dynamic weight adjustment according to an embodiment of the present invention;

[0039] Figure 3 This is a bit field distribution diagram of a single frame control data packet on the CAN bus according to an embodiment of the present invention. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Other embodiments obtained by those skilled in the art based on the ideas in this specification without creative effort all fall within the protection scope of this invention.

[0041] Reference Figures 1 to 3 This paper presents a collaborative control system for an onboard multi-functional electronic control unit.

[0042] Example 1:

[0043] Reference Figure 1 A collaborative control system for an onboard multi-functional electronic control unit, comprising:

[0044] The multimodal signal acquisition module receives touch signals, voice signals, mechanical switch signals, and status signals representing the current operating conditions of the double-floor structure motorhome from multiple physical interfaces in real time. The status signals include vehicle space and power supply mode data.

[0045] The collaborative control module constructs dynamic load control weights based on the vehicle space and power supply mode data in the status signals, and combines them with the touch signals, voice signals, and mechanical switch signals to make hierarchical decisions, and outputs decision control signals and backup power supply preparation signals.

[0046] The transactional instruction encapsulation module maps the decision control signal into an operation identifier, and packages the operation identifier together with the preparatory signal as an independent flag bit parameter according to the preset bit field distribution diagram to construct a control data packet adapted to single-frame transmission of CAN bus.

[0047] The closed-loop control execution module is connected to multiple controlled units via a bus, sends the control data packet to start a predetermined operation sequence, and automatically sends a predetermined rollback sequence to restore the multiple controlled units to a preset safe state when an execution timeout is detected or an error feedback signal is received from the controlled unit.

[0048] Furthermore, the signals acquired by the multimodal signal acquisition module include: the touch signal is a CAN bus data frame; the voice signal is a digital command output after processing by a local offline voice recognition chip; and the mechanical switch signal is a continuous analog signal representing the physical travel position acquired by an analog-to-digital converter.

[0049] The status signals include power supply condition signals characterizing the current power supply mode and spatial status signals related to the double-layer floor structure.

[0050] Specifically, the touch signals are acquired in the form of Controller Area Network (CAN) bus data frames. When an operator performs tapping, swiping, or other operations on the graphical user interface of the smart touchscreen, the touchscreen's embedded processor instantly parses the physical operation into a specific control command and encapsulates the command into one or more standard data frames according to the vehicle network's communication protocol. Each data frame contains an arbitration ID to uniquely identify the target controlled unit and data bytes defining the specific operation. The multimodal signal acquisition module, through its integrated CAN bus controller and transceiver, monitors the data stream on the bus in real time and captures command frames related to the system, parsing their contents.

[0051] The voice signal originates from a purely digital command output after processing by a local offline voice recognition chip. The system captures the operator's voice through one or more microphones, and this raw sound wave signal is directly input to a dedicated offline voice recognition processing unit. At the core of this unit is a dedicated integrated circuit (ASIC) that does not rely on an external network connection; it internally embeds an acoustic model and a preset command dictionary. It independently performs noise reduction, feature extraction, pattern matching, and semantic parsing of the input voice, ultimately outputting a digital code or level signal that precisely corresponds to the preset command. The multimodal signal acquisition module receives this digital command through its general-purpose input / output port or serial communication interface.

[0052] The mechanical switching signal is obtained by high-frequency sampling of a continuous analog signal representing the physical travel position using an analog-to-digital converter (ADC). This is mainly used in physical controllers that require linear or stepless adjustment. The mechanical travel of this controller is linked to a potentiometer whose resistance value changes continuously with the travel, thereby generating an analog voltage proportional to the physical travel position on its voltage divider circuit. The analog-to-digital converter in the multi-mode signal acquisition module continuously converts this voltage signal into a series of high-resolution digital values.

[0053] The acquisition of the status signals specifically includes three aspects: power supply condition signals characterizing the current power supply mode are monitored in real time by various electrical sensors to determine whether the vehicle is in external mains power, generator power supply, or battery inverter power supply mode, and key electrical parameters for each mode are obtained; spatial status signals related to the double-layer floor structure are obtained by limit switches or displacement sensors installed on the lifting mechanism to accurately obtain the specific position status of the floor; and parameter signals characterizing the environment and resources comprehensively cover information such as the temperature inside and outside the vehicle, the liquid level of each water tank, and the precise remaining power of the battery pack, which together constitute a complete picture of the vehicle's operating status.

[0054] Furthermore, as a preferred embodiment, the multimodal signal acquisition module also incorporates an adaptive signal noise reduction mechanism based on historical data statistics. This mechanism is configured to: create an independent noise characteristic file in memory for each input continuous analog signal (e.g., voltage, temperature, and other state signals); during the initial operation phase of the system, calculate and store the statistical baseline parameters of the signal under static conditions as initial noise characteristics by performing high-frequency sampling on the signal; and during normal vehicle operation, continuously update the statistical parameters of the signal in a sliding time window manner, and dynamically adjust the noise covariance matrix in the noise reduction algorithm (e.g., Kalman filtering) according to parameter changes, thereby achieving adaptive filtering of signal noise under different operating conditions.

[0055] Specifically, the mechanism establishes a dynamic profile for each sensor channel. In a "clean" environment where the vehicle is stationary and all equipment is off, the mechanism records, for example, 1,000 sampling points of the battery voltage signal within 10 seconds and calculates its mean and standard deviation. This initial standard deviation is considered the baseline noise level. When the vehicle is in motion, the generator intervenes, introducing new electrical noise. The mechanism continuously recalculates the standard deviation of the voltage signal using a sliding window of 5 seconds. If the new standard deviation is significantly higher than the baseline, the mechanism determines that the system operating conditions have changed and the noise model has changed. It automatically and proportionally increases the process noise covariance (Q) parameter in its internal Kalman filter model. Conversely, when the vehicle is turned off and returns to a static state, the signal fluctuation decreases, and the mechanism correspondingly lowers this parameter.

[0056] Specifically, the statistical parameter is the standard deviation of the signal fluctuation amplitude within a preset time window. The dynamic adjustment rule of this mechanism is as follows: when the standard deviation of the current signal fluctuation amplitude is detected to be larger than the baseline standard deviation when the vehicle is stationary, the value of the noise covariance matrix is ​​increased accordingly according to a preset nonlinear proportional relationship, thereby relaxing the tolerance of the filtering algorithm to process noise.

[0057] The adaptive noise reduction mechanism transforms signal processing from static filtering with fixed parameters to dynamic filtering that can learn and adapt to the changing electrical environment of the vehicle. It automatically identifies and compensates for noise introduced by the start-up and shutdown of different devices, ensuring the smoothest and most accurate data is provided to higher levels under any operating condition, significantly improving the accuracy and reliability of subsequent control decisions.

[0058] This embodiment constructs a comprehensive perception front-end with rich information dimensions and complementary physical characteristics by clearly defining the specific technical forms and acquisition methods of touch, voice, mechanical and status signals. This design not only ensures that the system can comprehensively and accurately capture user intentions and vehicle operating conditions, but more importantly, it provides a high-quality and standardized data foundation for the upper-level control module to realize complex intelligent decision-making based on multi-source information fusion, which is a key prerequisite for improving the intelligence and reliability of the vehicle control system.

[0059] Furthermore, the collaborative control module specifically includes: a spatial hierarchical load optimization unit, which establishes a vertical spatial partition weight library, defines the upper space of the RV as a comfort load zone and the lower space as a functional load zone; receives the current power supply mode in the status signal, dynamically reconstructs the weight library according to the mode, and outputs the reconstructed weights;

[0060] The predictive power supply switching unit receives power quality precursor indicators from the status signal and outputs a backup power supply preparation signal when the indicators exceed a preset switching threshold.

[0061] The priority decision unit receives the reconstructed weights and the touch signal, voice signal, and mechanical switch signal, executes the preset priority selection logic, and outputs the decision control signal.

[0062] Specifically, the spatial hierarchical load optimization unit is the foundation for dynamically adjusting load priorities. This unit establishes and maintains a vertical spatial partition weight library within the system. This weight library is based on a core design principle: according to the vehicle's unique double-layer floor structure, in-vehicle electrical equipment is logically divided into two areas: equipment located on the upper floor and directly related to passenger comfort is defined as the comfort load area, such as ambient lighting and audio-visual entertainment systems; while equipment located on the lower floor or inside the vehicle structure, ensuring the operation of core vehicle functions, is defined as the functional load area, such as water pumps, inverters, and various monitoring sensors. To achieve this division, the weight library pre-stores the attributes of each load in tabular form, as shown in Table 1.

[0063] Table 1: Weight Library Table

[0064]

[0065] This unit continuously receives power supply status signals from the multi-mode signal acquisition module and dynamically reconstructs the original weight values ​​of each load in the weight library based on whether the current power supply mode is mains, generator, or battery. Finally, it outputs a set of reconstructed weights that accurately reflect the current energy strategy for use by the priority decision unit. The dynamic adjustment rules of the weight library are as follows: Figure 2 As shown, it specifically includes:

[0066] In mains power supply mode, the system determines that power resources are sufficient, and all loads operate at their original weight (i.e., full power), and all device icons are highlighted in green.

[0067] In generator power supply mode, in order to save fuel, the system multiplies the weight of upper-level comfort loads (such as ambient lights and TV icons) by a weight reduction factor less than 1 (for example, the value of this factor can be preset to 0.5, that is, the priority is halved, and preferably the value range of the weight reduction factor is 0.3 to 0.7), making them appear yellow, while lower-level functional loads (such as water pumps and battery icons) remain green.

[0068] In battery-powered mode, to ensure core functions to the maximum extent, the system only keeps emergency loads (such as emergency load icons) green, and sets the weight of most upper-level comfort loads (such as ambient lights and TV icons) to 0 (this setting logically temporarily disables these devices, making them unable to be activated), making them appear gray.

[0069] The predictive power switching unit does not passively wait for the main power supply to fail. Instead, it continuously receives and analyzes a set of power quality precursor indicators from the status signals. These precursor indicators are early signals that the main power supply is about to become unstable or fail. For example, when the main power supply is AC mains, the indicators may include the instantaneous drop in grid voltage and frequency deviation; when the main power supply is a battery pack, the indicators may include the slope of the battery terminal voltage drop rate under load. The unit has a preset switching threshold. Once the detected precursor indicators exceed this threshold (for example, when the voltage drop exceeds 15% and lasts for 50 milliseconds, or the battery voltage drop rate exceeds 0.2 volts per second, it is determined that the indicator has exceeded the threshold), the unit will immediately output a backup power supply preparation signal. This signal is sent as a digital flag to the transactional instruction encapsulation module and related power management hardware to prepare for the upcoming seamless power switching.

[0070] Furthermore, before determining whether the power quality precursor index exceeds a preset switching threshold, the predictive power supply switching unit also incorporates an intelligent avoidance mechanism for instantaneous electrical disturbances. This mechanism is configured to: continuously sample the precursor index within a very short time window to form a time series sample; perform pattern matching between the time series sample and a pre-stored characteristic waveform template library representing known instantaneous disturbances (such as the startup of a large inductive load); and only when the time series sample does not match any template and its degradation duration exceeds a preset time length threshold, is the precursor index finally confirmed as valid and the backup power supply preparation signal is output.

[0071] Specifically, the core of this mechanism is to serve as an auxiliary pre-filtering method, aiming to eliminate benign voltage disturbances caused by the startup of specific known loads, thereby reducing the probability of misjudgment caused by such common events. For example, when the vehicle air conditioner compressor starts, the main power supply voltage will experience a sharp but recoverable instantaneous drop within tens to hundreds of milliseconds. This mechanism will capture this voltage waveform sequence of hundreds of milliseconds and compare it with the "air conditioner startup voltage drop" feature waveform stored in the template library (which pre-stores a standard voltage waveform array consisting of hundreds of sampling points. Preferably, the template data can be constructed by continuously collecting voltage signals for 500 milliseconds at a sampling frequency of 1kHz to represent the normal startup characteristics of air conditioners and other equipment). The comparison algorithm (such as dynamic time warping) will calculate the similarity distance between the real-time waveform and each template in the library. The judgment rule for this comparison is: if the calculated similarity distance is less than a preset matching threshold (such as 0.8), it is determined to be a successful match. Therefore, even if the instantaneous voltage value is below the switching threshold, the mechanism will determine that this is a normal instantaneous disturbance because the pattern matching is successful, and will temporarily block the preparatory signal triggered by this disturbance. Conversely, if the voltage remains low, and after comparing with all feature waveforms in the template library, the calculated similarity distance is greater than or equal to the matching threshold (i.e., no known benign disturbance feature can be matched), and the duration of this state exceeds, for example, a time length threshold of 1 second, then the event will be marked as a potential power quality problem that requires further attention, and the preparatory signal will be allowed.

[0072] The instantaneous disturbance avoidance mechanism introduces pattern recognition and time window analysis to provide the system with a method to identify disturbances initiated by specific normal loads. This pre-processing helps reduce the possibility of unnecessary power switching triggered by these known and harmless voltage fluctuations, greatly enhancing the stability of the power supply system and the service life of the power switching equipment, and ensuring the accuracy of the power supply strategy.

[0073] The priority decision-making unit receives two core inputs: first, the real-time reconstructed load weight from the spatial hierarchical load optimization unit; and second, a touch, voice, or mechanical switch signal representing the user's current intent from the multimodal signal acquisition module. Internally, this unit has a set of priority selection logic that correlates the user's operation command with its corresponding load weight, and combines this with the health status of each signal channel (which is assessed by evaluating indicators such as signal loss rate, recognition error rate, or electrical stability to obtain a quantitative score of 0-100, with higher scores indicating better health). Finally, it outputs a unique decision control signal. In this logic, the health score of the mechanical switch signal is checked first to see if it exceeds a preset mandatory threshold (e.g., 95 points). If it does, the signal is unconditionally adopted, achieving the highest priority mandatory intervention. This signal represents the operation the system ultimately decides to execute under the current operating conditions and energy strategy.

[0074] This embodiment decomposes the collaborative control module into three functional units: spatial layering, predictive switching, and priority decision-making. It constructs a logically clear and hierarchically distinct intelligent decision-making architecture. This architecture can dynamically adjust load priorities according to the vehicle's physical spatial layout and real-time power supply mode, and has a forward-looking power failure prediction capability. This design ensures that the system can prioritize the core functional loads when resources are limited or changing, significantly improving energy utilization efficiency and the reliability of vehicle operation.

[0075] Furthermore, the spatial layered load optimization unit includes: a vertical spatial partition weight library established by the spatial layered load optimization unit, which pre-stores original weight values ​​that distinguish the comfort loads of the upper space from the functional loads of the lower space; dynamically reconstructing the weight library according to the current power supply mode in the status signal, the reconstruction rules including: when the current power supply mode is detected to be mains power supply mode, retrieving and directly outputting the original weight values ​​from the weight library; when the current power supply mode is detected to be generator power supply mode, multiplying the original weight values ​​of non-critical loads in the comfort load zone by a preset weight reduction coefficient, and outputting a set of reconstructed weights; when the current power supply mode is detected to be battery power supply mode, setting the weights of non-essential loads in the comfort load zone and functional load zone to a preset null value, and retaining only the weights of essential loads as output.

[0076] Specifically, the core of the spatial hierarchical load optimization unit is a vertical spatial partition weight library pre-configured in non-volatile memory. This weight library stores the original weight values ​​of each controlled electrical device in the vehicle in the form of a data structure. These original weight values ​​are pre-set according to the physical location and functional attributes of the devices, clearly distinguishing between comfort loads installed in the upper space of the vehicle (such as ambient lighting and audio systems) and functional loads installed in the lower space (such as water pumps and power inverters).

[0077] The core task of this unit is to execute a set of explicit dynamic reconfiguration rules on the weight library based on the current power supply mode obtained in real time from the status signals, thereby outputting a set of weights that best suit the current energy situation. The reconfiguration rules include the following three cases:

[0078] In the first scenario, when the current power supply mode is detected to be mains power supply mode, it indicates that the vehicle is connected to a stable and sufficient external power grid. In this mode, the logic of the spatial hierarchical load optimization unit is set to directly retrieve and output the original weight values ​​of all loads from the weight library without any modification. This ensures that when power resources are abundant, all devices can respond to user operations according to their original design priorities, providing users with a complete functional experience.

[0079] In the second scenario, when the current power supply mode is detected to be generator power supply mode, it indicates that the vehicle is relying on its limited fuel to generate electricity. In this mode, the focus of the energy strategy shifts to balancing functional needs and fuel consumption. The unit first identifies all devices belonging to the comfort load zone and pre-marked as "non-critical" (e.g., decorative light strips). Subsequently, the unit retrieves the original weight values ​​of these non-critical comfort loads and multiplies them uniformly by a preset weighting factor less than 1, thereby reducing their weight in priority decision-making. The weights of all other functional loads and critical comfort loads remain unchanged. The unit finally outputs this set of selectively weighted and reconstructed weights.

[0080] In the third scenario, when the current power supply mode is detected to be battery-powered, it indicates that the vehicle is in a state of extreme resource strain, relying solely on stored electrical energy for operation. In this mode, the system's ultimate goal is to maximize the runtime of core functions. The unit will execute the strictest reconfiguration rules: it will identify all loads pre-marked as "non-essential" within the comfort and functional load zones and directly set the weights of these loads to a preset null value, such as zero. This operation logically temporarily masks these non-essential devices, preventing them from being activated. Only the original weight values ​​of those core loads marked as "essential" (such as emergency lighting, communication equipment, and critical sensors) are retained. The unit ultimately outputs this extremely simplified set of weights, containing only the weights of essential loads.

[0081] In one preferred embodiment, the “non-critical” load refers to equipment mainly used to enhance comfort and atmosphere, such as ambient lighting and audio-visual entertainment systems. The preferred value of the preset weighting coefficient is 0.5, and its value range can be set between 0.3 and 0.7. The “non-essential” load further includes high-power kitchen appliances, such as microwave ovens and induction cookers, in addition to the non-critical load.

[0082] This embodiment upgrades load management from static priority to dynamic energy strategy by pre-setting refined weight reconstruction rules for different power supply modes. This design can automatically and hierarchically adjust load permissions according to the sufficiency of power sources. Under the premise of ensuring core functions, it realizes intelligent and differentiated management of comfort and non-essential loads, which greatly improves the energy utilization efficiency and range of vehicles under different operating conditions.

[0083] Furthermore, after outputting the backup power supply preparation signal, the predictive power supply switching unit further executes a software phase-locked loop algorithm:

[0084] The software phase-locked loop algorithm processes the voltage signals of a main power supply and the backup power supply in real time, calculates the phase synchronization point at which the voltage phases of the two power supplies are synchronized, and generates a switching control signal based on the phase synchronization point to control the switching action, ensuring that the voltage fluctuation during the switching process is less than a preset safety value.

[0085] Specifically, after the predictive power supply switching unit completes its forward-looking judgment and outputs the backup power supply preparation signal, the unit will further initiate a control process to optimize the power switching process. The core of this process is to execute a software phase-locked loop algorithm. The purpose of this algorithm is to minimize the electrical impact of the switching action on the load and the switch itself by intelligent timing selection when both the main power supply and the backup power supply are AC power output from sources such as mains power, generators, or inverters.

[0086] Due to the inherent millisecond-level delay in task scheduling and CAN bus communication of the vehicle-mounted multi-function electronic control unit, this software phase-locked loop algorithm achieves impact optimization through a preferred prediction compensation method: the algorithm monitors the voltage waveforms of the main and backup power supplies in real time through high-frequency sampling and accurately marks the timestamps of the voltage signals crossing zero. Based on these zero-crossing points and the fixed frequency of the AC power, the algorithm can accurately predict the arrival times of a series of future voltage waveform zero-crossing points.

[0087] To compensate for the inherent overall delay of the system (including ECU processing, bus transmission, and physical switch action time), the algorithm generates and sends a switching control signal in advance based on a preset overall delay time parameter (e.g., 15 milliseconds). The switching target of the algorithm is not an infinitely small synchronization point, but a "low-voltage switching window" (e.g., ±2 milliseconds before and after the zero crossing) set around a predicted zero crossing point in the future. Through the above delay compensation, the algorithm ensures that the actual action time of the physical switch can fall within this window period with a high probability of extremely low effective voltage value.

[0088] In this way, the method avoids the huge impact and arc caused by switching at voltage peak (the worst moment). Although there is still a brief power interruption at the millisecond level during the switching process, its impact on the load and the electrical loss of the switching switch itself are significantly reduced. Therefore, the present invention greatly improves the smoothness and safety of the power switching process by optimizing the control of the switching timing.

[0089] Furthermore, the priority decision-making unit also includes a health assessment unit:

[0090] The health assessment unit generates a quantified health score for each control channel based on the CAN bus communication packet loss rate of the touch signal, the local offline voice recognition continuous error rate of the voice signal, and the electrical on / off state of the mechanical switch signal. The priority decision unit executes a two-layer arbitration logic, which unconditionally selects the corresponding signal when the health score of the mechanical switch signal exceeds a preset mandatory threshold; otherwise, it selects the signal with the highest health score multiplied by the dynamic load control weight.

[0091] Specifically, the health assessment unit continuously and in parallel monitors the signal quality from the three main control channels. Specifically, it evaluates the stability of the touchscreen control channel based on the CAN bus communication packet loss rate of the touch signals, calculated as the ratio of the number of successfully received data frames to the expected number of received data frames per unit time. Simultaneously, the unit evaluates the effectiveness of the voice control channel based on the local offline speech recognition continuous error rate of the voice signals, calculated by counting the number of consecutive commands issued by the user that were not successfully recognized as valid by the system. Furthermore, the unit also evaluates the integrity of the physical switch control channel by monitoring the electrical on / off state of the mechanical switch signals, such as detecting abnormal voltage fluctuations or unstable contact resistance. Based on these real-time monitored indicators, the health assessment unit generates a quantified, continuously dynamically updated health score for each control channel (touch, voice, mechanical). As a preferred implementation, the quantification rule can be preset as follows: For touch signals, the health score = 100 - (CAN bus communication packet loss rate × 100), where the packet loss rate is calculated in decimal form (for example, when the packet loss rate is 1%, 0.01 is used for calculation, and the score is 99; when the packet loss rate is 5%, 0.05 is used for calculation, and the score linearly decreases from 99 to 95); For voice signals, the evaluation rule for the health score aims to reflect the recent recognition success rate, rather than a simple count of consecutive failures. Specifically, the rule can be set as follows: The initial value of the health score is 100 points. The system maintains a short time window (e.g., 15 seconds). When a voice recognition failure occurs within this time window, the health score decreases by 20 points; conversely, if a recognition success occurs, the score recovers to 10 points (maximum not exceeding 100 points); When the score is lower than a certain preset warning threshold (e.g., 60 points), the system can proactively prompt the user via voice that "the current environment is noisy, which may affect voice recognition," thereby distinguishing channel quality issues from the reliability of the user's intent.

[0092] Subsequently, the priority decision-making unit executes a two-layer arbitration logic based on this health score to output the final decision control signal.

[0093] The first layer of this two-layer arbitration logic is a mandatory arbitration with the highest priority. The unit checks the health score corresponding to the mechanical switch signal in real time. This score is designed to be a very high set value when the switch is working normally, and to drop sharply when an electrical abnormality is detected. If this score exceeds a preset mandatory threshold representing "manual mandatory intervention," for example, when a specific physical switch used to cut off all power in an emergency is pressed, the arbitration logic will ignore all other input signals and weights and unconditionally select the mechanical switch signal as the decision control signal output.

[0094] If the first-level mandatory arbitration is not triggered, the arbitration logic proceeds to the second level, namely weighted selection arbitration. In this level, the unit associates the control signals representing normal operations from the touch, voice, and mechanical channels with their respective health scores and the dynamic load control weights provided by the spatial hierarchical load optimization unit. Specifically, the unit calculates the final priority score for each valid input signal, which is the product of the signal's health score and the load control weight. Finally, the unit selects the signal with the highest final priority score as the decision control signal output.

[0095] This embodiment expands the decision-making basis from a single load weight to a two-dimensional comprehensive evaluation of load weight and source reliability by adding a health assessment unit and a two-layer arbitration logic. This design not only realizes the priority ranking of different control methods, but also dynamically adapts to possible faults or interference in each control channel, ensuring that the system always adopts the most reliable and reasonable control input. In particular, the design of the forced arbitration layer provides the highest authority for manual emergency operations, which greatly enhances the system's security and redundancy.

[0096] Further, the resolution control signal and the preparation signal are mapped to operation identifiers, and the operation identifiers and operation parameters are packaged according to a preset bit field distribution diagram to construct a control data packet adapted for single-frame transmission on the CAN bus, including:

[0097] According to the resolution control signal, the corresponding operation identifier is retrieved from the preset mapping table. The retrieved operation identifier, the backup power preparation signal as a flag bit parameter, and the operation parameters extracted from the resolution control signal are filled into a specified bit field of a data frame of preset length through bit operations according to the preset bit field distribution diagram. Cyclic redundancy check calculation is performed on the data already filled in the data frame, and the calculated check code is written into the reserved check bit field of the data frame to construct a single control data packet.

[0098] Specifically, the first step in the encapsulation process is mapping. The module has a pre-set operation identifier mapping table. This table maps each possible decision control signal (e.g., "turn on the air conditioner" or "adjust the brightness of the lights") to a unique, fixed-length operation identifier in the form of key-value pairs. When the module receives a decision control signal, it uses this signal as an index to retrieve the corresponding operation identifier from the mapping table.

[0099] The second step is packaging. Based on a preset bit field distribution diagram, the module uses a series of bit operations to fill multiple discrete information fields into a specified bit field of a fixed-length (e.g., 8 bytes) data frame. The bit field distribution diagram precisely defines the purpose of each bit or group of bits within the data frame, such as... Figure 3 As shown, the data frame structure is divided from high to low bits as follows: an arbitration ID for network routing (e.g., occupying 29 bits), a 16-bit operation identifier for defining specific operations, a single-bit standby signal flag for characterizing power status, a 10-bit operation parameter for carrying specific values, and an 8-bit CRC checksum for ensuring data integrity. The module performs the following operations: filling the operation identifier retrieved in the previous step into the bit field in the data frame used to define the instruction type; filling the received backup power standby signal (which is itself a single-bit flag parameter) into a specially reserved status flag bit field in the data frame; and extracting the specific operation parameters from the decision control signal (e.g., a target brightness value of 75% or a target temperature of 22 degrees Celsius) and filling them into the bit field in the data frame used to define the instruction parameters.

[0100] The third step is verification. After all data bit fields are filled, the module performs a cyclic redundancy check (CRC) calculation on all filled data portions in the data frame. This calculation generates a fixed-length check code. Finally, the module writes the calculated check code into the reserved check bit field of the data frame. At this point, a single control data packet, which includes instruction type, status flags, operation parameters, and integrity verification and is adapted for single-frame transmission on the CAN bus, is completed and ready to be sent to the closed-loop control execution module.

[0101] Furthermore, when monitoring the execution process of the predetermined operation sequence, the closed-loop control execution module also incorporates a predictive fault intervention mechanism based on execution feature signatures. This mechanism is configured to: pre-store a set of healthy execution feature signatures for the controlled unit with mechanical motion (e.g., lifting floor, electric pedal), where the signature is a curve showing the change of the readings of its key sensors (e.g., motor current sensor) over time during normal operation; during operation, collect the reading sequence of the key sensors in real time and dynamically compare it with the stored healthy signatures; if the deviation between the real-time reading sequence and the healthy signature exceeds a preset intervention threshold, but before the controlled unit sends an error feedback signal or reaches the execution timeout, actively stop the current operation and trigger the predetermined rollback sequence.

[0102] Specifically, this mechanism establishes a "health model" for key execution components. Taking the raising of a double-layer floor as an example, the system records the complete current change curve of its motor from start-up to locking under unobstructed conditions at the factory and stores it as a "health signature." During a user's daily use, when the floor begins to rise, the mechanism collects the motor current in real time. Assuming that the resistance increases due to slight deformation of the mechanical structure, the real-time current curve will be higher than the healthy signature curve overall. Although the current has not yet reached the hardware threshold for triggering the motor's own overcurrent protection (i.e., the controlled unit has not yet reported an error), the mechanism finds through comparison that the difference in the integral area of ​​the two curves has exceeded the intervention threshold. At this point, the mechanism predicts that continuing execution will most likely lead to jamming or damage, so it will prematurely stop the lifting command and perform a rollback operation. This rollback operation is performed according to an operation rollback mapping table built into the system. This operation rollback mapping table clarifies that the predetermined rollback sequence corresponding to the "raising the floor" operation is "immediately stop the lifting motor, delay for 100 milliseconds, and then execute the floor lowering command." The ultimate goal of this sequence is to restore the floor to its "preset safe state," which is explicitly defined as "the floor is fully lowered and reliably locked by mechanical locking pins," while prompting the user with "abnormal running resistance detected, please check."

[0103] The predictive fault intervention mechanism compares real-time execution data with health feature models. It can identify subtle abnormal signs and intervene in advance before physical faults (such as jamming or overload) fully occur. This proactive intervention capability greatly reduces the risk of equipment damage, improves the safety and reliability of the system, and enables early warning of potential mechanical faults.

[0104] This embodiment efficiently encapsulates complex logical decisions into compact CAN bus data packets through a standardized mapping, packaging, and verification process. By using a preset bit field distribution diagram for bit operations, it can simultaneously carry instructions, parameters, and key status flags within a single data frame, greatly improving the utilization of bus bandwidth and the real-time performance of information transmission. The addition of cyclic redundancy check ensures the integrity and accuracy of instructions during transmission, providing a fundamental guarantee for the reliability of subsequent control execution.

[0105] Furthermore, the closed-loop control execution module specifically comprises:

[0106] The closed-loop control execution module is connected to multiple controlled units via a bus, sends the control data packet to start the predetermined operation sequence, and automatically sends the predetermined rollback sequence to restore the multiple controlled units to a preset safe state when an execution timeout is detected or an error feedback signal is received from the controlled unit.

[0107] Specifically, the predetermined operation sequence is not a single instruction, but an instruction queue containing multiple control instructions arranged in a time sequence, which is pre-fixed in the system to realize different scenario functions (such as "one-click parking" or "preparing to drive"). The instructions in the queue have a strict order to ensure that complex tasks can be executed step by step and safely.

[0108] When the closed-loop control execution module receives a start sequence command, it strictly executes the sequential and conditional control logic. The module retrieves the first instruction from the instruction queue and sends it to the corresponding controlled unit. Then it enters a monitoring waiting state. In this state, the module starts two monitoring mechanisms in parallel: one is timeout monitoring, which starts an internal timer. If no successful feedback is received within a preset time, it is judged as a fault; the other is error feedback monitoring, which continuously listens to the bus and captures error codes actively reported by the controlled unit.

[0109] Only when a clear "execution successful" feedback signal is received before the timer expires will the module confirm that the current instruction has been successfully completed and continue to send the next control instruction in the queue.

[0110] Conversely, if any fault (timeout or error feedback) is detected during the execution of any instruction, the module will immediately suspend the subsequent execution of the entire scheduled operation sequence, and all unsent instructions will be discarded; then, the system will automatically start the scheduled rollback sequence associated with the currently failed instruction.

[0111] The predetermined retraction sequence is an independent set of emergency instructions specifically designed for fault recovery. Its objective is very clear: to drive the relevant controlled units to perform reverse operations (e.g., to fully retract the extending compartment) and ultimately restore it to a preset safe state. The preset safe state is explicitly defined as a state that ensures the safe operation of the vehicle, in which all external movable parts are in their designated retracted positions.

[0112] Through this programmed closed-loop execution and fault recovery mechanism, the present invention ensures that complex multi-step operations are either executed completely and correctly, or can be safely and definitively rolled back to the initial safe state in the event of a fault, thereby greatly improving the reliability and security of the system.

[0113] This embodiment achieves a highly intelligent and reliable vehicle control architecture by constructing a modular system that includes signal acquisition, collaborative control, instruction encapsulation, and closed-loop execution. The system can integrate real-time vehicle operating conditions and multi-mode user input, adjust load priorities in real time, and ensure optimized energy utilization and stable operation of core functions. The use of atomic instruction encapsulation improves bus communication efficiency, while the closed-loop execution mechanism with timeout monitoring and automatic rollback capabilities greatly enhances the system's fault tolerance and safety in the face of abnormal situations, providing a comprehensive intelligent control and safety guarantee solution for double-floor structure motorhomes.

[0114] Example 2:

[0115] This embodiment describes a user driving a double-floor structure motorhome equipped with a collaborative control system of an onboard multi-functional electronic control unit of the present invention, and performing a complete switching process from "driving mode" to "parking camping mode" after arriving at a campsite.

[0116] Initially, the vehicle is in motion, powered by the generator, and the lower layer of the double-layer floor structure is locked. Once the vehicle has come to a stop and the handbrake is engaged, the operator selects the "Parking Camping Mode" option on the smart touchscreen.

[0117] The multimodal signal acquisition module starts working, which recognizes the touch screen's selection operation as a touch signal and packages it into a CAN bus data frame; at the same time, the module continuously acquires and updates status signals to confirm that the current vehicle speed is zero, the handbrake is engaged, the power supply status signal is "generator power supply", and the spatial status signal related to the double-layer floor structure is "lower layer locked".

[0118] Next, all collected signals are sent to the collaborative control module, at which point the operator connects the campsite's external AC power to the vehicle. The predictive power switching unit within the module monitors the AC power connection in real time through status signals and determines that its voltage and frequency are stable. This stable state serves as a precursor to power quality, triggering the unit to output a backup power supply ready signal. In this scenario, this signal explicitly indicates that "AC power is ready." Simultaneously, the spatial hierarchical load optimization unit receives changes in the power supply status signal and, according to its internal rules, retrieves and prepares to output the original weight values ​​of all loads from its weight library when it detects that the power supply mode is about to switch to AC power. The priority decision unit receives the initial "parking camping mode" touch signal, the ready signal representing AC power readiness, and the weights to be updated. The arbitration logic determines that the current highest priority task is to switch to the more economical AC power, and therefore outputs a "execute power switching" decision control signal.

[0119] The transactional instruction encapsulation module receives the decision control signal of "execute power switching" and the preparation signal of "mains power ready" as a flag bit parameter. The module retrieves the operation identifier corresponding to "execute power switching" according to the preset mapping table. Then, according to the preset bit field distribution diagram, the module fills the operation identifier and the preparation signal flag bit into a specified bit field of a data frame through bit operations to construct a control data packet.

[0120] Finally, the closed-loop control execution module sends the control data packet to the power management unit via the bus. After the power supply is successfully switched to mains power, the collaborative control module continues to execute the predetermined operation sequence of the "parking camping mode" and outputs the next decision control signal for "raising the upper floor". This signal is processed again by the transactional instruction encapsulation module and then sent by the closed-loop control execution module to the floor lifting actuator. After sending the instruction, the closed-loop control execution module enters the monitoring state. If the floor is blocked by an obstacle during the lifting process, the lifting actuator (as the controlled unit) will immediately send an error feedback signal. Upon receiving the error signal, the closed-loop control execution module immediately stops the current predetermined operation sequence and automatically retrieves the corresponding predetermined backoff sequence "lowering the floor to the initial safe state", encapsulates it into a new control data packet and sends it, instructing the floor to return to the safe position, thus completing a complete closed-loop control process with safety redundancy.

[0121] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be determined by the scope of protection defined in the claims.

Claims

1. A collaborative control system for a vehicle-mounted multi-functional electronic control unit, characterized in that, include: The multimodal signal acquisition module inputs touch signals, voice signals, mechanical switch signals, and status signals representing the current working condition of the double-floor structure RV from multiple physical interfaces in real time. The status signals include vehicle space and power supply mode data, wherein the vehicle space data is the specific location and state of the floor. The collaborative control module establishes a vertical space partition weight library and dynamically reconstructs the vertical space partition weight library based on the power supply mode data in the status signal, generates dynamic load control weights, and combines them with the touch signal, voice signal, and mechanical switch signal to make hierarchical decisions, outputting decision control signals and backup power supply preparation signals. The transactional instruction encapsulation module maps the decision control signal into an operation identifier, and packages the operation identifier together with the preparatory signal as an independent flag bit parameter according to the preset bit field distribution diagram to construct a control data packet adapted to single-frame transmission of CAN bus. The closed-loop control execution module is connected to multiple controlled units via a bus, sends the control data packet to start a predetermined operation sequence, and automatically sends a predetermined rollback sequence to restore the multiple controlled units to a preset safe state when an execution timeout is detected or an error feedback signal is received from the controlled unit.

2. The collaborative control system for a vehicle-mounted multi-functional electronic control unit according to claim 1, characterized in that, The signals acquired by the multimodal signal acquisition module include: the touch signal is a CAN bus data frame; the voice signal is a digital command output after processing by a local offline voice recognition chip; the mechanical switch signal is a continuous analog signal representing the physical travel position acquired by an analog-to-digital converter; and the status signal includes a power supply condition signal representing the current power supply mode and a spatial status signal related to the double-layer floor structure.

3. The collaborative control system for a vehicle-mounted multi-functional electronic control unit according to claim 1, characterized in that, The collaborative control module specifically includes: The spatial layered load optimization unit establishes a vertical spatial partition weight library. Based on the vehicle's double-layer floor structure, the upper space of the RV is defined as the comfort load zone, and the lower space is defined as the functional load zone. It receives the current power supply mode from the status signal and dynamically reconstructs the weight library according to the mode. The dynamic reconstruction is based on preset reconstruction rules. Under different current power supply modes, the load weights in the comfort load zone and the functional load zone are distinguished and processed, and the reconstructed weights are output. The predictive power supply switching unit receives power quality precursor indicators from the status signal and outputs a backup power supply preparation signal when the indicators exceed a preset switching threshold. The priority decision unit receives the reconstructed weights and the touch signal, voice signal, and mechanical switch signal, executes the preset priority selection logic, and outputs the decision control signal.

4. The collaborative control system of a vehicle-mounted multi-functional electronic control unit according to claim 3, characterized in that, The spatial hierarchical load optimization unit includes: a vertical spatial partition weight library established by the spatial hierarchical load optimization unit, which pre-stores original weight values ​​that distinguish the comfort load of the upper space from the functional load of the lower space; and dynamically reconstructs the weight library according to the current power supply mode in the status signal, wherein the reconstruction rules include: When the current power supply mode is detected to be AC ​​power supply mode, the original weight value is retrieved from the weight library and directly output; when the current power supply mode is detected to be generator power supply mode, the original weight value of the non-critical load in the comfort load zone is multiplied by a preset weight reduction coefficient, and the reconstructed weight is output; when the current power supply mode is detected to be battery power supply mode, the weights of the non-essential loads in the comfort load zone and functional load zone are set to preset null values, and only the weights of the essential loads are retained as output.

5. The collaborative control system for a vehicle-mounted multi-functional electronic control unit according to claim 3, characterized in that, After outputting the backup power supply preparation signal, the predictive power supply switching unit further executes a software phase-locked loop algorithm: the software phase-locked loop algorithm processes the voltage signals of the main power supply and the backup power supply in real time, calculates the phase synchronization point at which the voltage phases of the two power supplies are synchronized, and generates a switching control signal for controlling the switching action based on the phase synchronization point, ensuring that the voltage fluctuation during the switching process is less than a preset safety value.

6. The collaborative control system of a vehicle-mounted multi-functional electronic control unit according to claim 3, characterized in that, The priority decision unit also includes a health assessment unit: the health assessment unit generates a quantitative health score for each control channel based on the CAN bus communication packet loss rate of the touch signal, the local offline voice recognition continuous error rate of the voice signal, and the electrical on / off state of the mechanical switch signal. The priority decision unit executes a two-layer arbitration logic. When the health score of the mechanical switch signal exceeds a preset mandatory threshold, the corresponding signal is selected. Otherwise, the signal with the highest health score multiplied by the dynamic load control weight is selected.

7. The collaborative control system for a vehicle-mounted multi-functional electronic control unit according to claim 1, characterized in that, The process of mapping the resolution control signal to an operation identifier and packaging the operation identifier together with the preparation signal as an independent flag bit parameter according to a preset bit field distribution diagram to construct a control data packet adapted for single-frame transmission of CAN bus includes: retrieving the corresponding operation identifier from a preset mapping table according to the resolution control signal; filling the retrieved operation identifier, the backup power preparation signal as a flag bit parameter, and the operation parameters extracted from the resolution control signal into the specified bit field of a data frame of preset length through bit operations according to the preset bit field distribution diagram; performing cyclic redundancy check calculation on the data already filled in the data frame; and writing the calculated check code into the reserved check bit field of the data frame to construct a single control data packet.

8. The collaborative control system for a vehicle-mounted multi-functional electronic control unit according to claim 1, characterized in that, The closed-loop control execution module specifically comprises: a pre-defined operation sequence, which is a queue of multiple control instructions arranged in a time sequence, pre-set to achieve different scenario functions; when executing the pre-defined operation sequence, the closed-loop control execution module sequentially sends the control instructions in the queue to multiple controlled units, and after sending the instructions, it determines the execution status of the instructions by monitoring execution timeout and error feedback signals; when an instruction is confirmed to have been successfully executed, the module continues to send the next control instruction in the queue; if a fault is detected during the execution of any instruction, the subsequent execution of the pre-defined operation sequence is immediately stopped, and the corresponding pre-defined rollback sequence is automatically started; the pre-defined rollback sequence is an independent set of instructions used to drive the relevant controlled units to perform reverse operations, which can restore the controlled units to a predetermined safe state at a certain position.

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