New energy automobile air conditioner compressor variable frequency speed regulation and energy efficiency optimization integrated system

Abstract

The application relates to the technical field of new energy automobile air conditioners, and discloses a new energy automobile air conditioner compressor variable frequency speed regulation and energy efficiency optimization integrated system, which comprises a data sensing module, a strategy generation module, a parameter regulation module, an energy efficiency evaluation module and a system correction module. The data sensing module is used for determining the stability of a compressor operation state based on a speed fluctuation amount; the strategy generation module is used for determining a speed regulation control strategy and determining the correlation between speed and power based on the stability; the parameter regulation module is used for determining an energy efficiency optimization value judgment mode according to a power consumption rate based on the speed regulation strategy, and determining the compliance according to a response delay amount; the energy efficiency evaluation module is used for determining the compliance of speed and power according to an energy efficiency conversion ratio based on the speed regulation strategy; and the system correction module is used for correcting when the energy efficiency optimization value or the speed and power are not compliant. The system realizes the optimization of compressor variable frequency speed regulation and energy efficiency, improves the operation stability, the refrigeration demand matching degree and the energy efficiency level, reduces energy consumption, and plays an important role in prolonging the cruising range of new energy automobiles.

Description

Technical Field

[0001] This invention relates to the field of air conditioning technology for new energy vehicles, specifically to an integrated system for variable frequency speed regulation and energy efficiency optimization of air conditioning compressors for new energy vehicles. Background Technology

[0002] Against the backdrop of a global energy crisis and increasingly stringent environmental requirements, new energy vehicles have experienced rapid development due to their clean and energy-saving advantages. As a crucial component of new energy vehicles, the energy consumption of the air conditioning system directly impacts the vehicle's driving range and energy efficiency. Furthermore, the stability, speed control precision, and energy efficiency of the air conditioning compressor, as the core component of the air conditioning system, are of paramount importance.

[0003] Traditional automotive air conditioning compressor speed control and energy efficiency optimization technologies face numerous challenges when applied to new energy vehicles. Firstly, the power characteristics of new energy vehicles differ from those of traditional gasoline vehicles, with relatively larger voltage fluctuations. This places higher demands on the compressor's variable frequency speed control system. Traditional speed control strategies struggle to maintain stable compressor operation under such complex power conditions, easily leading to large speed fluctuations and consequently affecting the air conditioning system's cooling performance. Secondly, new energy vehicles have stricter energy efficiency requirements. Traditional energy efficiency optimization methods often fail to fully consider the compressor's actual needs under different operating conditions, resulting in poor energy efficiency optimization and an inability to achieve a proper match between speed and power, leading to energy waste.

[0004] Existing compressor control systems lack flexible and effective control strategies to meet varying cooling demands. When cooling requirements change, they cannot quickly and accurately adjust speed and power, resulting in poor matching of cooling needs. This not only affects passenger comfort but also increases system energy consumption. Furthermore, traditional technologies are inadequate in energy efficiency assessment and system calibration. They cannot promptly and accurately determine whether the energy conversion ratio meets requirements, and when discrepancies occur, they cannot take effective corrective measures based on the actual situation, making it difficult to effectively improve the system's energy efficiency level.

[0005] Traditional systems, in their parameter control processes, do not comprehensively consider response delay and cannot adjust the determination method for energy efficiency optimization values ​​in a timely manner based on changes in response delay. This makes it difficult to guarantee the compliance of energy efficiency optimization values, further affecting the overall energy efficiency of the system. With the continuous expansion of the new energy vehicle market and the continuous advancement of technology, there is an urgent need for an integrated system of variable frequency speed control and energy efficiency optimization for air conditioning compressors that can adapt to the characteristics of new energy vehicles. This system would address the aforementioned problems in traditional technologies, improve the operational stability and energy efficiency of the compressor, and meet the high requirements of new energy vehicles for their air conditioning systems. Summary of the Invention

[0006] The purpose of this invention is to provide an integrated system for variable frequency speed regulation and energy efficiency optimization of air conditioning compressors in new energy vehicles, so as to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an integrated system for variable frequency speed regulation and energy efficiency optimization of air conditioning compressors for new energy vehicles, the system comprising:

[0008] The data sensing module is used to determine the stability of the compressor's operating status based on the amount of speed fluctuation;

[0009] The strategy generation module, which is connected to the data sensing module, is used to determine the speed control strategy based on the stability of the compressor's operating state, and to determine the correlation between speed and power based on the matching degree of cooling demand under the corresponding speed control strategy.

[0010] The parameter control module, which is connected to the strategy generation module, is used to determine the energy efficiency optimization value based on the power consumption rate under the condition of the corresponding speed control strategy, and to determine the compliance of the energy efficiency optimization value based on the response delay during the adjustment process.

[0011] An energy efficiency assessment module, which is connected to the parameter control module, is used to determine the compatibility between speed and power based on the energy conversion ratio at each operating point under the condition of the corresponding speed control strategy.

[0012] The system calibration module, which is connected to the parameter control module and the energy efficiency evaluation module, is used to determine the improvement optimization value based on the difference between the preset response delay and the actual response delay when the energy efficiency optimization value does not meet the requirements, and to determine the improvement optimization value based on the difference between the preset response delay and the actual response delay when the energy efficiency optimization value does not meet the requirements, or to determine the power reduction based on the difference between the energy efficiency conversion ratio and the preset conversion ratio.

[0013] Preferably, the strategy generation module determines that the compressor is operating stably based on the comparison result that the speed fluctuation is less than the preset fluctuation, and determines that the higher the speed, the lower the power under the continuous speed control strategy based on the comparison result that the cooling demand matching degree is greater than or equal to the preset matching degree, and determines the energy efficiency optimization value based on the comparison result of the power consumption rate and the preset consumption rate.

[0014] Preferably, the strategy generation module determines that the compressor's operating state is unstable based on the comparison result of the speed fluctuation being greater than or equal to the preset fluctuation, and determines that the higher the speed, the higher the power under the segmented speed control strategy based on the comparison result of the cooling demand matching degree being greater than or equal to the preset matching degree, and determines the energy efficiency optimization value based on the comparison result of the power consumption rate and the preset consumption rate.

[0015] Preferably, under the condition of determining the energy efficiency optimization value, the parameter control module determines that the energy efficiency optimization value does not meet the requirements based on the comparison result that the response delay is greater than or equal to the preset delay, and determines to increase the optimization value with the first preset optimization adjustment coefficient based on the comparison result that the difference between the preset response delay and the actual response delay is less than or equal to the preset deviation.

[0016] Preferably, under the condition of determining the energy efficiency optimization value, the parameter control module determines that the energy efficiency optimization value does not meet the requirements based on the comparison result that the response delay is greater than or equal to the preset delay, and determines to increase the optimization value with the second preset optimization adjustment coefficient based on the comparison result that the difference between the preset response delay and the actual response delay is greater than the preset deviation.

[0017] Preferably, the system correction module, under the condition that the corresponding speed control strategy is executed on the compressor, determines that the speed and power do not match based on the comparison result that the energy efficiency conversion ratio of each operating point is less than the preset conversion ratio, and determines to increase the speed with the first preset speed adjustment coefficient based on the comparison result that the ratio of the energy efficiency conversion ratio to the preset conversion ratio is greater than or equal to the preset ratio.

[0018] Preferably, the system correction module, under the condition that the corresponding speed control strategy is executed on the compressor, determines that the speed and power do not match based on the comparison result that the energy efficiency conversion ratio of each operating point is less than the preset conversion ratio, and determines to increase the speed with the second preset speed adjustment coefficient based on the comparison result that the ratio of the energy efficiency conversion ratio to the preset conversion ratio is less than the preset ratio.

[0019] Preferably, under the condition that the corresponding speed control strategy is executed on the compressor, the energy efficiency assessment module determines that the speed and power do not match based on the comparison result that the energy efficiency conversion ratio of each operating point is less than the preset conversion ratio, and determines to reduce the power with the first preset power adjustment coefficient based on the comparison result that the difference between the energy efficiency conversion ratio and the preset conversion ratio is less than or equal to the preset difference.

[0020] Preferably, under the condition that the corresponding speed control strategy is executed on the compressor, the energy efficiency assessment module determines that the speed and power do not match based on the comparison result that the energy efficiency conversion ratio of each operating point is less than the preset conversion ratio, and determines to reduce the power with the second preset power adjustment coefficient based on the comparison result that the difference between the energy efficiency conversion ratio and the preset conversion ratio is greater than the preset difference.

[0021] Preferably, the system correction module, under the condition that the corresponding speed control strategy is executed on the compressor, determines that the speed and power are consistent based on the comparison result that the energy efficiency conversion ratio is equal to the preset conversion ratio, and keeps the current speed and power parameters unchanged.

[0022] Compared with the prior art, the beneficial effects of the present invention are:

[0023] The system uses a data sensing module to determine the stability of the compressor's operating status based on speed fluctuations, enabling precise judgment of the compressor's operation under different conditions. When the speed fluctuation is less than a preset fluctuation, the compressor's operating status is considered stable; otherwise, it is considered unstable, providing an accurate basis for subsequent speed control strategies.

[0024] The strategy generation module is connected to the data sensing module, and determines a suitable speed control strategy based on the stability of the compressor's operating state. When the operating state is stable and the cooling demand matching degree is greater than or equal to the preset matching degree, a continuous speed control strategy is determined, so that the power is lower at higher speeds. When the operating state is unstable but the cooling demand matching degree meets the conditions, a segmented speed control strategy is determined, so that the power is higher at higher speeds. This enables flexible adjustment of the speed control strategy according to the actual operating state, improves the cooling demand matching degree, ensures that the cooling demand can be better met under different conditions, and enhances the comfort inside the vehicle.

[0025] The parameter control module, based on the corresponding speed control strategy, determines the method for judging the energy efficiency optimization value according to the power consumption rate, and determines the compliance of the energy efficiency optimization value based on the response delay during the adjustment process. When the response delay is greater than or equal to the preset delay, it can promptly determine that the energy efficiency optimization value does not comply, and based on the difference between the preset response delay and the actual response delay, it uses different preset optimization adjustment coefficients to improve the optimization value, effectively ensuring the rationality and accuracy of the energy efficiency optimization value and improving the system's energy efficiency level.

[0026] The energy efficiency assessment module, based on the corresponding speed control strategy, determines the compatibility between speed and power according to the energy conversion ratio at each operating point. When the energy conversion ratio is less than the preset conversion ratio, it can accurately determine that the speed and power do not match, and reduce the power using different preset power adjustment coefficients according to the degree of difference between the energy conversion ratio and the preset conversion ratio, ensuring that the speed and power are reasonably matched at each operating point, thereby further optimizing the system's energy efficiency.

[0027] The system calibration module is connected to the parameter control module and the energy efficiency evaluation module. When the energy efficiency optimization value does not meet the requirements, the optimization value is increased based on the difference between the preset response delay and the actual response delay. When the speed and power do not meet the requirements, the speed is increased or the power is reduced based on the ratio or difference between the energy efficiency conversion ratio and the preset conversion ratio. This achieves precise calibration of the system, enabling the system to quickly return to its optimal operating state and improving the system's stability and reliability.

[0028] Through the coordinated work of various modules, this integrated system achieves comprehensive and precise control of variable frequency speed regulation and energy efficiency optimization of the air conditioning compressor in new energy vehicles. It not only improves the stability of the compressor's operating status and the matching degree of cooling demand, but also significantly improves the system's energy efficiency level and reduces energy consumption. This is of great significance for extending the driving range of new energy vehicles, and also provides strong support for the development of air conditioning technology for new energy vehicles. Attached Figure Description

[0029] Figure 1 This is a schematic diagram illustrating the working principle of the new energy vehicle air conditioning compressor variable frequency speed regulation and energy efficiency optimization integrated system described in this invention.

[0030] Figure 2 A flowchart of a continuous speed control strategy under steady-state conditions;

[0031] Figure 3 The flowchart shows the segmented speed control strategy under unstable conditions.

[0032] Figure 4 The flowchart shows the first optimization adjustment when the energy efficiency optimization value is not met.

[0033] Figure 5 This is a flowchart for the second optimization adjustment when the energy efficiency optimization value does not meet the requirements. Detailed Implementation

[0034] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0035] Please see Figures 1-5 This invention relates to an integrated system for variable frequency speed control and energy efficiency optimization of air conditioning compressors in new energy vehicles. The system includes: a data sensing module, a strategy generation module, a parameter control module, an energy efficiency assessment module, and a system calibration module. The specific implementation steps are as follows:

[0036] The data sensing module is used to determine the stability of the compressor's operating state based on speed fluctuations. Specifically, the data sensing module collects the compressor's speed data in real time and calculates the speed fluctuation. By comparing the speed fluctuation with a preset fluctuation value, it determines whether the compressor's operating state is stable.

[0037] The strategy generation module is connected to the data sensing module and is used to determine the speed control strategy based on the stability of the compressor's operating state, and to determine the correlation between speed and power according to the matching degree of cooling demand under the corresponding speed control strategy. When the data sensing module determines whether the compressor's operating state is stable or unstable, the strategy generation module will select a continuous speed control strategy or a segmented speed control strategy accordingly, and combine the matching degree of cooling demand to clarify the relationship between speed and power.

[0038] The parameter control module is connected to the strategy generation module. Under the corresponding speed control strategy, it determines the method for judging the energy efficiency optimization value based on the power consumption rate, and determines the compliance of the energy efficiency optimization value based on the response delay during the adjustment process. The parameter control module first determines the method for judging the energy efficiency optimization value based on the comparison between the power consumption rate and the preset consumption rate, and then judges whether the energy efficiency optimization value meets the requirements based on the comparison between the response delay and the preset delay.

[0039] The energy efficiency assessment module is connected to the parameter control module and is used to determine the compliance of speed and power based on the energy conversion ratio at each operating point under the corresponding speed control strategy. The energy efficiency assessment module analyzes the energy conversion ratio at each operating point and compares it with the preset conversion ratio to determine whether the speed and power meet the requirements.

[0040] The system calibration module is connected to the parameter control module and the energy efficiency assessment module. It is used to determine an increased optimization value based on the difference between the preset response delay and the actual response delay when the energy efficiency optimization value does not meet the requirements; or to determine a reduced power based on the difference between the preset response delay and the actual response delay when the energy efficiency optimization value does not meet the requirements; or to determine a power reduction based on the difference between the energy efficiency conversion ratio and the preset conversion ratio. In other words, when the energy efficiency optimization value does not meet the requirements, the system calibration module will take corresponding measures to adjust the optimization value or power according to different situations.

[0041] Example 1: In this example, the strategy generation module determines that the compressor is operating stably based on the comparison result that the speed fluctuation is less than the preset fluctuation, and determines that the higher the speed, the lower the power under the continuous speed control strategy based on the comparison result that the cooling demand matching degree is greater than or equal to the preset matching degree. The energy efficiency optimization value is determined based on the comparison result of the power consumption rate and the preset consumption rate.

[0042] The strategy generation module and the data sensing module maintain real-time data interaction. The data sensing module continuously collects compressor speed data during operation. The speed data collection frequency must meet the system's accuracy requirements for monitoring the compressor's operating status, such as collecting data multiple times per second, to ensure timely detection of subtle changes in speed. After collecting the speed data, the data sensing module processes it to calculate the speed fluctuation. The calculation method for speed fluctuation can be the difference between the maximum and minimum speed values ​​within a certain time window, or the standard deviation calculated using statistical methods. The specific calculation method needs to be set during system development based on actual needs and compressor characteristics to accurately reflect speed fluctuations.

[0043] After obtaining the calculated speed fluctuation from the data sensing module, the strategy generation module compares it with a preset fluctuation value. This preset fluctuation value is a threshold determined during the system design phase based on various factors, including the normal operating conditions, performance indicators, and actual usage requirements of the new energy vehicle air conditioning compressor. When the speed fluctuation is less than this preset fluctuation value, the strategy generation module determines that the compressor's operating state is stable. This is because a smaller speed fluctuation indicates that the compressor can operate relatively smoothly under the current operating conditions, without significant drastic changes or abnormal fluctuations in speed, which conforms to the characteristics of stable operation.

[0044] After confirming that the compressor's operating status is stable, the strategy generation module further acquires data on the cooling demand matching degree. The cooling demand matching degree is an indicator used to measure whether the current compressor's cooling capacity meets the vehicle's cooling needs. Its determination requires comprehensive consideration of various factors, including the vehicle's set temperature, actual temperature, number of passengers, and ambient temperature. For example, the system calculates the required cooling capacity based on the difference between the actual temperature collected by the vehicle's temperature sensor and the user-set temperature, combined with factors such as the ambient temperature and the presence of direct sunlight. Then, it compares the actual cooling capacity provided by the compressor with the required cooling capacity to obtain the cooling demand matching degree.

[0045] The strategy generation module compares the obtained cooling demand matching degree with the preset matching degree. The preset matching degree is also a standard value set during system design based on different usage scenarios and user requirements for cooling performance. When the cooling demand matching degree is greater than or equal to the preset matching degree, it indicates that the compressor's current cooling capacity can meet or exceed the vehicle's cooling needs. In this case, the strategy generation module determines to adopt a continuous speed control strategy, under which higher speed results in lower power consumption.

[0046] Continuous speed control means that the compressor speed can be continuously adjusted within a certain range, rather than through staged, jump-like adjustments. This strategy is suitable for situations where the compressor operates stably and the cooling demand can be well met. The reason for determining that higher speed results in lower power consumption under continuous speed control is based on in-depth research and analysis of the compressor's operating characteristics. Generally, within a specific operating range, increasing the compressor speed may improve its cooling efficiency, thus potentially reducing the power consumption required to meet the same cooling demand. Of course, this requires determining the specific relationship curve between speed and power through compressor performance testing and data analysis during system design and commissioning to ensure the accuracy and rationality of this correlation.

[0047] Next, the strategy generation module needs to determine the energy efficiency optimization value based on the comparison between the power consumption rate and the preset consumption rate. The power consumption rate refers to the power consumption of the compressor per unit time under a continuous speed control strategy. Its calculation requires obtaining the compressor's actual power consumption data and the corresponding operating time. For example, the system will collect parameters such as the compressor's input voltage and current in real time, calculate the actual power using formulas, and then combine this with the operating time to calculate the power consumption rate over a certain period.

[0048] The preset power consumption rate is a reference value set by the system to measure whether the compressor's power consumption is reasonable. It is determined based on factors such as the compressor's rated power, energy efficiency standards, and energy-saving requirements in actual use. The strategy generation module compares the calculated power consumption rate with the preset consumption rate. If the power consumption rate is lower than the preset consumption rate, it indicates that the compressor consumes relatively little power and performs well in its current operating state. In this case, the strategy generation module will determine a relatively small energy efficiency optimization value, which may only involve fine-tuning the current operating parameters to maintain a good energy efficiency state. If the power consumption rate is higher than the preset consumption rate, it indicates that the compressor consumes a lot of power and its energy efficiency needs to be improved. In this case, the strategy generation module will determine a corresponding energy efficiency optimization value based on the difference between the two values. This optimization value aims to reduce power consumption and improve energy efficiency by adjusting relevant parameters, such as further optimizing the matching relationship between speed and power.

[0049] Throughout the process, the strategy generation module continuously interacts with the data sensing module to acquire real-time data such as speed fluctuations, cooling demand matching, and power consumption rate. This data is then continuously compared and analyzed to ensure timely adjustments to the speed control strategy and determination of energy efficiency optimization values ​​based on the compressor's actual operating status. This integrated control of variable frequency speed regulation and energy efficiency optimization for the air conditioning compressor in new energy vehicles maximizes energy efficiency and minimizes energy consumption while ensuring stable compressor operation, thus meeting the energy-saving and environmental protection requirements of new energy vehicles. Simultaneously, the system must consider various possible interference factors and boundary conditions, such as vehicle vibrations and voltage fluctuations, to ensure the reliability and robustness of the strategy generation module's judgments and decisions, guaranteeing the stable and efficient operation of the entire system.

[0050] Example 2: In this example, the strategy generation module determines that the compressor is not running smoothly based on the comparison result of the speed fluctuation being greater than or equal to the preset fluctuation. It also determines that the higher the speed, the higher the power under the segmented speed control strategy, based on the comparison result of the cooling demand matching degree being greater than or equal to the preset matching degree. Finally, it determines the energy efficiency optimization value based on the comparison result of the power consumption rate and the preset consumption rate.

[0051] A stable data transmission channel is established between the strategy generation module and the data sensing module to ensure real-time acquisition of key data during compressor operation. During system operation, the data sensing module collects compressor speed data in real-time at a set sampling frequency. This sampling frequency must meet the requirements for accurate monitoring of compressor speed changes; for example, it can be set to collect data dozens of times per second to avoid missing speed fluctuations due to insufficient sampling frequency. After collecting continuous speed data, the data sensing module analyzes and processes this data, calculating the speed fluctuation using a specific algorithm. The method for calculating the speed fluctuation can be determined based on the actual operating characteristics of the compressor. For example, it can be done by calculating the difference between the maximum and minimum speed values ​​within a certain time period, or by using a time-series-based variance calculation method to accurately reflect the degree of speed fluctuation.

[0052] After receiving the speed fluctuation data from the data sensing module, the strategy generation module compares it with a pre-set fluctuation value. The determination of the pre-set fluctuation value comprehensively considers factors such as the type of air conditioning compressor in the new energy vehicle, its rated speed, the speed fluctuation range during normal operation, and potential changes in operating conditions during vehicle operation. When the speed fluctuation is greater than or equal to the pre-set fluctuation value, the strategy generation module determines that the compressor's operating state is unstable. This is because a large speed fluctuation indicates that the compressor may have been affected by factors such as rapid acceleration or deceleration of the vehicle, or sudden changes in external load during operation, causing significant fluctuations in its speed and making it unable to maintain operation within a relatively stable range.

[0053] After determining that the compressor's operating state is unstable, the strategy generation module further acquires relevant data on the cooling demand matching degree. The calculation of the cooling demand matching degree requires comprehensive consideration of various environmental and operating conditions, such as the actual temperature reported by the vehicle's in-vehicle temperature sensor, the target temperature set by the user through the air conditioning control panel, the number of passengers in the vehicle, the opening and closing status of the windows, the ambient temperature, and the intensity of solar radiation. Based on these input parameters, the system calculates the currently required cooling capacity using the established cooling demand model. Simultaneously, it combines the cooling capacity output characteristics of the compressor at different speeds to determine the degree of matching between the actual cooling capacity output by the compressor and the required cooling capacity, i.e., the cooling demand matching degree.

[0054] The strategy generation module compares the calculated cooling demand matching degree with a preset matching degree. The preset matching degree is a threshold set during the system design phase based on factors such as users' basic requirements for in-vehicle cooling performance under different climatic conditions, the compressor's cooling capacity range, and the energy consumption limitations of new energy vehicles. When the cooling demand matching degree is greater than or equal to the preset matching degree, it indicates that although the compressor's operating state is unstable, the current cooling capacity can still meet or exceed the vehicle's cooling needs. In this case, the strategy generation module determines to adopt a segmented speed control strategy, and under this strategy, higher speed results in higher power.

[0055] Segmented speed control divides the compressor's speed range into several distinct speed segments, each corresponding to different speed control rules and power output characteristics. This strategy is suitable for situations where the compressor's operating state is unstable. Segmented control allows for better adaptation to the compressor's operating characteristics within different speed ranges, improving system stability and control accuracy. The principle that higher speed equates to higher power under segmented speed control is based on the compressor's characteristics under unstable operating conditions. When the compressor speed is low, a larger power input may be needed to maintain cooling capacity to meet certain refrigeration demands. However, when the speed increases to higher speeds, although the compressor's operating state remains unstable, the increased speed leads to higher power consumption due to internal mechanical losses and volumetric efficiency, thus establishing the correlation between higher speed and higher power. This relationship needs to be determined during system development through extensive testing and data analysis of the compressor's power consumption under different speed segments and load conditions to ensure the rationality and effectiveness of the segmented speed control strategy.

[0056] The strategy generation module needs to determine the energy efficiency optimization value based on the comparison between the power consumption rate and the preset consumption rate. The power consumption rate refers to the average power consumption level of the compressor per unit time under a segmented speed control strategy. Its calculation process requires real-time acquisition of the compressor's power data at each speed segment and a weighted average based on the operating time of each speed segment. For example, the system records the compressor's operating time at each speed segment and the real-time power consumption within that speed segment, and calculates the average power consumption rate throughout the entire operation.

[0057] The preset power consumption rate is a baseline value set by the system for power consumption under the segmented speed control strategy. This value is determined considering factors such as the compressor's rated power at different speed ranges, energy efficiency standards, and the energy consumption requirements of air conditioning systems for new energy vehicles. The strategy generation module compares the calculated power consumption rate with the preset rate. If the power consumption rate is lower than the preset rate, it indicates that the compressor's power utilization efficiency under the segmented speed control strategy is relatively high, and its energy efficiency is good. In this case, the strategy generation module will determine a smaller energy efficiency optimization value based on the actual situation, possibly only fine-tuning the control parameters of some speed ranges to further optimize energy efficiency. If the power consumption rate is higher than the preset rate, it indicates that the compressor's power consumption exceeds the expected level, and energy efficiency needs improvement. In this case, the strategy generation module will determine a corresponding energy efficiency optimization value based on the degree of difference between the two. This optimization value aims to reduce power consumption and improve the system's energy efficiency level by adjusting the division of the segmented speed ranges, the speed control range of each segment, or the power output characteristics.

[0058] Throughout the implementation process, the strategy generation module needs to continuously interact with the data sensing module to monitor changes in speed fluctuations, cooling demand matching, and power consumption rate in real time. When the compressor's operating state changes from unstable to stable, or when the cooling demand matching changes significantly, the strategy generation module needs to adjust the speed control strategy and energy efficiency optimization values ​​in a timely manner to adapt to the compressor's actual operating conditions. Simultaneously, the system also needs to consider the complexity and variability of the operating conditions of new energy vehicles during operation, such as the impact of different vehicle speeds, road conditions, and air conditioning loads on the compressor's operating state. This ensures that the strategy generation module's decisions accurately reflect the compressor's actual needs, thereby achieving integrated control of the compressor's variable frequency speed regulation and energy efficiency optimization. This minimizes energy consumption and improves the driving range and energy utilization efficiency of new energy vehicles while ensuring cooling performance. Furthermore, to cope with potential anomalies, such as inaccurate data due to sensor malfunctions or drastic speed fluctuations caused by external interference, the system also needs corresponding fault diagnosis and fault-tolerant processing mechanisms to ensure the reliability of the strategy generation module's judgments and decisions, and guarantee the stable operation of the entire system.

[0059] Example 3: In this example, under the condition of determining the energy efficiency optimization value, the parameter control module determines that the energy efficiency optimization value does not meet the requirements based on the comparison result that the response delay is greater than or equal to the preset delay. It then determines to increase the optimization value with the first preset optimization adjustment coefficient based on the comparison result that the difference between the preset response delay and the actual response delay is less than or equal to the preset deviation.

[0060] There is a close data interaction between the parameter control module and the strategy generation module. During system operation, the strategy generation module determines the corresponding speed control strategy based on the compressor's operating status and cooling demand, and transmits information such as the power consumption rate under this strategy to the parameter control module. The parameter control module first needs to determine the energy efficiency optimization value based on the comparison between the power consumption rate and the preset consumption rate. Here, the power consumption rate refers to the power consumption of the compressor per unit time under a specific speed control strategy, and its calculation requires combining data such as the compressor's actual power output and operating time. The preset consumption rate is a reference threshold pre-set by the system based on factors such as the compressor's energy efficiency standards and operating conditions. When the power consumption rate is higher than the preset consumption rate, the parameter control module determines that energy efficiency optimization is needed, and determines an initial energy efficiency optimization value based on the difference between the two. This value aims to reduce power consumption and improve energy efficiency by adjusting relevant parameters.

[0061] After determining the optimal energy efficiency value, the parameter control module needs to monitor the response delay during the adjustment process in real time. The response delay refers to the time elapsed from when the system issues an adjustment command to when the compressor actually executes the command and produces the corresponding effect. The parameter control module collects the compressor's response data to the adjustment command in real time through sensors or other monitoring devices and calculates the actual response delay. This response data acquisition needs to be highly real-time and accurate. For example, the response delay can be determined by monitoring parameters such as the time it takes for the compressor speed to change and the timing of power output adjustments, ensuring that the system's response is captured promptly.

[0062] The parameter control module compares the actual response delay with the preset delay. The preset delay is a time threshold determined during the system design phase based on factors such as the compressor's mechanical characteristics, the control algorithm's processing speed, and actual operational requirements; it represents the system's expected response speed. When the actual response delay is greater than or equal to the preset delay, the parameter control module determines that the energy efficiency optimization value does not meet the requirements. This is because a longer response delay indicates that the system's execution speed of energy efficiency optimization commands is slow, and it may not be able to adapt to changes in the compressor's operating state in a timely manner, thus affecting the effectiveness of energy efficiency optimization and causing the energy efficiency optimization value to fail to reach the expected target.

[0063] After determining that the energy efficiency optimization value does not meet the requirements, the parameter control module needs to further analyze the difference between the preset response delay and the actual response delay. Specifically, the parameter control module calculates the difference between the two and compares it with the preset deviation. The preset deviation is an allowable range set by the system for the difference in response delay, and its determination takes into account factors such as normal fluctuations that may occur during compressor operation and sensor measurement errors. When the difference between the preset response delay and the actual response delay is less than or equal to the preset deviation, it indicates that although the response delay exceeds the preset delay, the difference is within an acceptable range and is considered a relatively small deviation.

[0064] In this scenario, the parameter control module determines to increase the optimized value using a first preset optimization adjustment coefficient. This first preset optimization adjustment coefficient is a fixed value pre-set by the system, and its magnitude is determined based on factors such as the energy efficiency optimization target, the compressor's adjustment precision, and the degree of deviation in response delay. By increasing the optimized value using this first preset optimization adjustment coefficient, the parameter control module aims to moderately adjust the energy efficiency optimization value with minimal deviation in response delay, thereby shortening the response delay, improving the system's response speed, and ensuring that the energy efficiency optimization value better meets the requirements.

[0065] For example, assuming the preset response delay is T0 and the actual response delay is T1, when T1 ≥ T0 and T1 - T0 ≤ ΔT (ΔT is the preset deviation), the parameter control module will multiply the current energy efficiency optimization value by (1 + K1), where K1 is the first preset optimization adjustment coefficient. After increasing the optimization value in this way, the system will reissue the adjustment command and monitor the response delay again to determine whether the adjusted energy efficiency optimization value can shorten the response delay to below the preset delay.

[0066] Throughout the implementation process, the parameter control module needs to continuously collect, calculate, compare, and make decisions based on data. This requires the module to have efficient data processing capabilities and a rapid response mechanism to ensure timely detection of abnormal response delays and the implementation of corresponding adjustments. Simultaneously, the system must consider various complex operating conditions that new energy vehicles may encounter during operation, such as acceleration, deceleration, and hill climbing. These changes in operating conditions may cause sudden shifts in compressor load, thus affecting response delays. Therefore, the parameter control module needs strong adaptability, accurately determining the compliance of energy efficiency optimization values ​​under different operating conditions and reasonably determining optimization adjustment coefficients to ensure the effectiveness of energy efficiency optimization.

[0067] Furthermore, to improve the system's reliability and stability, the parameter control module also needs to possess a certain degree of fault tolerance. For example, when a sensor experiences a brief malfunction leading to inaccurate response delay data, the parameter control module should be able to process the data through methods such as data filtering and outlier detection to avoid making incorrect decisions based on erroneous data. Simultaneously, the system can also incorporate multiple verification mechanisms, such as combining data from multiple sensors to determine the response delay, thereby improving data accuracy and reliability.

[0068] Example 4: In this example, under the condition of determining the energy efficiency optimization value, the parameter control module determines that the energy efficiency optimization value does not meet the requirements based on the comparison result that the response delay is greater than or equal to the preset delay. It then determines to increase the optimization value with the second preset optimization adjustment coefficient based on the comparison result that the difference between the preset response delay and the actual response delay is greater than the preset deviation.

[0069] The parameter control module and the strategy generation module maintain real-time data interaction. After the strategy generation module determines the speed control strategy based on the compressor's operating status, it transmits information such as the power consumption rate to the parameter control module. The parameter control module needs to determine the energy efficiency optimization value based on the comparison between the power consumption rate and the preset consumption rate. For example, under the segmented speed control strategy, if the compressor operates at a certain speed range with an actual power consumption rate of 1.2 kW / h and a preset consumption rate of 1.0 kW / h, the parameter control module determines that energy efficiency needs to be optimized and initially determines an energy efficiency optimization value, such as setting it to increase the power adjustment range by 5% to reduce power consumption.

[0070] After determining the optimal energy efficiency value, the parameter control module begins monitoring the response delay during the adjustment process. Monitoring the response delay is achieved through sensors and timers within the system. For example, the timer starts counting from when the system issues a command to increase the compressor speed until the actual change in compressor speed begins; this time is the response delay. Assuming the preset delay is 500 milliseconds, if the actual response delay is 650 milliseconds during a certain adjustment, the parameter control module compares the actual delay and finds it exceeds the preset delay. It then determines that the current optimal energy efficiency value does not meet the requirements, meaning the system failed to complete the adjustment within the expected time, potentially affecting the energy efficiency optimization effect.

[0071] The parameter control module calculates the difference between the preset response delay and the actual response delay, i.e., 650 milliseconds - 500 milliseconds = 150 milliseconds, and compares this difference with the preset deviation. The preset deviation needs to take into account the fluctuation range during normal system operation; for example, the preset deviation is 100 milliseconds. When the difference of 150 milliseconds is greater than the preset deviation of 100 milliseconds, it indicates that the deviation in response delay is large. This may be because the current energy efficiency optimization value setting is not effectively driving the compressor to respond quickly, or changes in external operating conditions have increased the system load, causing a significant lag in the execution speed of the adjustment command.

[0072] In this situation, the parameter control module determines to increase the optimized value using a second preset optimization adjustment coefficient. This second preset optimization adjustment coefficient is typically larger than the first preset optimization adjustment coefficient to address larger response delay deviations. For example, the first preset optimization adjustment coefficient is 0.1, and the second preset optimization adjustment coefficient is 0.3. Assuming the original energy efficiency optimization value is to reduce the power target at a certain speed range by 10%, when it is determined that the second preset optimization adjustment coefficient is needed to increase the optimization value, the new optimization value becomes a reduction of 10% × (1 + 0.3) = 13%. This means that by increasing the power adjustment range, the compressor receives a larger drive signal during the adjustment process, thereby shortening the response delay.

[0073] In practical implementation, the parameter control module needs to continuously collect response delay data. For example, when a new energy vehicle encounters a hill climb, the battery output voltage fluctuates, causing the power response of the compressor drive motor to slow down. In this case, the actual response delay may increase from 400 milliseconds under normal operating conditions to 700 milliseconds. The parameter control module compares this to the preset delay of 500 milliseconds and finds a difference of 200 milliseconds, which is greater than the preset deviation of 100 milliseconds. It then activates a mechanism to increase the optimized value using a second preset optimization adjustment coefficient. Assuming the original optimized value was to increase the speed from 2000 rpm to 2200 rpm to match the cooling demand, after increasing the optimized value, the new target speed is adjusted to 2300 rpm. By increasing the speed adjustment range, the compressor can still respond to adjustment commands more quickly under voltage fluctuation conditions.

[0074] The parameter control module also needs to consider the differences in response characteristics under different speed control strategies. For example, in a continuous speed control strategy, the compressor speed can be continuously adjusted, and the response delay may be significantly affected by the motor's speed regulation inertia; while in a segmented speed control strategy, the response delay may be affected by the action time of the mechanical switching components when switching between different speed segments. Therefore, the preset delay and preset deviation settings need to be configured differently for different strategies. For example, under a continuous speed control strategy, the preset delay can be set to 400 milliseconds and the preset deviation to 80 milliseconds; under a segmented speed control strategy, the preset delay can be set to 600 milliseconds and the preset deviation to 120 milliseconds, to adapt to the response characteristics of different strategies.

[0075] After the parameter control module increases the optimized value using the second preset optimization adjustment coefficient, it will continue to monitor the subsequent response delay. For example, after adjusting the optimized value, if the adjustment command is issued again and the response delay is reduced from 700 milliseconds to 550 milliseconds, the difference of 550 milliseconds - 500 milliseconds = 50 milliseconds is less than the preset deviation of 100 milliseconds. Then, the module can switch to the first preset optimization adjustment coefficient for fine-tuning. If the response delay is still greater than the preset delay and the difference exceeds the preset deviation, it may be necessary to increase the optimized value again using the second preset optimization adjustment coefficient, or trigger the system calibration module to perform deeper parameter adjustments.

[0076] Throughout the process, the parameter control module must work collaboratively with sensors, controllers, and other components in the system. For example, the current sensor needs to provide real-time feedback on the compressor motor's operating current to determine the actual effect of power regulation; the speed sensor needs to accurately monitor speed changes to provide data support for calculating response delay. Simultaneously, the parameter control module's decision-making logic must be fault-tolerant. If a response delay data point becomes abnormal due to sensor interference (e.g., a sudden jump to 1000 milliseconds), the module must use a data filtering algorithm (such as moving average filtering) to eliminate outliers and avoid misjudgments.

[0077] The system also needs to consider the impact of battery voltage changes in new energy vehicles on response delay. When the battery charge is low, the voltage drop may weaken the motor's driving capability and increase the response delay. In this case, when the parameter control module detects that the response delay deviation exceeds the preset value, in addition to increasing the optimization value, it can also coordinate with the battery management system to obtain the voltage status. If the voltage is lower than the threshold, the adjustment coefficient will be appropriately increased when increasing the optimization value to compensate for the impact of insufficient voltage on the response speed.

[0078] The core of this embodiment lies in the parameter control module's ability to monitor response delay in real time. When the deviation is large, it increases the energy efficiency optimization value with a larger adjustment coefficient, thereby shortening the system response time and ensuring the effective implementation of energy efficiency optimization measures. This process requires dynamic adjustment of the optimization strategy based on parameter changes under specific operating conditions, such as vehicle load, battery voltage, and compressor speed range, to achieve integrated control of variable frequency speed regulation and energy efficiency optimization, improving system energy efficiency while ensuring cooling requirements.

[0079] Example 5: In this example, the system correction module is connected to the parameter control module and the energy efficiency evaluation module. Under the condition that a corresponding speed control strategy is implemented for the compressor, the module determines that the speed and power do not match based on the comparison results of the energy efficiency conversion ratio (EER) being less than the preset EER at each operating point. It then determines to increase the speed using a first preset speed adjustment coefficient based on the comparison results of the EER being greater than or equal to the preset ratio. Simultaneously, it determines that the speed and power match based on the comparison results of the EER being equal to the preset EER, and maintains the current speed and power parameters without adjustment. Furthermore, under the condition that a corresponding speed control strategy is implemented for the compressor, the energy efficiency evaluation module determines that the speed and power do not match based on the comparison results of the EER being less than the preset EER at each operating point. It then determines to reduce the power using a first preset power adjustment coefficient based on the comparison results of the difference between the EER and the preset EER being less than or equal to a preset difference, or to reduce the power using a second preset power adjustment coefficient based on the comparison results of the difference being greater than a preset difference.

[0080] When the compressor executes the speed control strategy, the system calibration module needs to acquire the energy efficiency conversion ratio (EER) data for each operating point in real time. The EER is an indicator that measures the efficiency of the cooling capacity produced by the compressor under unit power input. Its data comes from the real-time calculation of compressor operating parameters by the energy efficiency assessment module, such as by collecting parameters like the compressor's input power and cooling capacity output for comprehensive evaluation. The preset EER is a benchmark value pre-set by the system based on factors such as the compressor's design energy efficiency standards and the energy consumption requirements of new energy vehicles, used to determine whether the current energy efficiency meets the standards.

[0081] When the energy efficiency conversion ratio (EER) at a certain operating point is less than the preset EER, the system calibration module determines that the speed and power matching relationship under that operating point does not meet the requirements, meaning that the current speed and power settings have failed to enable the compressor to achieve the expected energy efficiency level. In this case, the system calibration module needs to further analyze the ratio of the EER to the preset EER. For example, if the preset EER is 3.5 and the EER at a certain operating point is 3.0, the ratio is 3.0 / 3.5≈0.86. If the preset ratio is set to 0.8, then this ratio is greater than or equal to the preset ratio, indicating that the difference between the EER and the preset value is relatively small. In this situation, the system calibration module determines to increase the speed using a first preset speed adjustment coefficient. For example, if the first preset speed adjustment coefficient is set to 0.05, then the current speed will be increased from 2500 rpm to 2500 × (1 + 0.05) = 2625 rpm. By moderately increasing the speed, the compressor's cooling efficiency is optimized, causing the EER to approach the preset value.

[0082] If the energy conversion ratio at another operating point is 2.8, and its ratio to the preset conversion ratio of 3.5 is 0.8, which equals the preset ratio, the mechanism of increasing the speed with the first preset speed adjustment coefficient is also triggered. However, when the energy conversion ratio is 2.5, and the ratio is 0.71, which is less than the preset ratio of 0.8, the system correction module determines to increase the speed with the second preset speed adjustment coefficient. The second preset speed adjustment coefficient is usually greater than the first preset coefficient. For example, if it is set to 0.1, the speed will be increased from 2500 rpm to 2500 × (1 + 0.1) = 2750 rpm, using a larger speed increase to enhance the cooling capacity output and compensate for the large difference in energy conversion ratio.

[0083] Meanwhile, the energy efficiency assessment module will also activate the power adjustment mechanism when it detects that the energy efficiency conversion ratio is less than the preset conversion ratio. The energy efficiency assessment module will calculate the difference between the energy efficiency conversion ratio and the preset conversion ratio, for example, the difference can be measured by the absolute value of the difference between the two. The preset difference is a threshold set by the system to judge the degree of difference, such as a preset difference of 0.5. When the energy efficiency conversion ratio at a certain operating point is 3.2, and the difference between it and the preset conversion ratio of 3.5 is 0.3, which is less than or equal to the preset difference of 0.5, the energy efficiency assessment module determines to reduce the power by the first preset power adjustment coefficient. For example, if the first preset power adjustment coefficient is 0.04, then the current power will be reduced from 800W to 800×(1-0.04)=768W, thus optimizing the energy efficiency conversion ratio by slightly reducing the power.

[0084] If the energy conversion ratio is 2.9, and the difference from the preset conversion ratio is 0.6, which is greater than the preset difference of 0.5, the energy efficiency assessment module will reduce the power using the second preset power adjustment coefficient. For example, if the second preset coefficient is 0.08, the power will be reduced from 800W to 800×(1-0.08)=736W. This larger power reduction will encourage the energy conversion ratio to recover. During the power adjustment process, the energy efficiency assessment module must ensure that the compressor's cooling capacity still meets the vehicle's cooling needs after the power reduction, avoiding insufficient cooling effect due to excessive power reduction.

[0085] Furthermore, when the system calibration module detects that the energy efficiency conversion ratio at a certain operating point is equal to the preset conversion ratio, it determines that the matching relationship between speed and power under that operating condition meets the requirements. At this time, the current speed and power parameters are not adjusted to maintain the compressor operating in a high-efficiency state. For example, if the compressor operates at a speed of 3000 rpm and a power of 900W, and the energy efficiency conversion ratio is exactly equal to the preset conversion ratio of 3.5, the system calibration module will not trigger any adjustment action, allowing the compressor to continue operating under that condition.

[0086] In practical applications, the system calibration module and the energy efficiency assessment module need to work together, taking corresponding adjustment measures based on different deviations in the energy efficiency conversion ratio. For example, when the energy efficiency conversion ratio at a certain operating point is lower than the preset conversion ratio and the difference is significant, the system calibration module increases the speed using a second preset speed adjustment coefficient, while the energy efficiency assessment module decreases the power using a second preset power adjustment coefficient. This dual adjustment of speed and power quickly optimizes energy efficiency. Conversely, when the deviation in the energy efficiency conversion ratio is small, a smaller adjustment coefficient is used for fine-tuning to avoid over-adjustment that could cause system fluctuations.

[0087] The system also needs to consider parameter changes under different operating conditions. For example, when the vehicle is traveling at high speed, the compressor load may increase, and the energy conversion ratio may decrease. In this case, the system calibration module and energy efficiency assessment module need to dynamically adjust the speed and power parameters based on the real-time collected energy conversion ratio data. For example, when the vehicle is traveling at high speed, the outside temperature rises, and the cooling demand inside the vehicle increases. When the compressor is running at 3500 rpm and 1000W, the energy conversion ratio is 3.2, which is less than the preset conversion ratio of 3.5. The ratio of the compressor to the preset conversion ratio is 0.91 (greater than the preset ratio of 0.8), and the difference is 0.3 (less than the preset difference of 0.5). Then, the system calibration module will increase the speed to 3500 × 1.05 = 3675 rpm using the first preset speed adjustment coefficient, and the energy efficiency assessment module will decrease the power to 1000 × 0.96 = 960W using the first preset power adjustment coefficient. Through the coordinated adjustment of increasing the speed and decreasing the power, the energy conversion ratio is improved while meeting the cooling demand.

[0088] During the adjustment process, the system also needs to monitor the compressor's operating status to prevent speed or power adjustments from exceeding the compressor's safe operating range. For example, when the speed increases to the preset upper limit, even if the energy conversion ratio still does not meet the standard, the system correction module will stop further increasing the speed and instead adjust the power parameters or trigger other optimization strategies through the energy efficiency assessment module. Simultaneously, the system must have data filtering and outlier handling mechanisms to prevent abnormal energy conversion ratio data caused by sensor malfunctions, which could lead to incorrect adjustment actions.

[0089] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0090] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A variable frequency speed regulation and energy efficiency optimization integrated system for a new energy vehicle air conditioning compressor, characterized in that, include: The data sensing module is used to determine the stability of the compressor's operating status based on the amount of speed fluctuation; The strategy generation module, which is connected to the data sensing module, is used to determine the speed control strategy based on the stability of the compressor's operating state, and to determine the correlation between speed and power based on the matching degree of cooling demand under the corresponding speed control strategy. The parameter control module, which is connected to the strategy generation module, is used to determine the energy efficiency optimization value based on the power consumption rate under the condition of the corresponding speed control strategy, and to determine the compliance of the energy efficiency optimization value based on the response delay during the adjustment process. An energy efficiency assessment module, which is connected to the parameter control module, is used to determine the compatibility between speed and power based on the energy conversion ratio at each operating point under the condition of the corresponding speed control strategy. The system calibration module, which is connected to the parameter control module and the energy efficiency evaluation module, is used to determine the improvement optimization value based on the difference between the preset response delay and the actual response delay when the energy efficiency optimization value does not meet the requirements, and to determine the improvement optimization value based on the difference between the preset response delay and the actual response delay when the energy efficiency optimization value does not meet the requirements, or to determine the power reduction based on the difference between the energy efficiency conversion ratio and the preset conversion ratio.

2. The new energy vehicle air conditioning compressor variable frequency speed regulation and energy efficiency optimization integrated system according to claim 1, characterized in that, The strategy generation module determines that the compressor is operating stably based on the comparison result that the speed fluctuation is less than the preset fluctuation, and determines that the higher the speed, the lower the power under the continuous speed control strategy based on the comparison result that the cooling demand matching degree is greater than or equal to the preset matching degree. The energy efficiency optimization value is determined based on the comparison result of the power consumption rate and the preset consumption rate.

3. The new energy vehicle air conditioning compressor variable frequency speed regulation and energy efficiency optimization integrated system according to claim 1, characterized in that, The strategy generation module determines that the compressor's operating state is unstable based on the comparison result of the speed fluctuation being greater than or equal to the preset fluctuation amount, and determines that the higher the speed, the higher the power under the segmented speed control strategy based on the comparison result of the cooling demand matching degree being greater than or equal to the preset matching degree. The energy efficiency optimization value is determined based on the comparison result of the power consumption rate and the preset consumption rate.

4. The new energy vehicle air conditioning compressor variable frequency speed regulation and energy efficiency optimization integrated system according to claim 3, characterized in that, Under the condition of determining the energy efficiency optimization value, the parameter control module determines that the energy efficiency optimization value does not meet the requirements based on the comparison result that the response delay is greater than or equal to the preset delay. It then determines to increase the optimization value with the first preset optimization adjustment coefficient based on the comparison result that the difference between the preset response delay and the actual response delay is less than or equal to the preset deviation.

5. The new energy vehicle air conditioning compressor variable frequency speed regulation and energy efficiency optimization integrated system according to claim 3, characterized in that, Under the condition of determining the energy efficiency optimization value, the parameter control module determines that the energy efficiency optimization value does not meet the requirements based on the comparison result that the response delay is greater than or equal to the preset delay. It then determines to increase the optimization value with the second preset optimization adjustment coefficient based on the comparison result that the difference between the preset response delay and the actual response delay is greater than the preset deviation.

6. The new energy vehicle air conditioning compressor variable frequency speed regulation and energy efficiency optimization integrated system according to claim 5, characterized in that, Under the condition that the corresponding speed control strategy is executed on the compressor, the system correction module determines that the speed and power do not match based on the comparison result that the energy efficiency conversion ratio of each operating point is less than the preset conversion ratio, and determines to increase the speed with the first preset speed adjustment coefficient based on the comparison result that the ratio of the energy efficiency conversion ratio to the preset conversion ratio is greater than or equal to the preset ratio.

7. The new energy vehicle air conditioning compressor variable frequency speed regulation and energy efficiency optimization integrated system according to claim 6, characterized in that, Under the condition that the corresponding speed control strategy is executed on the compressor, the system correction module determines that the speed and power do not match based on the comparison result that the energy efficiency conversion ratio is less than the preset conversion ratio at each operating point, and determines to increase the speed with the second preset speed adjustment coefficient based on the comparison result that the ratio of the energy efficiency conversion ratio to the preset conversion ratio is less than the preset ratio.

8. The new energy vehicle air conditioning compressor variable frequency speed regulation and energy efficiency optimization integrated system according to claim 7, characterized in that, Under the condition that the corresponding speed control strategy is executed on the compressor, the energy efficiency evaluation module determines that the speed and power do not match based on the comparison result that the energy efficiency conversion ratio of each operating point is less than the preset conversion ratio, and determines to reduce the power with the first preset power adjustment coefficient based on the comparison result that the difference between the energy efficiency conversion ratio and the preset conversion ratio is less than or equal to the preset difference.

9. The new energy vehicle air conditioning compressor variable frequency speed regulation and energy efficiency optimization integrated system according to claim 8, characterized in that, Under the condition that the corresponding speed control strategy is executed on the compressor, the energy efficiency evaluation module determines that the speed and power do not match based on the comparison result that the energy efficiency conversion ratio of each operating point is less than the preset conversion ratio, and determines to reduce the power with the second preset power adjustment coefficient based on the comparison result that the difference between the energy efficiency conversion ratio and the preset conversion ratio is greater than the preset difference.

10. The new energy vehicle air conditioning compressor variable frequency speed regulation and energy efficiency optimization integrated system according to claim 6, characterized in that, Under the condition that the corresponding speed control strategy is executed on the compressor, the system correction module determines that the speed and power are consistent based on the comparison result that the energy efficiency conversion ratio is equal to the preset conversion ratio, and keeps the current speed and power parameters unchanged.

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