A dynamic management system and method for power consumption of extended-range motorhome

Abstract

The present invention relates to the field of power management technology, specifically to a dynamic power management system and method for extended-range recreational vehicles, including an environment-internal resistance monitoring module that monitors environmental parameters in real time and measures battery internal resistance, and evaluates the environmental threat level through an environmental threat assessment model; a battery stratified sleep control module that stratifies battery groups and calculates battery health to control sleep depth; a wake-up trigger module that calculates the time required for full battery activation based on historical internal resistance recovery data and determines the wake-up start time; a battery progressive wake-up and stop module that performs stratified progressive wake-up according to the quality of battery internal resistance and determines the number of awakened batteries through power verification; and a battery re-sleep module that dynamically corrects battery health and sleep depth based on real-time battery internal resistance combined with accumulated environmental damage, and puts the remaining batteries back into sleep. The present invention can achieve collaborative power management and dynamic battery protection for multiple extended-range recreational vehicles in extreme environments.

Description

Technical Field

[0001] The present invention relates to the technical field of power management, and in particular to a dynamic power management system and method for an extended-range motorhome. Background Art

[0002] With the widespread adoption of portable energy systems in travel scenarios, power management systems based on extended-range energy replenishment are gaining increasing attention due to their advantages, such as long battery life and environmental performance. Existing power management systems typically include energy storage battery packs, range-extending power modules, battery management systems (BMS), and power distribution control units. These components provide multi-load output, intelligent power scheduling, and optimized energy storage management.

[0003] However, these systems still face the following challenges in actual operation: First, they lack protection mechanisms for energy storage units in complex external environments (such as high temperature, high humidity, and extreme cold). Traditional BMS systems are unable to dynamically adjust the battery pack's charge and discharge strategies based on environmental variables, leading to battery performance degradation and even safety hazards, affecting the stability of the overall power supply system. Second, most current portable power systems operate independently, lacking a mechanism for sharing power resources. When multiple systems are deployed in the same operating area or temporary campsite, power coordination and load balancing between the systems are impossible. This often results in some equipment experiencing power redundancy while others experience power shortages, leading to inefficient energy allocation. Especially in scenarios such as outdoor camping, RVers often face the dual challenges of a lack of charging facilities and harsh environmental conditions.

[0004] Therefore, how to achieve coordinated power management and dynamic battery protection of multiple extended-range mobile vehicles under extreme environmental conditions is an urgent problem to be solved.

[0005] To this end, a dynamic power management system and method for an extended-range motorhome is proposed. Summary of the Invention

[0006] The purpose of the present invention is to provide a dynamic power management system and method for extended-range motorhomes, which can achieve coordinated power management and dynamic battery protection of multiple extended-range motorhomes under extreme environmental conditions.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A dynamic power management system for an extended-range motorhome, comprising:

[0009] The environment-internal resistance monitoring module monitors the surrounding environment parameters in real time and measures the battery internal resistance, and assesses the environmental threat level through the environmental threat assessment model;

[0010] The battery hierarchical sleep control module divides battery packs into tiers based on environmental threat levels and calculates battery health to control the sleep depth of each tier. It also calculates the time required for full battery activation based on historical internal resistance recovery data and determines the wake-up time based on the sleep depth.

[0011] The wake-up trigger module calculates the battery internal resistance change rate based on the battery internal resistance value; when the internal resistance change rate meets the preset wake-up trigger condition, it triggers the formal wake-up based on the wake-up start time;

[0012] The battery progressive wake-up and stop module uses a progressive battery quantity determination strategy. First, the first batch of wake-up batteries are selected based on the battery internal resistance and battery health, and the power gap is evaluated. If the power gap is positive, the number of batteries is progressively increased. If the power gap is negative for N consecutive times, the number of batteries is stopped.

[0013] The battery re-hibernation module dynamically corrects the battery health and hibernation depth based on the real-time battery internal resistance value and the accumulated environmental damage, and puts the remaining batteries back into hibernation.

[0014] Preferably, the environmental threat assessment model comprises: an environmental parameter input unit, a parameter standardization processing unit and an environmental threat level assessment unit;

[0015] The environmental parameter input unit inputs the real-time monitored environmental parameters, including the temperature, humidity, air pressure and ultraviolet intensity around the RV; the parameter standardization processing unit standardizes the environmental parameters, compares them with the battery's optimal working environment parameters, and calculates the deviation values ​​of each environmental parameter; the environmental threat level assessment unit uses the weighted summation method to numerically assess the environmental threat level based on the deviation values ​​of each environmental parameter, and divides the environment into safe, warning, dangerous and extremely dangerous according to the environmental threat level.

[0016] Preferably, the process of determining the wake-up start time is:

[0017] The battery pack is divided into three layers according to the environmental threat level: when the environmental threat level is safe and / or warning, the battery pack is set as the working layer; when the environmental threat level is dangerous, the battery pack is set as the buffer layer; when the environmental threat level is critical, the battery pack is set as the core protection layer; the battery health is calculated based on the battery internal resistance, state of charge and temperature coefficient; wherein the temperature coefficient is determined according to the current temperature around the RV;

[0018] The sleep depth is determined according to the battery health and the level of the battery pack, including shallow sleep for the working layer, moderate sleep for the buffer layer, and deep sleep for the core protection layer; the battery full activation time is calculated based on historical internal resistance recovery data, sleep depth coefficient and temperature correction coefficient; wherein, the sleep depth coefficient is determined based on the sleep depth of the level of the battery pack; the temperature correction coefficient is corrected according to the temperature change around the current RV; based on the battery full activation time, combined with the power demand forecast time and setting a safety buffer time, the wake-up start time is determined.

[0019] Preferably, the preset wake-up triggering conditions include:

[0020] When the internal resistance change rate turns from negative to positive and is greater than the preset environmental improvement threshold for M consecutive measurements, it is determined that the environment begins to improve; based on the real-time environmental parameters when the environment begins to improve, the internal resistance stability detection threshold is set; when the absolute value of the internal resistance change rate is less than the internal resistance stability detection threshold, and the difference between the current battery internal resistance value and the standard working internal resistance value is less than the preset internal resistance difference threshold and lasts for a preset time, it is confirmed that the environmental conditions are stable and a formal wake-up is triggered.

[0021] Preferably, the progressive battery quantity determination strategy includes:

[0022] The first batch of wake-up batteries are screened based on the battery internal resistance value and battery health, and the output power and internal resistance changes of the first batch of wake-up batteries are continuously monitored to evaluate the power gap; if the power gap is positive, the remaining power demand is calculated; based on the battery internal resistance value, battery health and remaining power demand, the next batch of wake-up batteries are selected, and the power gap is evaluated again; if the power gap is negative for N consecutive times, stop adding batteries; for each batch of wake-up batteries, the batteries with the internal resistance value that best matches the standard working internal resistance value and the highest battery health are selected for wake-up first; establish a battery rotation mechanism, and when the internal resistance change of the working battery exceeds the preset working internal resistance change threshold, it is replaced with a dormant battery.

[0023] Preferably, the process of dynamically correcting the battery health and the sleep depth is:

[0024] The internal resistance degradation rate is calculated based on the real-time measured internal resistance value of the battery; the environmental damage accumulation is calculated based on the environmental threat level and exposure time; the battery health is corrected based on the internal resistance degradation rate and the environmental damage accumulation; the hibernation depth is re-determined based on the corrected battery health, and the remaining batteries are put back into hibernation.

[0025] Preferably, a method for dynamic management of power in an extended-range motorhome comprises:

[0026] Real-time monitoring of ambient environmental parameters and measurement of battery internal resistance, and assessment of environmental threat levels using an environmental threat assessment model;

[0027] The battery pack is stratified according to the environmental threat level, and the battery health is calculated to control the sleep depth of each battery layer. The time required for full battery activation is calculated based on historical internal resistance recovery data, and the wake-up start time is determined based on the sleep depth.

[0028] Calculate the battery internal resistance change rate based on the battery internal resistance value; when the internal resistance change rate meets the preset wake-up trigger condition, trigger the formal wake-up based on the wake-up start time;

[0029] A progressive battery quantity determination strategy is adopted. First, the first batch of awakened batteries are selected based on the battery internal resistance and battery health, and the power gap is evaluated. The number of batteries is then progressively added based on the power gap. If the power gap is negative for N consecutive times, the number of batteries is stopped.

[0030] Based on the real-time battery internal resistance value and the accumulated environmental damage, the battery health and sleep depth are dynamically corrected, and the remaining batteries are put back into sleep mode.

[0031] Compared with the prior art, the present invention has the following beneficial effects:

[0032] 1. The present invention can accurately identify extreme environmental conditions that are harmful to batteries by constructing an environmental threat assessment model and a dual monitoring mechanism for battery internal resistance, and implement differentiated hierarchical dormancy protection strategies based on the threat level. By incorporating environmental factors into the protection decision-making system, it can actively enter a deep dormant state in extreme environments such as high temperature, severe cold, and high humidity, effectively avoiding irreversible damage to the battery caused by environmental stress. At the same time, by monitoring the changes in battery internal resistance in real time and dynamically correcting the battery health based on the accumulation of environmental damage, the actual state of each battery can be accurately assessed to ensure that the protection parameters are adjusted in time when the battery performance degrades, avoiding rapid attenuation caused by excessive use. This active and refined protection mechanism significantly extends the service life of the battery in extreme environments and reduces the replacement frequency and maintenance cost of RV batteries.

[0033] 2. The present invention adopts a hierarchical progressive battery wake-up strategy driven by the internal resistance change rate. By monitoring the trend of battery internal resistance changes, the optimal wake-up time is accurately determined, avoiding energy waste caused by premature wake-up and response delay caused by late wake-up. The progressive battery quantity determination strategy can dynamically adjust the number of batteries involved in the work according to the actual load demand. First, the battery with the best performance is activated for power verification, and then the battery is gradually supplemented according to the power gap situation to ensure that both power demand is met and battery resource waste is avoided. This precise configuration strategy can maximize the utilization efficiency of battery resources while meeting the diverse power needs of RVs, reduce unnecessary battery activation, reduce overall system power consumption, and extend the endurance of RVs in an off-grid state. It is particularly suitable for application scenarios such as long-term outdoor camping.

[0034] 3. The present invention designs an adaptive power management mechanism for the complex and changeable environment faced by RVs. Through real-time monitoring of environmental parameters and threat level assessment, it can dynamically adjust the battery management strategy according to environmental changes to ensure that a stable power supply can be maintained under various extreme conditions. The introduction of internal resistance monitoring technology can directly sense the actual state changes of the battery in harsh environments. The battery rotation mechanism and dynamic health correction function ensure the long-term stable operation of the system. When the performance of some batteries degrades due to environmental factors, the backup battery is automatically called and the configuration plan is re-optimized. This multi-level protection mechanism enables the RV power system to maintain a good working condition in the face of various extreme environments such as high temperature in the desert, low pressure on the plateau, and high humidity on the coast, providing users with continuous and reliable power protection, which significantly improves the adaptability and safety of extended-range RVs in harsh environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 A schematic diagram of a dynamic power management system for an extended-range motorhome provided by an embodiment of the present invention;

[0036] Figure 2 A schematic diagram of a process for determining a wake-up start time according to an embodiment of the present invention;

[0037] Figure 3 A schematic diagram of a process for determining the number of batteries in a progressive manner according to an embodiment of the present invention;

[0038] Figure 4 A flowchart of a method for dynamically managing the power consumption of an extended-range motorhome provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0039] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0040] The present invention proposes a dynamic battery management system and method for extended-range motorhomes, which can achieve coordinated battery management and dynamic battery protection for multiple extended-range motorhomes under extreme environmental conditions. The effectiveness of the present invention will be demonstrated in two examples below.

[0041] Example 1:

[0042] In this embodiment, the proposed system was used to dynamically manage the power consumption of three extended-range RVs. These RVs were camped for a week at the edge of a desert, where the daytime temperature reached over 45°C, dropping to below 10°C at night, the relative humidity was extremely low, the ultraviolet light intensity was extremely high, and there was no external power supply. Figure 1 This is a specific structural diagram of the system of the present invention, including: an environment-internal resistance monitoring module, which monitors the surrounding environmental parameters in real time and measures the internal resistance of the battery, and evaluates the environmental threat level through an environmental threat assessment model; a battery stratification sleep control module, which stratifies the battery pack according to the environmental threat level, and calculates the battery health to control the sleep depth of each layer of batteries; calculates the time required for full activation of the battery based on historical internal resistance recovery data, and determines the wake-up start time in combination with the sleep depth; a wake-up trigger module, which calculates the battery internal resistance change rate based on the battery internal resistance value; when the internal resistance change rate meets the preset wake-up trigger condition, triggers the formal wake-up based on the wake-up start time; a battery progressive wake-up and stop module, which adopts a progressive battery quantity determination strategy, firstly screens the first batch of wake-up batteries based on the battery internal resistance value and battery health and evaluates the power gap; if the power gap is positive, the number of batteries is progressively supplemented; if the power gap is negative for N consecutive times, stop adding batteries; a battery re-sleep module, which dynamically corrects the battery health and sleep depth based on the real-time battery internal resistance value combined with the accumulated environmental damage, and puts the remaining batteries back into sleep. The following is based on Figure 1 The following content is described:

[0043] The environment-internal resistance monitoring module monitors the surrounding environmental parameters in real time and measures the battery internal resistance. Specifically, the environmental parameters are collected every five minutes through a temperature sensor, humidity sensor, air pressure sensor, and ultraviolet intensity sensor installed on the RV shell. The battery internal resistance is measured by a micro-current pulse detection circuit that sends microampere detection pulses to the dormant battery every ten minutes.

[0044] Evaluate the environmental threat level through an environmental threat assessment model; the environmental threat assessment model includes: an environmental parameter input unit, a parameter standardization processing unit and an environmental threat level assessment unit;

[0045] The environmental parameter input unit inputs the real-time monitored environmental parameters, including the temperature, humidity, air pressure and ultraviolet intensity around the RV; the parameter standardization processing unit standardizes the environmental parameters, compares them with the battery's optimal working environment parameters, and calculates the deviation values ​​of each environmental parameter; the environmental threat level assessment unit uses the weighted summation method to numerically assess the environmental threat level based on the deviation values ​​of each environmental parameter, and divides the environment into safe, warning, dangerous and extremely dangerous according to the environmental threat level.

[0046] Specifically, the environmental threat level assessment unit obtains the environmental threat level by weightedly summing the temperature deviation value, humidity deviation value, air pressure deviation value, and ultraviolet intensity deviation value; the weight coefficient of the weighted summation is determined according to the battery's sensitivity to different environmental factors, for example, the temperature deviation coefficient is set to the highest weight; in the high temperature environment of the desert, the calculated environmental threat level is an extremely dangerous level.

[0047] By establishing an environmental threat assessment model, an accurate quantitative assessment of complex and extreme environmental conditions is achieved. Multidimensional environmental factors such as temperature, humidity, air pressure, and ultraviolet intensity are uniformly converted into comparable threat level values, providing a scientific stratification basis for the battery stratified sleep control module. Standardization eliminates the impact of differences in the dimensions and numerical ranges of different environmental parameters, ensuring the accuracy and consistency of threat assessment. The weighted summation method is used to achieve a comprehensive multi-factor assessment, providing a reliable environmental benchmark for subsequent wake-up trigger condition setting and battery health correction, thus solving the technical problem that traditional systems cannot accurately assess the degree of complex environmental threats.

[0048] Furthermore, the battery hierarchical sleep control module divides the battery pack into tiers according to the environmental threat level and calculates the battery health to control the sleep depth of each tier. It also calculates the time required for the battery to fully activate based on historical internal resistance recovery data and determines the wake-up start time based on the sleep depth.

[0049] See Figure 2 , the process of determining the wake-up start time is:

[0050] The battery pack is divided into three layers according to the environmental threat level: when the environmental threat level is safe and / or warning, the battery pack is set as the working layer; when the environmental threat level is dangerous, the battery pack is set as the buffer layer; when the environmental threat level is critical, the battery pack is set as the core protection layer; the battery health is calculated based on the battery internal resistance, state of charge and temperature coefficient; wherein the temperature coefficient is determined according to the current temperature around the RV;

[0051] The sleep depth is determined according to the battery health and the level of the battery pack, including shallow sleep for the working layer, moderate sleep for the buffer layer, and deep sleep for the core protection layer; the battery full activation time is calculated based on historical internal resistance recovery data, sleep depth coefficient and temperature correction coefficient; wherein, the sleep depth coefficient is determined based on the sleep depth of the level of the battery pack; the temperature correction coefficient is corrected according to the temperature change around the current RV; based on the battery full activation time, combined with the power demand forecast time and setting a safety buffer time, the wake-up start time is determined.

[0052] Specifically, after detecting that the environmental threat level is extremely dangerous, the 24 battery modules of the RV are reallocated: eight battery modules are set as the core protection layer and adopt deep sleep mode; eight battery modules are set as the buffer layer and adopt moderate sleep mode; the remaining eight battery modules are set as the working layer and adopt shallow sleep or continue working state.

[0053] Battery health is comprehensively assessed based on the battery's internal resistance, state of charge, and temperature coefficient. The calculation formula is: Battery Health = (Standard Internal Resistance / Current Internal Resistance) × State of Charge × Temperature Coefficient. The temperature coefficient is determined by the difference between the current ambient temperature and the battery's optimal operating temperature; a larger temperature difference results in a smaller coefficient. In high-temperature environments, the temperature coefficient significantly decreases, resulting in a corresponding downward adjustment in the battery health assessment result.

[0054] The battery full activation time is calculated based on historical internal resistance recovery data, the sleep depth coefficient, and the temperature correction factor. The formula is: Battery full activation time = basic activation time × sleep depth coefficient × temperature correction factor. The basic activation time is set according to the battery type in the historical internal resistance recovery data.

[0055] Combined with power demand forecasts, the expected start time of power consumption is calculated based on the user's historical power usage habits and the current time. For example, if the user is predicted to start using high-power devices to prepare dinner at 7 PM, the wake-up start time = 7 PM - activation duration - safety buffer time. In this embodiment, the safety buffer time is 10 minutes.

[0056] This embodiment establishes a three-layer hierarchical protection mechanism for batteries based on the environmental threat level and a precise wake-up timing calculation method. By dividing the battery group into a working layer, a buffer layer, and a core protection layer, differentiated protection strategies are implemented under different threat levels to maximize the protection of key battery resources. The battery health is calculated by comprehensively considering the battery internal resistance, state of charge, and temperature coefficient, providing an accurate battery status assessment basis for the wake-up trigger module. The activation duration is calculated based on historical internal resistance recovery data, sleep depth coefficient, and temperature correction coefficient, and the precise wake-up start time is determined in combination with power demand forecasts, providing the optimal start-up timing for the progressive wake-up module, avoiding energy waste and response delay problems caused by fixed-time wake-up or rough threshold triggering, thereby achieving refined timing management of battery resources.

[0057] Furthermore, the wake-up trigger module calculates the battery internal resistance change rate based on the battery internal resistance value; when the internal resistance change rate meets the preset wake-up trigger condition, it triggers a formal wake-up based on the wake-up start time;

[0058] The preset wake-up triggering conditions include:

[0059] When the internal resistance change rate turns from negative to positive and is greater than the preset environmental improvement threshold for M consecutive measurements, it is determined that the environment begins to improve; based on the real-time environmental parameters when the environment begins to improve, the internal resistance stability detection threshold is set; when the absolute value of the internal resistance change rate is less than the internal resistance stability detection threshold, and the difference between the current battery internal resistance value and the standard working internal resistance value is less than the preset internal resistance difference threshold and lasts for a preset time, it is confirmed that the environmental conditions are stable and a formal wake-up is triggered.

[0060] Specifically, the internal resistance change rate is the difference between the current battery internal resistance value and the last measured battery internal resistance value divided by the time interval.

[0061] In this embodiment, when the internal resistance change rate turns from negative to positive and is greater than a preset environmental improvement threshold for three consecutive measurements (M=3), it is determined that the environment is beginning to improve;

[0062] The internal resistance stability detection threshold is calculated based on the degree of deviation between the real-time temperature, humidity and other environmental parameters when the environment begins to improve and the optimal working environment of the battery. The environmental stability coefficient is then multiplied by the standard internal resistance stability threshold; the preset internal resistance difference threshold is 15%; and the continuous preset duration is 60 minutes.

[0063] Through a multi-level judgment mechanism for the internal resistance change rate, a reliable wake-up trigger condition based on changes in the battery's physical characteristics is established. When the internal resistance change rate turns from negative to positive and continuously meets the improvement threshold, the environmental improvement trend is accurately identified, providing the best start-up opportunity for the battery progressive wake-up module. By dynamically setting the internal resistance stability detection threshold and the internal resistance difference threshold, it is ensured that wake-up is triggered only when the environmental conditions are truly stable and the battery status is suitable, avoiding the risk of false start-up during environmental fluctuations. The duration requirement further improves the reliability of the trigger condition, providing a stable working basis for subsequent battery quantity determination and power evaluation, thereby improving the accuracy and reliability of the system response.

[0064] Furthermore, the battery progressive wake-up and stop module adopts a progressive battery quantity determination strategy. First, the first batch of wake-up batteries are selected based on the battery internal resistance and battery health and the power gap is evaluated. If the power gap is positive, the number of batteries is progressively increased. If the power gap is negative for N consecutive times, the number of batteries is stopped.

[0065] See Figure 3 , the progressive battery quantity determination strategy includes:

[0066] The first batch of wake-up batteries are screened based on the battery internal resistance value and battery health, and the output power and internal resistance changes of the first batch of wake-up batteries are continuously monitored to evaluate the power gap; if the power gap is positive, the remaining power demand is calculated; based on the battery internal resistance value, battery health and remaining power demand, the next batch of wake-up batteries are selected, and the power gap is evaluated again; if the power gap is negative for N consecutive times, stop adding batteries; for each batch of wake-up batteries, the batteries with the internal resistance value that best matches the standard working internal resistance value and the highest battery health are selected for wake-up first; establish a battery rotation mechanism, and when the internal resistance change of the working battery exceeds the preset working internal resistance change threshold, it is replaced with a dormant battery.

[0067] Specifically, all candidate batteries are sorted based on the battery internal resistance and battery health, and the three battery modules with the battery internal resistance closest to the standard working internal resistance and the highest battery health are selected as the first batch of wake-up targets.

[0068] After the first batch of batteries awaken, the output power and internal resistance of the first batch of batteries are continuously monitored. The power gap assessment is calculated by comparing the actual output power with the load power demand: Power Gap = Load Power Requirement - Actual Output Power - Preset Safety Margin. The preset safety margin is set at 10%-20% of the load power demand, and the specific value is dynamically adjusted based on the power output stability of the battery pack and the power fluctuation characteristics of the load equipment. A positive power gap indicates that the current number of batteries is insufficient to meet the load demand.

[0069] The remaining power requirement is estimated based on the power gap and battery performance parameters. Based on the remaining power requirement, the internal resistance and health of the candidate batteries, the next two best battery modules are selected as the next batch of wake-up batteries for wake-up, and the power gap is re-evaluated.

[0070] Repeat the above steps. If the power gap is negative for two consecutive times (N=2), stop adding batteries.

[0071] When the battery rotation mechanism detects that the internal resistance change of the working battery exceeds the preset working internal resistance change threshold, it automatically replaces it with the battery with the optimal internal resistance in the sleep state to achieve uninterrupted power supply optimization; in this embodiment, the preset working internal resistance change threshold is 15% of the initial internal resistance value.

[0072] Through a progressive battery quantity determination strategy, dynamic optimization and precise deployment of battery resources are achieved. First, the optimal battery is selected based on internal resistance and health for power verification, avoiding resource waste caused by activating too many batteries at one time. By continuously monitoring output power and evaluating power gaps, the number of batteries is gradually increased according to actual needs to ensure that both load requirements are met and over-configuration is avoided. The established battery rotation mechanism provides a performance optimization basis for the battery re-sleep module, and when the performance of the working battery degrades, it is replaced in time to maintain overall efficiency. This dual judgment mechanism ensures the accuracy of stopping the addition of batteries, provides a stable working state foundation for subsequent health correction and sleep depth adjustment, and improves battery resource utilization efficiency and overall system performance.

[0073] Furthermore, the battery re-hibernation module dynamically corrects the battery health and hibernation depth based on the real-time battery internal resistance value combined with the accumulated environmental damage, and puts the remaining batteries back into hibernation.

[0074] The process of dynamically correcting the battery health and the sleep depth is as follows:

[0075] The internal resistance degradation rate is calculated based on the real-time measured internal resistance value of the battery; the environmental damage accumulation is calculated based on the environmental threat level and exposure time; the battery health is corrected based on the internal resistance degradation rate and the environmental damage accumulation; the hibernation depth is re-determined based on the corrected battery health, and the remaining batteries are put back into hibernation.

[0076] Specifically, the calculation formula for the internal resistance degradation rate is: (current internal resistance value - initial internal resistance value) / initial internal resistance value × 100%;

[0077] Environmental damage accumulation is calculated based on the product of environmental threat level and exposure time.

[0078] Corrected battery health = initial battery health × (1-internal resistance degradation rate) × (1-accumulated environmental damage × damage coefficient); the damage coefficient is determined based on the battery type and environmental factors, reflecting the impact of the environment on battery performance.

[0079] Through a dual assessment mechanism of internal resistance degradation rate and accumulated environmental damage, a dynamic correction system for battery health status has been established, which reflects the actual performance changes of the battery in extreme environments in real time and provides adaptive adjustment capabilities for the long-term stable operation of the system. By combining the internal resistance degradation rate and accumulated environmental damage to correct the battery health, the current state of each battery is accurately assessed, providing a precise decision-making basis for the next round of battery stratification and dormancy control. A mechanism for re-determining the dormancy depth based on the corrected health status ensures that the battery protection strategy always matches the actual state, providing optimized monitoring object configuration for subsequent monitoring of the environmental-internal resistance monitoring module, realizing the intelligent evolution of the system protection strategy and maximizing the battery life.

[0080] This embodiment constructs a complete extended-range motorhome power dynamic management system architecture, and realizes dual perception of environmental threats and battery status through the environment-internal resistance monitoring module, providing an accurate data basis for subsequent battery stratification protection and intelligent wake-up; the battery stratification sleep control module implements differentiated protection strategies according to the threat level to ensure the safety of key batteries in extreme environments, and at the same time provides accurate timing prediction for the wake-up trigger module; the wake-up trigger module determines the optimal wake-up time based on the internal resistance change rate, avoiding energy loss caused by waking up too early or too late, and creating the best starting conditions for the progressive wake-up module; the battery progressive wake-up and stop module realizes precise configuration of the number of batteries, maximizes resource utilization efficiency, and provides an optimization basis for the re-sleep module; the battery re-sleep module realizes adaptive adjustment of the system through a dynamic correction mechanism, forming a complete closed-loop control system, which can realize collaborative power management and dynamic battery protection of multiple extended-range motorhomes under extreme environmental conditions.

[0081] Example 2:

[0082] In Example 1, the method proposed in the present invention successfully achieved the coordinated power management and dynamic battery protection of multiple extended-range caravans under extreme environmental conditions. To further verify the effectiveness of the present invention, a dynamic power management method for extended-range caravans is also proposed in the embodiment of this application to perform dynamic power management on multiple extended-range caravans. Figure 4 , Figure 4 Flowchart of the method of the present invention.

[0083] Real-time monitoring of ambient environmental parameters and measurement of battery internal resistance, and assessment of environmental threat levels using an environmental threat assessment model;

[0084] The environmental threat assessment model includes: an environmental parameter input unit, a parameter standardization processing unit and an environmental threat level assessment unit;

[0085] The environmental parameter input unit inputs the real-time monitored environmental parameters, including the temperature, humidity, air pressure and ultraviolet intensity around the RV; the parameter standardization processing unit standardizes the environmental parameters, compares them with the battery's optimal working environment parameters, and calculates the deviation values ​​of each environmental parameter; the environmental threat level assessment unit uses the weighted summation method to numerically assess the environmental threat level based on the deviation values ​​of each environmental parameter, and divides the environment into safe, warning, dangerous and extremely dangerous according to the environmental threat level.

[0086] Furthermore, the environmental threat level assessment unit further includes:

[0087] The environmental trend prediction unit establishes a time series prediction model based on historical environmental parameters to predict the changing trend of environmental parameters in the next 2-6 hours; the adaptive weight adjustment unit dynamically adjusts the weight coefficient of each environmental parameter in the weighted summation method according to the predicted results of the environmental parameter changing trend and the current seasonal characteristics; the early warning unit triggers the corresponding battery stratification adjustment and sleep depth pre-adjustment in advance when the predicted environmental threat level will change across levels within a preset time.

[0088] Through environmental trend forecasting, environmental threat changes can be predicted 2-6 hours in advance, giving the system forward-looking management capabilities; the adaptive weight adjustment mechanism makes environmental threat assessment more accurate and adapts to the environmental characteristics of different seasons and regions; the early warning function can avoid battery damage caused by sudden environmental changes and improve system response speed.

[0089] Furthermore, the battery pack is stratified according to the environmental threat level, and the battery health is calculated to control the sleep depth of each battery layer. The time required for the battery to fully activate is calculated based on historical internal resistance recovery data, and the wake-up start time is determined based on the sleep depth.

[0090] The process of determining the wake-up start time is as follows:

[0091] The battery pack is divided into three layers according to the environmental threat level: when the environmental threat level is safe and / or warning, the battery pack is set as the working layer; when the environmental threat level is dangerous, the battery pack is set as the buffer layer; when the environmental threat level is critical, the battery pack is set as the core protection layer; the battery health is calculated based on the battery internal resistance, state of charge and temperature coefficient; wherein the temperature coefficient is determined according to the current temperature around the RV;

[0092] The sleep depth is determined according to the battery health and the level of the battery pack, including shallow sleep for the working layer, moderate sleep for the buffer layer, and deep sleep for the core protection layer; the battery full activation time is calculated based on historical internal resistance recovery data, sleep depth coefficient and temperature correction coefficient; wherein, the sleep depth coefficient is determined based on the sleep depth of the level of the battery pack; the temperature correction coefficient is corrected according to the temperature change around the current RV; based on the battery full activation time, combined with the power demand forecast time and setting a safety buffer time, the wake-up start time is determined.

[0093] Furthermore, the battery internal resistance change rate is calculated based on the battery internal resistance value; when the internal resistance change rate meets the preset wake-up trigger condition, a formal wake-up is triggered based on the wake-up start time;

[0094] The preset wake-up triggering conditions include:

[0095] When the internal resistance change rate turns from negative to positive and is greater than the preset environmental improvement threshold for M consecutive measurements, it is determined that the environment begins to improve; based on the real-time environmental parameters when the environment begins to improve, the internal resistance stability detection threshold is set; when the absolute value of the internal resistance change rate is less than the internal resistance stability detection threshold, and the difference between the current battery internal resistance value and the standard working internal resistance value is less than the preset internal resistance difference threshold and lasts for a preset time, it is confirmed that the environmental conditions are stable and a formal wake-up is triggered.

[0096] Furthermore, before triggering the formal awakening, a multi-level verification mechanism is also included, including:

[0097] Level 1 verification detects whether the standard deviation of the battery's internal resistance is less than the preset standard deviation threshold for 5 consecutive minutes; level 2 verification simultaneously monitors the actual power demand of the electrical equipment inside the RV, and passes the verification when the matching degree between the actual power demand and the current available power is greater than the preset matching degree threshold; level 3 verification detects whether the environmental parameters remain stable at the safety or warning level for longer than the preset verification time; only after all three levels of verification are passed will the formal wake-up be performed. If any level of verification fails, the wake-up will be delayed and the verification cycle will be repeated.

[0098] A multi-level verification mechanism effectively prevents false wake-ups and reduces the false wake-up rate. Power requirement matching verification ensures that the number of awakened batteries accurately matches actual needs, avoiding unnecessary battery activation. The hierarchical verification strategy improves system stability and reduces frequent wake-up-sleep switching operations caused by environmental fluctuations.

[0099] Furthermore, a progressive battery quantity determination strategy is adopted. First, the first batch of wake-up batteries are screened based on the battery internal resistance and battery health, and the power gap is evaluated. If the power gap is positive, the number of batteries is gradually increased. If the power gap is negative for N consecutive times, the number of batteries is stopped.

[0100] The progressive battery quantity determination strategy includes:

[0101] The first batch of wake-up batteries are screened based on the battery internal resistance value and battery health, and the output power and internal resistance changes of the first batch of wake-up batteries are continuously monitored to evaluate the power gap; if the power gap is positive, the remaining power demand is calculated; based on the battery internal resistance value, battery health and remaining power demand, the next batch of wake-up batteries are selected, and the power gap is evaluated again; if the power gap is negative for N consecutive times, stop adding batteries; for each batch of wake-up batteries, the batteries with the internal resistance value that best matches the standard working internal resistance value and the highest battery health are selected for wake-up first; establish a battery rotation mechanism, and when the internal resistance change of the working battery exceeds the preset working internal resistance change threshold, it is replaced with a dormant battery.

[0102] Furthermore, the battery health and sleep depth are dynamically corrected based on the real-time battery internal resistance value combined with the accumulated environmental damage, and the remaining batteries are put back into sleep mode;

[0103] The process of dynamically correcting the battery health and the sleep depth is as follows:

[0104] The internal resistance degradation rate is calculated based on the real-time measured internal resistance value of the battery; the environmental damage accumulation is calculated based on the environmental threat level and exposure time; the battery health is corrected based on the internal resistance degradation rate and the environmental damage accumulation; the hibernation depth is re-determined based on the corrected battery health, and the remaining batteries are put back into hibernation.

[0105] Furthermore, the specific process of calculating the cumulative environmental damage is as follows:

[0106] An environmental damage factor database is established to store the unit time damage coefficient caused by various environmental parameters to the battery under different environmental threat levels; the total environmental damage accumulation value is calculated using the piecewise integration method based on the exposure time of the battery under each environmental threat level and the corresponding environmental damage factor; different environmental damage weight coefficients are assigned to different batteries based on their position and importance level in the battery pack; an environmental damage history tracking unit is used to record the historical environmental damage accumulation trajectory of each battery and establish an individualized battery damage file to accurately calculate the specific impact of the current environmental damage accumulation on the battery health.

[0107] The segmented integral calculation method and environmental damage factor database make the cumulative calculation of environmental damage more accurate and can truly reflect the cumulative damage effects under different environmental conditions; the environmental damage weight distribution mechanism realizes individualized and fine management of batteries and improves the protection effect of key batteries; the historical damage tracking function establishes a complete battery health file system, which provides reliable data support for predictive maintenance and precise correction of battery health, significantly improving the reliability and service life of the entire battery system.

[0108] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. A dynamic power management system for an extended-range motorhome, characterized in that: include: The environment-internal resistance monitoring module monitors the surrounding environment parameters in real time and measures the battery internal resistance, and assesses the environmental threat level through the environmental threat assessment model; The battery hierarchical sleep control module divides battery packs into tiers based on environmental threat levels and calculates battery health to control the sleep depth of each tier. It also calculates the time required for full battery activation based on historical internal resistance recovery data and determines the wake-up time based on the sleep depth. The wake-up trigger module calculates the battery internal resistance change rate based on the battery internal resistance value; when the internal resistance change rate meets the preset wake-up trigger condition, it triggers the formal wake-up based on the wake-up start time; The battery progressive wake-up and stop module uses a progressive battery quantity determination strategy to select the first batch of wake-up batteries based on the battery internal resistance and battery health and evaluate the power gap. If the power gap is positive, the number of batteries is progressively increased. If the power gap is negative for N consecutive times, stop adding batteries; The battery re-hibernation module dynamically corrects the battery health and hibernation depth based on the real-time battery internal resistance value and the accumulated environmental damage, and puts the remaining battery back into hibernation.

2. The range-extended motorhome power dynamic management system according to claim 1, characterized in that: The environmental threat assessment model includes: an environmental parameter input unit, a parameter standardization processing unit and an environmental threat level assessment unit; The environmental parameter input unit inputs the real-time monitored environmental parameters, including the temperature, humidity, air pressure and ultraviolet intensity around the RV; the parameter standardization processing unit standardizes the environmental parameters, compares them with the battery's optimal working environment parameters, and calculates the deviation values ​​of each environmental parameter; the environmental threat level assessment unit uses the weighted summation method to numerically assess the environmental threat level based on the deviation values ​​of each environmental parameter, and divides the environment into safe, warning, dangerous and extremely dangerous according to the environmental threat level.

3. The range-extended motorhome power dynamic management system according to claim 2, characterized in that: The process of determining the wake-up start time is as follows: The battery pack is divided into three layers according to the environmental threat level: when the environmental threat level is safe and / or warning, the battery pack is set as the working layer; when the environmental threat level is dangerous, the battery pack is set as the buffer layer; when the environmental threat level is critical, the battery pack is set as the core protection layer; the battery health is calculated based on the battery internal resistance, state of charge and temperature coefficient; wherein the temperature coefficient is determined according to the current temperature around the RV; The sleep depth is determined according to the battery health and the level of the battery pack, including shallow sleep for the working layer, moderate sleep for the buffer layer, and deep sleep for the core protection layer; the battery full activation time is calculated based on historical internal resistance recovery data, sleep depth coefficient and temperature correction coefficient; wherein, the sleep depth coefficient is determined based on the sleep depth of the level of the battery pack; the temperature correction coefficient is corrected according to the temperature change around the current RV; based on the battery full activation time, combined with the power demand forecast time and setting a safety buffer time, the wake-up start time is determined.

4. The range-extended motorhome power dynamic management system according to claim 1, characterized in that: The preset wake-up triggering conditions include: When the internal resistance change rate turns from negative to positive and is greater than the preset environmental improvement threshold for M consecutive measurements, it is determined that the environment begins to improve; based on the real-time environmental parameters when the environment begins to improve, the internal resistance stability detection threshold is set; when the absolute value of the internal resistance change rate is less than the internal resistance stability detection threshold, and the difference between the current battery internal resistance value and the standard working internal resistance value is less than the preset internal resistance difference threshold and lasts for a preset time, it is confirmed that the environmental conditions are stable and a formal wake-up is triggered.

5. The range-extended motorhome power dynamic management system according to claim 1, characterized in that: The progressive battery quantity determination strategy includes: The first batch of wake-up batteries are screened based on the battery internal resistance value and battery health, and the output power and internal resistance changes of the first batch of wake-up batteries are continuously monitored to evaluate the power gap; if the power gap is positive, the remaining power demand is calculated; based on the battery internal resistance value, battery health and remaining power demand, the next batch of wake-up batteries are selected, and the power gap is evaluated again; if the power gap is negative for N consecutive times, stop adding batteries; for each batch of wake-up batteries, the batteries with the internal resistance value that best matches the standard working internal resistance value and the highest battery health are selected for wake-up first; establish a battery rotation mechanism, and when the internal resistance change of the working battery exceeds the preset working internal resistance change threshold, it is replaced with a dormant battery.

6. The range-extended motorhome power dynamic management system according to claim 1, characterized in that: The process of dynamically correcting the battery health and the sleep depth is as follows: The internal resistance degradation rate is calculated based on the real-time measured internal resistance value of the battery; the environmental damage accumulation is calculated based on the environmental threat level and exposure time; the battery health is corrected based on the internal resistance degradation rate and the environmental damage accumulation; the hibernation depth is re-determined based on the corrected battery health, and the remaining batteries are put back into hibernation.

7. A method for dynamic management of power consumption of an extended-range motorhome, characterized in that: include: Real-time monitoring of ambient environmental parameters and measurement of battery internal resistance, and assessment of environmental threat levels using an environmental threat assessment model; The battery pack is stratified according to the environmental threat level, and the battery health is calculated to control the sleep depth of each battery layer. The time required for full battery activation is calculated based on historical internal resistance recovery data, and the wake-up start time is determined based on the sleep depth. Calculate the battery internal resistance change rate based on the battery internal resistance value; when the internal resistance change rate meets the preset wake-up trigger condition, trigger the formal wake-up based on the wake-up start time; A progressive battery quantity determination strategy is adopted. First, the first batch of wake-up batteries are selected based on the battery internal resistance and battery health, and the power gap is evaluated. If the power gap is positive, the number of batteries is gradually increased. If the power gap is negative for N consecutive times, stop adding batteries; Based on the real-time battery internal resistance value and the accumulated environmental damage, the battery health and sleep depth are dynamically corrected, and the remaining batteries are put back into sleep mode.

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