A new energy vehicle power system cooperative control method and system

Abstract

The application is suitable for the field of power and energy collaborative control technology of new energy vehicle power system, and provides a new energy vehicle power system collaborative control method and system.The method comprises the following steps: determining a longitudinal following control strength parameter corresponding to a current driver operation characteristic mode according to a corresponding relationship, and judging whether the longitudinal following control strength parameter exceeds a longitudinal following control strength parameter threshold value; if the judgment is yes, generating a preference correction factor according to the difference between the longitudinal following control strength parameter and the longitudinal following control strength parameter threshold value.The application quantitatively analyzes the coupling influence between the safe following control strategy and the driver operation characteristic mode by introducing the longitudinal following control strength parameter and the energy saving effect consistency parameter, and makes correction through the energy saving execution preference parameter without changing the existing safe following control strategy and without relying on the driving mode prompt, so that the vehicle can maintain stable and predictable energy saving effect in a specific low-speed slope following scene.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of power and energy collaborative control technology of new energy vehicle power system, and particularly relates to a new energy vehicle power system collaborative control method and system. BACKGROUND

[0002] New energy vehicles are usually equipped with a relatively complete power and energy management control system for coordinating control of driving output, brake energy recovery and power distribution under different working conditions. In the prior art, the vehicle system generally adjusts the power system adaptively based on the vehicle operating state, road conditions and the preset driving mode to achieve the energy saving goal under the premise of ensuring driving safety and basic comfort. For example, in the low-speed driving or following vehicle working condition, the existing control strategy can keep the overall energy consumption of the vehicle within a reasonable range by adjusting the acceleration and deceleration response and the energy recovery ratio. At the same time, the driver usually sets the energy saving execution preference parameters in advance in the initial or specific stage of vehicle use to reflect his comprehensive preference for energy consumption, power response and comfort, which remains unchanged for a long time and serves as an important basis for the vehicle system to control energy saving.

[0003] However, in actual application, especially in the low-speed slope following vehicle driving scene, the vehicle often needs to run under the condition of continuous following and superimposed slope load, and the existing power system control strategy usually prioritizes safe following control, thereby issuing a relatively conservative or safe longitudinal control strategy. At the same time, the operation behavior of the driver in such a scene has strong individual difference, and different driver operation characteristic modes will be coupled with the safe following control strategy in the actual driving process, thereby affecting the longitudinal control behavior of the vehicle. Although the existing vehicle system has certain self-learning and adaptive ability, its adjustment object mainly focuses on the working condition change itself, and less on the coupling effect between the driver operation characteristic mode and the control strategy for special recognition and quantitative analysis.

[0004] Therefore, the existing technology still has certain limitations in the low-speed slope following vehicle driving scene. On the one hand, the existing energy management system is difficult to determine whether the intervention caused by the driver's operation characteristic mode has exceeded the adaptive adjustment ability of the system, which easily leads to a decrease in energy recovery effect or an increase in energy consumption; on the other hand, the existing technology usually relies on driving mode switching prompts or whole-process energy consumption statistics for optimization, which is difficult to fine-tune for specific road sections or specific scenes, and easily affects driving comfort. Therefore, there is an urgent need for a technical solution that can collaboratively optimize the energy saving control of the power system for the low-speed slope following vehicle driving scene without changing the existing safe following control strategy and without significantly affecting the driving experience. SUMMARY

[0005] The purpose of this invention is to provide a collaborative control method and system for the power system of new energy vehicles, aiming to solve the problems mentioned in the background art.

[0006] This invention is implemented as follows: a collaborative control method for a new energy vehicle powertrain system, the method comprising:

[0007] When it is determined that the target road segment where the vehicle is about to travel is a low-speed slope following scenario, the current following composite working condition intensity corresponding to the target road segment is obtained, and the historical driving database of the target road segment is retrieved.

[0008] Several samples were selected from the database. The samples had the same energy-saving execution preference parameters and the intensity of the vehicle-following composite working condition as the current samples, but the driver operation characteristics before entering the target road section were different from the current samples.

[0009] The longitudinal following control intensity parameters of each sample during the driving process on the target road segment were obtained, as well as the consistency parameters of energy-saving effect obtained from the post-driving evaluation.

[0010] Establish the correspondence between longitudinal following control intensity parameters and energy-saving effect consistency parameters for several samples, and determine the threshold of longitudinal following control intensity parameters that causes the energy-saving effect consistency parameters to change from a stable state to a deteriorated state.

[0011] Based on the correspondence, the longitudinal following control strength parameter corresponding to the current driver operation characteristic mode is determined, and it is determined whether it exceeds the longitudinal following control strength parameter threshold. If it does, a preference correction factor is generated based on the difference between the longitudinal following control strength parameter and the longitudinal following control strength parameter threshold, and the energy-saving execution preference parameter is corrected based on the preference correction factor.

[0012] As a further limitation of the technical solution of the present invention, the current vehicle-following composite working condition intensity is obtained by predicting and evaluating based on the road slope information, traffic flow information and vehicle current operating status information of the target road section;

[0013] The intensity of the following vehicle composite working condition corresponding to the sample is obtained by evaluating historical operating data of vehicle speed changes, start-stop behavior and following vehicle status collected during the actual driving of the vehicle on the target road section.

[0014] As a further limitation of the technical solution of the present invention, the driver operation feature mode is used to characterize the operation feature mode parameters formed by the driver actively controlling the vehicle during the driving process before entering the target road segment. The operation feature mode parameters are determined based on the change characteristics of the driver control input signal collected by the vehicle.

[0015] As a further limitation of the technical solution of the present invention, the difference in longitudinal following control intensity parameters of different samples comes from the fact that, under the premise that the vehicle's vehicle system issues the same following control strategy based on the same following composite working condition intensity, the longitudinal control related parameters collected by the vehicle during the driving of the target road segment are different due to the different operating characteristic modes of the driver.

[0016] The longitudinal control-related parameters include at least one of longitudinal acceleration / deceleration variation characteristics, driving torque variation characteristics, and braking control variation characteristics; the longitudinal following control strength parameters are determined by comprehensively characterizing the collected longitudinal control-related parameters.

[0017] As a further limitation of the technical solution of the embodiment of the present invention, the process of determining the energy-saving effect consistency parameter includes: after the vehicle completes the driving of the target road segment, obtaining the actual energy-saving effect parameter within the target road segment, wherein the actual energy-saving effect parameter includes at least the energy consumption parameter per unit driving distance and the regenerative braking energy recovery parameter;

[0018] A preset energy-saving effect reference benchmark is retrieved, and based on the energy-saving effect reference benchmark, the expected energy-saving effect parameters are obtained under the condition that the corresponding longitudinal control parameters are adopted and the driver's operation characteristic mode intervention is allowed. The energy-saving effect consistency parameter is determined according to the deviation of the actual energy-saving effect parameters from the expected energy-saving effect parameters.

[0019] As a further limitation of the technical solution of this invention, the step of establishing the correspondence between longitudinal following control intensity parameters and energy-saving effect consistency parameters of several samples, and determining the threshold of longitudinal following control intensity parameters that causes the energy-saving effect consistency parameters to change from a stable state to a deteriorated state, includes:

[0020] Several samples are analyzed and arranged in order of magnitude of the longitudinal following control intensity parameters corresponding to each sample to form a sample sequence;

[0021] Based on the sample sequence, the variation characteristics of the corresponding energy-saving effect consistency parameter with the longitudinal following control intensity parameter are obtained.

[0022] Determine whether there is a turning point in the changing features that causes the energy-saving effect consistency parameter to exceed the preset allowable range and continue to be maintained in subsequent samples. If so, determine the longitudinal following control strength parameter corresponding to the turning point as the longitudinal following control strength parameter threshold that causes the energy-saving effect consistency parameter to change from a stable state to a deteriorated state.

[0023] As a further limitation of the technical solution of this embodiment of the invention, the following steps include: determining the longitudinal following control intensity parameter corresponding to the current driver operation characteristic mode according to the correspondence, and determining whether it exceeds the longitudinal following control intensity parameter threshold; if so, generating a preference correction factor based on the difference between the longitudinal following control intensity parameter and the longitudinal following control parameter threshold, and correcting the energy-saving execution preference parameter according to the preference correction factor:

[0024] From a number of samples, samples that match the current driver operation pattern of the vehicle are selected, the longitudinal following control strength parameter corresponding to the sample is identified, and it is determined whether the longitudinal following control strength parameter exceeds the threshold of the longitudinal following control strength parameter.

[0025] If the determination is yes, then a preference correction factor is generated based on the difference between the identified longitudinal following control strength parameter and the threshold value of the longitudinal following control strength parameter;

[0026] The energy-saving execution preference parameters are corrected based on the preference correction factor to obtain optimized energy-saving execution preference parameters, and the vehicle uses the optimized energy-saving execution preference parameters for energy-saving control when entering the target road segment.

[0027] As a further limitation of the technical solution of this embodiment of the invention, a preset correction formula is used in the process of correcting the energy-saving execution preference parameters. The correction formula is as follows:

[0028] ;

[0029] in, This refers to the revised energy-saving execution preference parameters. This refers to the uncorrected energy-saving performance preference parameter. This refers to the maximum possible value of the energy-saving execution preference parameter. This refers to the identified longitudinal following control strength parameters. This refers to the threshold value of the longitudinal following control strength parameter. This refers to the preference correction factor. This refers to the preset control correction strength coefficient, and it satisfies... .

[0030] A collaborative control system for a new energy vehicle powertrain, the system comprising:

[0031] The road condition identification module is used to obtain the current following composite condition intensity of the target road segment when it is determined that the target road segment to be driven by the vehicle is a low-speed slope following scenario, and to retrieve the historical driving database of the target road segment.

[0032] The sample screening module is used to screen several samples from the database. The samples have the same energy-saving execution preference parameters and vehicle-following composite working condition intensity as the current samples, but the driver operation characteristic patterns before entering the target road segment are different from the current samples.

[0033] The parameter acquisition module is used to acquire the longitudinal following control strength parameters of each sample during the driving process on the target road segment, as well as the energy-saving effect consistency parameters obtained from the post-driving evaluation.

[0034] The threshold determination module is used to establish the correspondence between the longitudinal following control intensity parameters and the energy-saving effect consistency parameters of several samples, and to determine the threshold of the longitudinal following control intensity parameters that causes the energy-saving effect consistency parameters to change from a stable state to a deteriorated state.

[0035] The preference correction module is used to determine the longitudinal following control strength parameter corresponding to the current driver operation characteristic mode according to the correspondence, and to determine whether it exceeds the longitudinal following control strength parameter threshold. If it does, a preference correction factor is generated based on the difference between the longitudinal following control strength parameter and the longitudinal following control strength parameter threshold, and the energy-saving execution preference parameter is corrected according to the preference correction factor.

[0036] As a further limitation of the technical solution of the present invention, the current vehicle-following composite condition intensity is obtained by predicting and evaluating based on the road slope information, traffic flow information and vehicle current operating status information of the target road section; the vehicle-following composite condition intensity corresponding to the sample is obtained by evaluating based on the historical operating data of vehicle speed change, start-stop behavior and following status collected during the actual driving process of the vehicle on the target road section.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] This invention addresses the issue that the adaptive energy management capabilities of new energy vehicles in low-speed incline following scenarios are easily affected by driver operating patterns, and proposes a powertrain cooperative control method. By introducing longitudinal following control intensity parameters and energy-saving effect consistency parameters, the coupling influence between the safe following control strategy and driver operating patterns is quantitatively analyzed. Based on historical samples, a correspondence between the two is established, identifying the key threshold at which the energy-saving effect transitions from a stable state to a deteriorating state. Without changing the existing safe following control strategy and without relying on driving mode prompts, this invention makes small, adaptive adjustments to the long-term unchanged energy-saving execution preference parameters, enabling the vehicle to maintain stable and predictable energy-saving effects in specific low-speed incline following scenarios.

[0039] This method balances energy efficiency and driving comfort, with gradual parameter adjustments that have minimal impact on the driver's subjective experience. It boasts advantages such as low implementation cost, strong engineering feasibility, and clear application scenarios, making it suitable for new energy vehicles that require high-frequency commuting and fixed-route driving. Attached Figure Description

[0040] Figure 1 A flowchart of the method provided in the embodiments of the present invention;

[0041] Figure 2 This is a flowchart illustrating the process of determining the threshold value of the longitudinal following control intensity parameter in the method provided in this embodiment of the invention;

[0042] Figure 3 This is a flowchart illustrating the modification of energy-saving execution preference parameters in the method provided in this embodiment of the invention;

[0043] Figure 4 The application architecture diagram of the system provided in the embodiments of the present invention. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0045] Figure 1 A flowchart of the method provided by an embodiment of the present invention is shown.

[0046] Specifically, a collaborative control method for a new energy vehicle powertrain system includes the following steps:

[0047] Step S100: When it is determined that the target road segment to which the vehicle is about to travel is a low-speed slope following scenario, the current following composite working condition intensity corresponding to the target road segment is obtained, and the historical driving database of the target road segment is retrieved.

[0048] Step S200: Select several samples from the database. The samples have the same energy-saving execution preference parameters and vehicle-following composite working condition intensity as the current samples, but the driver operation characteristic mode before entering the target road section is different from the current samples.

[0049] The current vehicle-following composite condition intensity is predicted and evaluated based on the road slope information, traffic flow information, and current vehicle operating status information of the target road segment; the corresponding vehicle-following composite condition intensity in the sample is evaluated based on the historical operating data of vehicle speed changes, start-stop behavior, and following status collected during the actual driving process of the vehicle on the target road segment.

[0050] The driver operation feature pattern is a parameter used to characterize the operation feature pattern formed by the driver actively controlling the vehicle during the driving process before entering the target road segment. The operation feature pattern parameter is determined based on the change characteristics of the driver control input signal collected by the vehicle.

[0051] In this embodiment of the invention, the vehicle is a new energy vehicle, specifically a pure electric vehicle or a plug-in hybrid electric vehicle. The vehicle possesses energy recovery capabilities, an intelligent vehicle system, an onboard sensing and control system, and cloud-based network communication capabilities. The intelligent vehicle system can perceive, analyze, and process vehicle operating status, driver behavior, and external traffic environment information, thereby achieving comprehensive control and coordinated adjustment of the vehicle's power system.

[0052] This invention primarily addresses the application scenario of low-speed, slope-following driving. This type of scenario typically occurs on fixed road sections with frequent commuting, such as overpass ramps, tunnel entrance / exit ramps, and underground parking lot entrance / exit connecting sections in urban commuting routes. These road sections have a certain longitudinal gradient, and due to dense traffic flow or signal control, vehicles are often in a low-speed, frequent stop-and-go, or continuously following driving conditions. Since vehicles repeatedly pass through such road sections during daily use, the relevant driving data is repeatable and accumulative, providing a practical basis for subsequent analysis and control based on historical samples.

[0053] The core research scenario of this invention is selected as low-speed incline following vehicle scenario because this scenario has certain unique characteristics in the energy management of new energy vehicles. On the one hand, the energy-saving control systems of existing new energy vehicles are already relatively sophisticated, typically possessing the ability to adaptively adjust based on vehicle status and environmental conditions. On the other hand, when using the vehicle, drivers usually pre-set an energy-saving execution preference parameter in the vehicle's infotainment system according to their personal preferences, such as a preference for energy-saving mode, a preference for balanced mode, or a preference for power response mode. This energy-saving execution preference parameter is used to characterize the driver's comprehensive preference for the vehicle's energy consumption level, power response characteristics, and comfort; once set, it is usually not frequently changed over a relatively long period.

[0054] Under current technological conditions, the energy management and recovery control strategies of vehicle systems typically possess a certain degree of self-learning and adaptive capabilities. Even under relatively simple driving conditions such as low speed, slow driving, or following other vehicles, they can maintain the overall energy consumption of the vehicle at an optimal level by adjusting drive and braking control strategies. Therefore, under most conventional operating conditions, existing energy-saving control systems can adapt well to low-speed incline driving scenarios.

[0055] However, those skilled in the art have found through practical applications and data analysis that in low-speed hill-following scenarios, drivers often exhibit different driving characteristics due to varying traffic conditions, psychological expectations, or operating habits. For example, some drivers tend to frequently accelerate and brake slightly while following another vehicle on a slope, while others tend to maintain a larger following margin and perform relatively gentle longitudinal control. When these driving characteristics persist to a certain extent, especially in the case of continuous following on a low-speed slope, the vehicle's longitudinal control behavior gradually deviates from the longitudinal operating characteristics expected by the energy-saving execution preference parameters. This leads to a decrease in the original adaptive energy-saving effect of the vehicle's infotainment system, manifested as insufficient energy recovery or increased energy consumption.

[0056] Based on the above understanding, in step S100 of this invention, when it is determined that the target road segment the vehicle is about to travel on is a low-speed slope following scenario, the current following composite condition intensity corresponding to the target road segment is obtained, and the historical driving database of the target road segment is retrieved. The current following composite condition intensity is used to characterize the comprehensive following level faced by the vehicle when it is about to enter the target road segment. It can be predicted and evaluated based on the road slope information, traffic flow information, and the vehicle's current operating status information of the target road segment. For example, the operating condition prediction of the target road segment can be made by combining road slope data obtained from high-precision maps, real-time traffic flow information from the Internet of Vehicles or the cloud, and vehicle speed, acceleration, and forward distance information collected by the vehicle itself. The following composite condition intensity corresponding to the sample is evaluated based on historical operating data such as vehicle speed changes, start-stop behavior, and following status collected during the actual driving process of the vehicle on the target road segment. The current vehicle-following composite operating condition intensity and the vehicle-following composite operating condition intensity in the sample are obtained using different methods, corresponding to the predicted operating condition and the historical actual operating condition, respectively. Both are mature and feasible technical means in the existing technology and can be implemented under the existing vehicle and vehicle system architecture.

[0057] In step S200, several samples are selected from the historical driving database. These samples have the same energy-saving execution preference parameters and following-vehicle composite operating condition intensity as the current samples, but the driver's operating characteristic patterns before entering the target road segment are different from the current samples. This selection method highlights the impact of driver operating characteristic patterns—a human factor—on vehicle longitudinal control behavior and energy-saving effects while maintaining consistency in energy-saving execution preference parameters and objective operating conditions, thus providing a comparative basis for subsequent analysis.

[0058] The driver operation characteristic pattern is used to reflect the driver's longitudinal control characteristics during the driving process before entering the target road segment. The parameters of the operation characteristic pattern can be determined based on the changing characteristics of the driver's control input signals collected by the vehicle, such as a comprehensive evaluation based on changes in accelerator pedal input, brake pedal input, and changes in the vehicle's longitudinal motion state. Those skilled in the art can determine the driver operation characteristic pattern using different signal combinations or processing methods according to actual application needs; this invention does not limit this.

[0059] By screening samples and differentiating driver operation feature patterns in step S200, this invention can further reveal the impact of different driver operation feature patterns on the longitudinal following control strength and energy-saving effect of the vehicle under the same objective working conditions and the same energy-saving execution preference parameters for the low-speed slope following driving scenario identified in step S100. This lays the foundation for subsequent threshold identification and adaptive correction of energy-saving execution preference parameters.

[0060] Furthermore, the new energy vehicle power system coordinated control method also includes the following steps:

[0061] Step S300: Obtain the longitudinal following control strength parameters of each sample during the driving process on the target road segment, as well as the energy-saving effect consistency parameters obtained from the post-driving evaluation.

[0062] The differences in longitudinal following control intensity parameters among different samples arise from the fact that, under the premise that the vehicle's infotainment system issues the same following control strategy based on the same following composite operating conditions, the longitudinal control-related parameters collected during the vehicle's journey on the target road segment differ due to different driver operation characteristic modes. The longitudinal control-related parameters include at least one of longitudinal acceleration / deceleration change characteristics, driving torque change characteristics, and braking control change characteristics. The longitudinal following control intensity parameters are determined by comprehensively characterizing the collected longitudinal control-related parameters.

[0063] The process of determining the consistency parameter of energy saving effect includes: after the vehicle completes the target road segment, obtaining the actual energy saving effect parameters within the target road segment, wherein the actual energy saving effect parameters include at least the energy consumption parameter per unit driving distance and the regenerative braking energy recovery parameter; retrieving a preset energy saving effect reference benchmark, and based on the energy saving effect reference benchmark, obtaining the expected energy saving effect parameters under the condition of taking corresponding longitudinal control related parameters and allowing the driver to intervene in the characteristic mode of operation; and determining the consistency parameter of energy saving effect based on the deviation of the actual energy saving effect parameters from the expected energy saving effect parameters.

[0064] In this embodiment of the invention, after completing the sample screening in steps S100 and S200, in step S300, the longitudinal following control intensity parameters of each sample during the driving process on the target road segment and the energy-saving effect consistency parameters obtained after the driving of the target road segment are obtained are acquired respectively.

[0065] First, regarding the longitudinal following control intensity parameters, this invention comprehensively characterizes the longitudinal following control intensity parameters based on the longitudinal control-related parameters collected during the vehicle's travel on the target road segment, reflecting the coupling result between the following control strategy and the driver's operating characteristic patterns. Specifically, under the premise that the vehicle's infotainment system issues the same following control strategy based on the same following composite operating condition intensity, different drivers will exhibit different longitudinal control behaviors during actual driving due to different operating characteristic patterns, resulting in differences in the longitudinal control-related parameters collected by the vehicle.

[0066] The longitudinal control-related parameters include at least one of longitudinal acceleration / deceleration variation characteristics, drive torque variation characteristics, and braking control variation characteristics. For example, the aggressiveness or gentleness of the vehicle's longitudinal control behavior can be reflected by analyzing the magnitude of acceleration changes, acceleration / deceleration frequency, drive motor output torque changes, and braking system intervention characteristics within the target road segment. This invention comprehensively characterizes the above-mentioned longitudinal control-related parameters to determine the corresponding longitudinal following control intensity parameters, thereby quantitatively describing the overall intensity level of the vehicle's longitudinal following control behavior under the combined effects of specific following composite operating conditions and specific driver operation characteristic patterns.

[0067] It should be noted that existing technologies typically focus only on the generation and distribution of the following control strategy itself, with little quantitative analysis of the coupling effect between the following control strategy and the driver's operating characteristic patterns during actual driving. This invention introduces a longitudinal following control intensity parameter and uses historical driving data to objectively characterize this coupling effect, thereby providing a foundation for subsequent identification of energy-saving effect trends and preference adjustments.

[0068] Secondly, in step S300, energy-saving consistency parameters are further determined. Unlike the common method in existing technologies that statistically analyzes energy consumption based on the entire journey or long distance, this invention adopts a short-distance identification method targeting the target road segment, that is, it only evaluates the actual energy-saving effect of the vehicle in a specific low-speed slope following scenario. This method can more sensitively reflect the changes in the vehicle's energy-saving control effect under specific operating conditions and specific driving behaviors.

[0069] Specifically, after the vehicle completes its journey along the target road segment, the actual energy-saving effect parameters within that segment are obtained. These parameters include at least energy consumption per unit distance traveled and regenerative braking energy recovery parameters. Subsequently, a preset energy-saving effect reference benchmark is retrieved, and based on this benchmark, the expected energy-saving effect parameters are obtained under conditions where corresponding longitudinal control parameters are applied and driver intervention in the operating characteristic mode is permitted. This energy-saving effect reference benchmark can be constructed from sample data in a historical driving database under the same energy-saving execution preference parameters and the same following-vehicle composite operating condition intensity, with the longitudinal following-vehicle control intensity parameters remaining within a stable range. This method represents a mature data statistics and benchmark modeling approach in the existing technology and can be implemented in existing vehicle systems or cloud platforms.

[0070] By comparing the actual energy-saving effect parameters within the target road segment with the expected energy-saving effect parameters obtained based on an energy-saving effect reference benchmark, the deviation between the two is calculated, thereby determining the energy-saving effect consistency parameter. This energy-saving effect consistency parameter characterizes the degree of consistency between the actual energy-saving effect and the energy-saving effect expected by the energy-saving execution preference parameters during vehicle operation on the target road segment.

[0071] In summary, the longitudinal following control strength parameter reflects the actual coupling performance between the following control strategy and the driver's operating characteristic mode within the target road segment, while the energy-saving effect consistency parameter reflects the specific impact of this coupling performance on the energy-saving effect. By simultaneously introducing these two parameters in step S300, this invention can conduct targeted analysis of energy management issues in low-speed slope following scenarios from both the control behavior and energy-saving effect perspectives, providing a reliable basis for subsequent threshold identification and adaptive correction of energy-saving execution preference parameters.

[0072] Furthermore, the new energy vehicle power system coordinated control method also includes the following steps:

[0073] Step S400: Establish the correspondence between longitudinal following control strength parameters and energy-saving effect consistency parameters for several samples, and determine the threshold of longitudinal following control strength parameters that causes the energy-saving effect consistency parameters to change from a stable state to a deteriorated state.

[0074] Specifically, Figure 2 A flowchart is shown to determine the threshold values ​​for longitudinal following control strength parameters.

[0075] The process of establishing the correspondence between longitudinal following control intensity parameters and energy-saving effect consistency parameters for several samples, and determining the threshold of longitudinal following control intensity parameters that causes the energy-saving effect consistency parameters to change from a stable state to a deteriorated state, specifically includes the following steps:

[0076] Step S401: Analyze several samples and arrange them in order of magnitude of the longitudinal following control intensity parameters corresponding to each sample to form a sample sequence;

[0077] Step S402: Based on the sample sequence, obtain the variation characteristics of the corresponding energy-saving effect consistency parameter with the longitudinal following control intensity parameter.

[0078] Step S403: Determine whether there is a turning point in the changing features that causes the energy-saving effect consistency parameter to exceed the preset allowable range and continue to be maintained in subsequent samples. If there is, determine the longitudinal following control strength parameter corresponding to the turning point as the longitudinal following control strength parameter threshold that causes the energy-saving effect consistency parameter to change from a stable state to a deteriorated state.

[0079] In this embodiment of the invention, after obtaining the longitudinal following control strength parameter and the energy-saving effect consistency parameter in step S300, step S400 is further executed to establish the correspondence between the longitudinal following control strength parameter and the energy-saving effect consistency parameter of several samples, and to determine the threshold of the longitudinal following control strength parameter that causes the energy-saving effect consistency parameter to change from a stable state to a deteriorated state.

[0080] Specifically, such as Figure 2 As shown, in step S401, several samples obtained from the historical driving database are analyzed and arranged according to the magnitude of the longitudinal following control intensity parameters corresponding to each sample, forming a sample sequence. This arrangement method allows for the orderly organization of the longitudinal following control intensity exhibited by different samples on the target road segment from low to high, providing a clear reference order for subsequent analysis of the energy-saving effect variation patterns.

[0081] In step S402, based on the sample sequence, the variation characteristics of the corresponding energy-saving effect consistency parameter with the longitudinal following control intensity parameter are obtained. Since each sample maintains consistency in energy-saving execution preference parameters and following composite operating condition intensity, the variation characteristics can reflect the influence trend of different longitudinal following control intensity levels on energy-saving effect consistency under the same objective operating conditions. Through this step, it is possible to observe whether the energy-saving effect consistency parameter remains relatively stable or shows a significant downward trend as the longitudinal following control intensity gradually increases.

[0082] In step S403, it is determined whether there is a turning point among the changing characteristics that causes the energy-saving effect consistency parameter to exceed a preset allowable range and remain so in subsequent samples. The preset allowable range is used to characterize the range of energy-saving effect fluctuations allowed by the existing vehicle energy control system within its normal adaptive adjustment capability. In other words, within this preset allowable range, changes in the energy-saving effect consistency parameter are considered normal fluctuations that the vehicle system's adaptive capability can effectively repair or absorb, and will not have a significant impact on the overall energy-saving effect.

[0083] It should be noted that, as mentioned earlier, the vehicle energy control systems of existing new energy vehicles typically possess a certain degree of adaptive capability. Under different driving behaviors and slight control interventions, they can adjust energy recovery strategies or power distribution methods to maintain energy consumption levels within a relatively stable range. Therefore, fluctuations in the consistency parameter of energy-saving performance within a certain range are normal in low-speed hill-climbing scenarios. The preset allowable range in this invention is precisely used to characterize the fluctuation range that this adaptive adjustment can cover. It can be set based on statistical results of historical stable samples or engineering experience, and is a parameter setting method achievable in existing technologies.

[0084] However, when the consistency parameter of energy-saving effect exceeds the preset allowable range and continues to be maintained in subsequent samples where the longitudinal following control intensity further increases, it indicates that in this low-speed slope following scenario, the coupling intervention between the vehicle's longitudinal following control behavior and the driver's operating characteristic mode has exceeded the effective repair range of the vehicle's energy control system's adaptive capability. At this point, the turning point appearing in the changing characteristics reflects the key point where the energy-saving effect changes from a stable state to a deteriorating state.

[0085] In this case, the longitudinal following control strength parameter corresponding to the turning point is determined as the threshold value of the longitudinal following control strength parameter that causes the energy-saving effect consistency parameter to change from a stable state to a deteriorated state. Through this method, the present invention can identify energy management problems in low-speed slope following situations, caused by the coupling between driver operation characteristic patterns and the safe following control strategy, which are difficult for the vehicle system's adaptive capabilities to fully address, without interfering with existing safe following control strategies.

[0086] In layman's terms, in low-speed hill-following scenarios, the vehicle's infotainment system often prioritizes safe following control, thus implementing a relatively conservative longitudinal control strategy. However, due to the inherent coupling of longitudinal following control intensity parameters, the driver's actual driving behavior may positively or negatively interfere with this safe following control. Furthermore, the driver's operating characteristics are random and diurnal variations, making it difficult for the vehicle's infotainment system to predict the extent of their impact on energy recovery. This invention uses the correspondence and threshold recognition mechanism established in step S400 to determine whether the adaptive adjustment of the existing vehicle energy control system remains effective in this specific low-speed hill-following scenario, thereby providing a basis for subsequent correction of energy-saving execution preference parameters.

[0087] Furthermore, the new energy vehicle power system coordinated control method also includes the following steps:

[0088] Step S500: Based on the correspondence, determine the longitudinal following control strength parameter corresponding to the current driver operation characteristic mode, and determine whether it exceeds the longitudinal following control strength parameter threshold. If it does, generate a preference correction factor based on the difference between the longitudinal following control strength parameter and the longitudinal following control strength parameter threshold, and correct the energy-saving execution preference parameter based on the preference correction factor.

[0089] Specifically, Figure 3 A flowchart is shown for modifying the energy-saving execution preference parameters.

[0090] Specifically, based on the correspondence, the longitudinal following control strength parameter corresponding to the current driver operation characteristic mode is determined, and it is determined whether it exceeds the longitudinal following control strength parameter threshold. If it does, a preference correction factor is generated based on the difference between the longitudinal following control strength parameter and the longitudinal following control parameter threshold, and the energy-saving execution preference parameter is corrected based on the preference correction factor. The steps include:

[0091] Step S501: Select samples that match the current driver operation characteristic mode from a number of samples, identify the longitudinal following control strength parameter corresponding to the sample, and determine whether the longitudinal following control strength parameter exceeds the longitudinal following control strength parameter threshold.

[0092] Step S502: If the determination is yes, then generate a preference correction factor based on the difference between the identified longitudinal following control strength parameter and the longitudinal following control strength parameter threshold.

[0093] Step S503: The energy-saving execution preference parameters are corrected according to the preference correction factor to obtain optimized energy-saving execution preference parameters, and the vehicle uses the optimized energy-saving execution preference parameters for energy-saving control when driving into the target road segment.

[0094] In the process of correcting the energy-saving performance preference parameters, a preset correction formula is used, which is:

[0095] ;

[0096] in, This refers to the revised energy-saving execution preference parameters. This refers to the uncorrected energy-saving performance preference parameter. This refers to the maximum possible value of the energy-saving execution preference parameter. This refers to the identified longitudinal following control strength parameters. This refers to the threshold value of the longitudinal following control strength parameter. This refers to the preference correction factor. This refers to the preset control correction strength coefficient, and it satisfies... .

[0097] In this embodiment of the invention, the core objective of step S500 is to enable the vehicle to maintain good fuel efficiency in specific low-speed incline following scenarios by making small, adaptive adjustments to the long-term unchanged fuel-saving execution preference parameters. This step is based on the important premise that, in low-speed incline following scenarios, the longitudinal power demand of the vehicle changes relatively smoothly. When the fuel-saving execution preference parameters are moderately increased, the impact on vehicle comfort is small and may even be difficult for the driver to perceive subjectively. This is because, in the continuous following state on a low-speed incline, the vehicle itself is already in a low-speed, low-longitudinal-acceleration range, and the changes in power output and braking control are limited. Therefore, fine-tuning the fuel-saving execution preference parameters will not cause obvious acceleration changes or abrupt braking sensations.

[0098] Meanwhile, in situations involving long-distance, low-speed driving on inclines, especially on continuous uphill sections, vehicle energy consumption increases significantly. If energy recovery control is insufficient, it will directly lead to increased energy consumption for the entire journey. Therefore, compared to common human-machine interaction methods in existing technologies, such as prompting the driver to change driving modes, this invention chooses to maintain and optimize energy-saving effects by making small, automated adjustments to energy-saving execution preference parameters within the system, thereby avoiding additional interference to the driver.

[0099] In step S501, samples matching the current driver's operating characteristic pattern are selected from a pool of samples, and the longitudinal following control strength parameter corresponding to the sample is identified. When no sample in the historical driving database is completely consistent with the current driver's operating characteristic pattern, the sample that is closest in the operating characteristic pattern parameter space can be selected as the matching sample. This matching method can be implemented based on existing driving behavior similarity assessment methods, which are mature and feasible technical means in the prior art. Subsequently, it is determined whether the longitudinal following control strength parameter exceeds the determined longitudinal following control strength parameter threshold.

[0100] In step S502, when it is determined that the longitudinal following control intensity parameter exceeds the longitudinal following control intensity parameter threshold, a preference correction factor is generated based on the deviation difference between the two. The basis for using this deviation difference as the correction factor is that the degree to which the longitudinal following control intensity parameter exceeds the threshold directly reflects the additional intervention intensity caused to the vehicle system's adaptive energy-saving capability after the driver's operating characteristic mode and the safe following control strategy are coupled. The larger the deviation difference, the weaker the vehicle system's adaptive repair capability to this intervention under the existing energy-saving execution preference parameters; therefore, a more significant correction needs to be applied to the energy-saving execution preference parameters. By using the deviation difference as the correction factor, the energy-saving execution preference parameters can be adaptively changed with the intervention intensity, rather than using a fixed amplitude or abrupt adjustment, thereby ensuring the smoothness and controllability of the system adjustment process.

[0101] In step S503, the energy-saving execution preference parameters are corrected according to the preference correction factor to obtain optimized energy-saving execution preference parameters, and the vehicle uses the optimized energy-saving execution preference parameters for energy-saving control when entering the target road segment. This correction process is constrained by the maximum possible value of the energy-saving execution preference parameters to avoid affecting the overall operating characteristics of the vehicle due to over-correction.

[0102] In this embodiment of the invention, the calculation method used to correct the energy-saving execution preference parameter is intuitive and effective. Its basic idea is to use the original energy-saving execution preference parameter as a base, and then proportionally amplify the preference parameter based on the excess ratio of the longitudinal following control intensity parameter relative to the threshold, while imposing an upper limit on the result. This method does not rely on complex models, has a simple calculation process, and is easy to implement in vehicle systems or cloud platforms. It also reflects the impact of changes in control intensity on energy-saving demand. Besides the above method, piecewise linear methods, exponentially increasing methods, or table-based methods can also be used to correct the energy-saving execution preference parameter; this invention does not limit the specific method used.

[0103] The following example illustrates the overall implementation process of this invention. Assume a target road segment is an 800-meter-long low-speed uphill following section, and the vehicle's current energy-saving execution preference parameter is set to 5, indicating a bias towards energy saving but not reaching the maximum energy-saving level. Through historical sample analysis, the threshold for the longitudinal following control intensity parameter corresponding to this road segment is determined to be 100. Under the current driver operation characteristic mode, the matched longitudinal following control intensity parameter is 120, exceeding the threshold by 20. Dividing the excess 20 by the threshold 100 yields a deviation ratio of 0.2. The system's preset control correction intensity coefficient is 0.5, resulting in a final correction magnitude of 0.1. Based on this correction magnitude, the original energy-saving execution preference parameter 5 is corrected, resulting in a corrected energy-saving execution preference parameter of 5.5. As long as this correction result does not exceed the maximum possible value of the energy-saving execution preference parameter, the vehicle, upon entering the target road segment, adopts this corrected energy-saving execution preference parameter for energy-saving control, thereby increasing the energy recovery ratio and reducing energy consumption per unit travel distance.

[0104] As can be seen from the above implementation process, the present invention effectively improves the energy recovery effect in low-speed slope following vehicle scenarios by using a small and continuous parameter correction method without significantly affecting driving comfort.

[0105] In summary, this invention addresses the coupling intervention problem between driver operation characteristics and safe following control strategies in low-speed slope following scenarios by introducing longitudinal following control strength parameters, energy-saving effect consistency parameters, and their threshold recognition mechanisms. It achieves adaptive correction of energy-saving execution preference parameters, effectively addressing the core research point raised in step S100: the potential inadequacy of adaptive capabilities in existing vehicle-mounted energy control systems in such scenarios. Without altering existing safe following control strategies or frequently prompting drivers to change driving behavior, this invention, through minor adjustments to energy-saving execution preference parameters, enables vehicles to maintain good energy-saving performance during low-speed slope following, while having minimal impact on vehicle longitudinal response and driving comfort, and minimal changes in driver subjective perception. It boasts advantages such as low implementation cost, user-friendly experience, and stable energy-saving effects, making it suitable for typical new energy vehicle application scenarios such as urban commuting and high-frequency fixed-route driving, and has promising application prospects.

[0106] Furthermore, Figure 4 An application architecture diagram of the system provided in an embodiment of the present invention is shown.

[0107] In another preferred embodiment of the present invention, a collaborative control system for a new energy vehicle power system includes:

[0108] The road condition identification module 100 is used to obtain the current following composite condition intensity of the target road segment when it is determined that the target road segment to be driven by the vehicle is a low-speed slope following scenario, and to retrieve the historical driving database of the target road segment.

[0109] The current vehicle-following composite condition intensity is predicted and evaluated based on the road slope information, traffic flow information, and current vehicle operating status information of the target road segment; the corresponding vehicle-following composite condition intensity in the sample is evaluated based on the historical operating data of vehicle speed changes, start-stop behavior, and following status collected during the actual driving process of the vehicle on the target road segment.

[0110] Furthermore, the new energy vehicle power system collaborative control system also includes:

[0111] The sample screening module 200 is used to screen several samples from the database. The samples have the same energy-saving execution preference parameters and vehicle-following composite working condition intensity as the current samples, but the driver operation characteristic mode before entering the target road section is different from the current samples.

[0112] Furthermore, the new energy vehicle power system collaborative control system also includes:

[0113] The parameter acquisition module 300 is used to acquire the longitudinal following control intensity parameters of each sample during the driving process on the target road segment, as well as the energy-saving effect consistency parameters obtained from the post-driving evaluation.

[0114] Furthermore, the new energy vehicle power system collaborative control system also includes:

[0115] The threshold determination module 400 is used to establish the correspondence between the longitudinal following control intensity parameters and the energy-saving effect consistency parameters of several samples, and to determine the threshold of the longitudinal following control intensity parameters that causes the energy-saving effect consistency parameters to change from a stable state to a deteriorated state.

[0116] Furthermore, the new energy vehicle power system collaborative control system also includes:

[0117] The preference correction module 500 is used to determine the longitudinal following control intensity parameter corresponding to the current driver operation characteristic mode according to the correspondence, and to determine whether it exceeds the longitudinal following control intensity parameter threshold. If it does, a preference correction factor is generated based on the difference between the longitudinal following control intensity parameter and the longitudinal following control intensity parameter threshold, and the energy-saving execution preference parameter is corrected based on the preference correction factor.

[0118] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0119] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0120] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0121] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0122] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for coordinated control of a new energy vehicle power system, characterized in that, The method includes: When it is determined that the target road segment where the vehicle is about to travel is a low-speed slope following scenario, the current following composite working condition intensity corresponding to the target road segment is obtained, and the historical driving database of the target road segment is retrieved. Several samples were selected from the database. The samples had the same energy-saving execution preference parameters and the intensity of the vehicle-following composite working condition as the current samples, but the driver operation characteristics before entering the target road section were different from the current samples. The longitudinal following control intensity parameters of each sample during the driving process on the target road segment were obtained, as well as the consistency parameters of energy-saving effect obtained from the post-driving evaluation. Establish the correspondence between longitudinal following control intensity parameters and energy-saving effect consistency parameters for several samples, and determine the threshold of longitudinal following control intensity parameters that causes the energy-saving effect consistency parameters to change from a stable state to a deteriorated state. Based on the correspondence, the longitudinal following control strength parameter corresponding to the current driver operation characteristic mode is determined, and it is determined whether it exceeds the longitudinal following control strength parameter threshold. If it does, a preference correction factor is generated based on the difference between the longitudinal following control strength parameter and the longitudinal following control strength parameter threshold, and the energy-saving execution preference parameter is corrected based on the preference correction factor.

2. The collaborative control method for a new energy vehicle power system according to claim 1, characterized in that, The current vehicle-following composite working condition intensity is obtained by predicting and evaluating based on the road slope information, traffic flow information and vehicle current operating status information of the target road section. The intensity of the following vehicle composite working condition corresponding to the sample is obtained by evaluating historical operating data of vehicle speed changes, start-stop behavior and following vehicle status collected during the actual driving of the vehicle on the target road section.

3. The collaborative control method for a new energy vehicle power system according to claim 1, characterized in that, The driver operation feature pattern is a parameter used to characterize the operation feature pattern formed by the driver actively controlling the vehicle during the driving process before entering the target road segment. The operation feature pattern parameter is determined based on the change characteristics of the driver control input signal collected by the vehicle.

4. The collaborative control method for a new energy vehicle power system according to claim 1, characterized in that, The difference in longitudinal following control intensity parameters among different samples stems from the fact that, under the premise that the vehicle's infotainment system issues the same following control strategy based on the same following composite working condition intensity, the longitudinal control-related parameters collected by the vehicle during the target road segment are different due to the different driver operation characteristics. The longitudinal control-related parameters include at least one of longitudinal acceleration / deceleration variation characteristics, driving torque variation characteristics, and braking control variation characteristics; the longitudinal following control strength parameters are determined by comprehensively characterizing the collected longitudinal control-related parameters.

5. The collaborative control method for a new energy vehicle power system according to claim 4, characterized in that, The process of determining the consistency parameters of the energy-saving effect includes: after the vehicle completes the driving of the target road segment, obtaining the actual energy-saving effect parameters within the target road segment, wherein the actual energy-saving effect parameters include at least the energy consumption parameters per unit driving distance and the regenerative braking energy recovery parameters; A preset energy-saving effect reference benchmark is retrieved, and based on the energy-saving effect reference benchmark, the expected energy-saving effect parameters are obtained under the condition that the corresponding longitudinal control parameters are adopted and the driver's operation characteristic mode intervention is allowed. The energy-saving effect consistency parameter is determined according to the deviation of the actual energy-saving effect parameters from the expected energy-saving effect parameters.

6. The collaborative control method for a new energy vehicle power system according to claim 5, characterized in that, The steps for establishing the correspondence between longitudinal following control intensity parameters and energy-saving effect consistency parameters for several samples, and determining the threshold of the longitudinal following control intensity parameter that causes the energy-saving effect consistency parameter to change from a stable state to a deteriorated state, include: Several samples are analyzed and arranged in order of magnitude of the longitudinal following control intensity parameters corresponding to each sample to form a sample sequence; Based on the sample sequence, the variation characteristics of the corresponding energy-saving effect consistency parameter with the longitudinal following control intensity parameter are obtained. Determine whether there is a turning point in the changing features that causes the energy-saving effect consistency parameter to exceed the preset allowable range and continue to be maintained in subsequent samples. If so, determine the longitudinal following control strength parameter corresponding to the turning point as the longitudinal following control strength parameter threshold that causes the energy-saving effect consistency parameter to change from a stable state to a deteriorated state.

7. The collaborative control method for a new energy vehicle power system according to claim 6, characterized in that, Based on the correspondence, the longitudinal following control strength parameter corresponding to the current driver operation characteristic mode is determined, and it is determined whether it exceeds the longitudinal following control strength parameter threshold. If it does, a preference correction factor is generated based on the difference between the longitudinal following control strength parameter and the longitudinal following control parameter threshold. The steps of correcting the energy-saving execution preference parameter based on the preference correction factor include: From a number of samples, samples that match the current driver operation pattern of the vehicle are selected, the longitudinal following control strength parameter corresponding to the sample is identified, and it is determined whether the longitudinal following control strength parameter exceeds the threshold of the longitudinal following control strength parameter. If the determination is yes, then a preference correction factor is generated based on the difference between the identified longitudinal following control strength parameter and the threshold value of the longitudinal following control strength parameter; The energy-saving execution preference parameters are corrected based on the preference correction factor to obtain optimized energy-saving execution preference parameters, and the vehicle uses the optimized energy-saving execution preference parameters for energy-saving control when entering the target road segment.

8. The collaborative control method for a new energy vehicle power system according to claim 7, characterized in that, In the process of correcting the energy-saving performance preference parameters, a preset correction formula is used, which is: ； in, This refers to the revised energy-saving execution preference parameters. This refers to the uncorrected energy-saving performance preference parameter. This refers to the maximum possible value of the energy-saving execution preference parameter. This refers to the identified longitudinal following control strength parameters. This refers to the threshold value of the longitudinal following control strength parameter. This refers to the preference correction factor. This refers to the preset control correction strength coefficient, and it satisfies... .

9. A collaborative control system for a new energy vehicle power system, characterized in that, The system includes: The road condition identification module is used to obtain the current following composite condition intensity of the target road segment when it is determined that the target road segment to be driven by the vehicle is a low-speed slope following scenario, and to retrieve the historical driving database of the target road segment. The sample screening module is used to screen several samples from the database. The samples have the same energy-saving execution preference parameters and vehicle-following composite working condition intensity as the current samples, but the driver operation characteristic patterns before entering the target road segment are different from the current samples. The parameter acquisition module is used to acquire the longitudinal following control intensity parameters of each sample during the driving process on the target road segment, as well as the energy-saving effect consistency parameters obtained from the post-driving evaluation. The threshold determination module is used to establish the correspondence between the longitudinal following control intensity parameters and the energy-saving effect consistency parameters of several samples, and to determine the threshold of the longitudinal following control intensity parameters that causes the energy-saving effect consistency parameters to change from a stable state to a deteriorated state. The preference correction module is used to determine the longitudinal following control strength parameter corresponding to the current driver operation characteristic mode according to the correspondence, and to determine whether it exceeds the longitudinal following control strength parameter threshold. If it does, a preference correction factor is generated based on the difference between the longitudinal following control strength parameter and the longitudinal following control strength parameter threshold, and the energy-saving execution preference parameter is corrected according to the preference correction factor.

10. The new energy vehicle power system coordinated control system according to claim 9, characterized in that, The current vehicle-following composite condition intensity is predicted and evaluated based on the road slope information, traffic flow information, and current vehicle operating status information of the target road segment; the corresponding vehicle-following composite condition intensity in the sample is evaluated based on the historical operating data of vehicle speed changes, start-stop behavior, and following status collected during the actual driving process of the vehicle on the target road segment.

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