A new energy vehicle infotainment system and energy feedback control method

Abstract

This application provides a vehicle infotainment system and energy recovery control method for a new energy vehicle. When the battery charge level of a hybrid vehicle is lower than its energy recovery threshold, the method determines the cumulative energy recovery time of the battery. Based on this cumulative recovery time and the vehicle's battery information, a battery state constraint for the energy recovery intensity is determined. A vehicle speed constraint for the energy recovery intensity after entering a curve is also determined. The energy recovery intensity in the curve is then balanced and arbitrated using the battery state constraint and the vehicle speed constraint. The balanced energy recovery intensity is then sent to the vehicle infotainment system for energy recovery operation. Based on this solution, a visual interaction between driving intention and energy recovery strategy during curve driving in a hybrid vehicle can be achieved.

Description

Technical Field

[0001] This application relates to the field of hybrid vehicle technology, and more specifically, to a new energy vehicle infotainment system and energy feedback control method. Background Technology

[0002] Hybrid vehicles are cars that combine a gasoline engine and an electric motor as power sources, possessing the range advantage of gasoline vehicles and the environmentally friendly and energy-saving characteristics of electric vehicles. During start-up and low-speed driving, the electric motor primarily drives the vehicle, resulting in quiet operation and low energy consumption. When high-speed driving is required or the battery is low, the gasoline engine intervenes to provide power to the vehicle or charge the battery.

[0003] Existing hybrid vehicle infotainment systems suffer from significant human-machine interface deficiencies in visualizing energy recovery. When energy recovery braking is activated, the system neither clearly displays the current recovery intensity on the dashboard nor provides predictions of impending braking force changes. This makes it difficult for drivers to accurately assess the situation. In complex conditions such as cornering, the lack of visual guidance on energy recovery behavior often leads drivers to misinterpret a sudden increase in recovery intensity as a braking system malfunction. This can result in instinctively applying the brakes or abruptly releasing the accelerator, causing conflicts between driver and vehicle actions such as overlapping or interruption of braking force. This not only affects driving comfort but may also endanger driving safety and reduce energy recovery efficiency. Therefore, achieving visualized interaction between driving intentions and energy recovery strategies during cornering in hybrid vehicles, thereby improving the human-machine co-driving experience, has become a challenging issue for the industry. Summary of the Invention

[0004] This application provides a vehicle infotainment system and energy feedback control method for new energy vehicles, which can realize the visual interaction between driving intention and energy recovery strategy during curve driving of hybrid vehicles.

[0005] In a first aspect, this application provides an energy feedback control method for a new energy vehicle infotainment system, including:

[0006] After the energy management display mode is activated in the vehicle system of the hybrid vehicle, the driving status information of the hybrid vehicle is monitored, and then the battery information and vehicle motion parameters of the hybrid vehicle are extracted from the driving status information.

[0007] When the battery charge value in the battery information is lower than the feedback threshold of the hybrid vehicle, the cumulative feedback time of the battery energy in the hybrid vehicle is determined. The battery state constraint of the battery energy feedback intensity in the hybrid vehicle is determined by combining the cumulative feedback time with the battery temperature, state of charge and health status in the battery information.

[0008] The safe entry speed of the hybrid vehicle is calculated based on the curve radius in the vehicle motion parameters and road information. During the vehicle braking process before entering the curve, the energy feedback intensity is gradually increased based on the entry distance of the hybrid vehicle until the current speed of the hybrid vehicle is less than the safe entry speed. Then, the vehicle speed constraint of the battery energy feedback intensity of the hybrid vehicle after entering the curve is determined.

[0009] The battery energy feedback intensity of the hybrid vehicle in a curve is balanced and arbitrated by the battery state constraint and vehicle speed constraint of the battery energy feedback intensity, and the balanced and arbitrated energy feedback intensity is sent to the hybrid vehicle's vehicle system for energy recovery operation.

[0010] In some embodiments, extracting the battery information and vehicle motion parameters of the hybrid vehicle from the driving status information specifically includes:

[0011] The battery temperature, state of charge, health status, current vehicle speed, acceleration, and brake pedal opening are obtained from the driving status information.

[0012] Battery information for hybrid vehicles is determined by battery temperature, state of charge, and state of health.

[0013] The vehicle motion parameters of the hybrid vehicle are determined by the current vehicle speed, acceleration, and brake pedal opening.

[0014] In some embodiments, determining the cumulative energy return time of the battery in a hybrid vehicle specifically includes:

[0015] When the energy feedback mode is activated, a timer is started to record the current feedback time, thus obtaining the duration of each energy feedback cycle.

[0016] The cumulative energy return time of the battery in the hybrid vehicle is determined by all durations.

[0017] In some embodiments, the battery state constraint for determining the battery energy feedback intensity in a hybrid vehicle by combining the cumulative feedback time with the battery temperature, state of charge, and health status in the battery information specifically includes:

[0018] The basic constraint coefficients for determining the battery energy feedback intensity are determined based on the battery temperature, state of charge, and state of health information in the battery information.

[0019] Determine the attenuation factor of the cumulative feedback time on the battery energy feedback intensity;

[0020] The battery state constraints for determining the battery energy feedback intensity in hybrid vehicles are determined by the attenuation factor and the basic constraint coefficient.

[0021] In some embodiments, calculating the safe entry speed of the hybrid vehicle into a curve based on the vehicle motion parameters and the curve radius in the road information specifically includes:

[0022] Obtain the road surface adhesion coefficient and the curve radius from the road information of the road where the hybrid vehicle is traveling;

[0023] The maximum entry speed of the hybrid vehicle into a curve is determined based on the road surface adhesion coefficient and the curve radius.

[0024] The safety margin of the hybrid vehicle is set by the aforementioned vehicle motion parameters;

[0025] The safe cornering speed of the hybrid vehicle is determined based on the safety margin and the maximum cornering speed.

[0026] In some embodiments, gradually increasing the energy feedback intensity based on the hybrid vehicle's entry distance during vehicle braking before entering a curve specifically includes:

[0027] Obtain the entry distance of the hybrid vehicle into the curve, and obtain the current vehicle speed from the vehicle motion parameters;

[0028] The deceleration curve of the hybrid vehicle before entering the curve is determined by the entry distance, the current vehicle speed, and the safe entry speed.

[0029] Under the premise of ensuring the coordination of the braking system, the gradient for increasing the energy feedback intensity is determined based on the deceleration curve before entering the curve, and then the gradient is used to gradually increase the energy feedback intensity of the hybrid vehicle before entering the curve.

[0030] In some embodiments, balancing and arbitrating the battery energy feedback intensity of a hybrid vehicle in a curve through battery state constraints and vehicle speed constraints specifically includes:

[0031] The balance value of the battery energy feedback intensity is determined by the battery state constraint and the vehicle speed constraint of the battery energy feedback intensity.

[0032] The aforementioned balance value is used to perform power balancing on the battery energy feedback intensity of the hybrid vehicle in a curve, thereby obtaining the balance arbitration value of the battery energy feedback intensity of the hybrid vehicle in a curve.

[0033] In some embodiments, the hybrid vehicle is a hybrid electric vehicle that integrates a fuel engine and an electric motor.

[0034] In some embodiments, the vehicle infotainment system is an intelligent interactive display and control system based on multi-source data fusion.

[0035] Secondly, this application provides a new energy vehicle infotainment system, including a feedback control unit, wherein the feedback control unit includes:

[0036] The monitoring module is used to monitor the driving status information of the hybrid vehicle after the energy management display mode is activated in the vehicle system of the hybrid vehicle, and then extract the battery information and vehicle motion parameters of the hybrid vehicle from the driving status information.

[0037] The processing module is used to determine the cumulative feedback time of battery energy in the hybrid vehicle when the battery charge value in the battery information is lower than the feedback threshold of the hybrid vehicle, and to determine the battery state constraint of the battery energy feedback intensity in the hybrid vehicle by combining the cumulative feedback time with the battery temperature, state of charge and health status in the battery information.

[0038] The processing module is also used to calculate the safe entry speed of the hybrid vehicle into a curve based on the vehicle motion parameters and the curve radius in the road information. During the vehicle braking process before entering the curve, the energy feedback intensity is gradually increased based on the entry distance of the hybrid vehicle into the curve until the current speed of the hybrid vehicle is less than the safe entry speed into the curve, thereby determining the vehicle speed constraint of the battery energy feedback intensity of the hybrid vehicle after the current entry into the curve.

[0039] The execution module is used to balance and arbitrate the battery energy feedback intensity of the hybrid vehicle in the curve by means of battery state constraints and vehicle speed constraints of the battery energy feedback intensity, and send the balanced and arbitrated energy feedback intensity to the hybrid vehicle's vehicle system for energy recovery operation.

[0040] The technical solutions provided by the embodiments disclosed in this application have the following beneficial effects:

[0041] In the new energy vehicle infotainment system and energy feedback control method provided in this application, after the energy management display mode of the hybrid vehicle's infotainment system is activated, the driving status information of the hybrid vehicle is monitored, and then the battery information and vehicle motion parameters of the hybrid vehicle are extracted from the driving status information. When the charge value in the battery information is lower than the feedback threshold of the hybrid vehicle, the cumulative feedback time of the battery energy in the hybrid vehicle is determined. The battery state constraint of the battery energy feedback intensity in the hybrid vehicle is determined by combining the cumulative feedback time with the battery temperature, state of charge and health status in the battery information. The safe entry speed of the hybrid vehicle into the curve is calculated based on the vehicle motion parameters and the curve radius in the road information. During the vehicle braking process before entering the curve, the energy feedback intensity is gradually increased based on the entry distance of the hybrid vehicle into the curve until the current speed of the hybrid vehicle is less than the safe entry speed, and then the vehicle speed constraint of the battery energy feedback intensity of the hybrid vehicle after entering the curve is determined. The battery state constraint of the battery energy feedback intensity and the vehicle speed constraint are used to balance and arbitrate the battery energy feedback intensity of the hybrid vehicle in the curve, and the balanced and arbitrated energy feedback intensity is sent to the hybrid vehicle infotainment system for energy recovery operation.

[0042] Therefore, in this application, the battery energy feedback intensity of the hybrid vehicle in a curve is balanced and arbitrated through battery state constraints and vehicle speed constraints. The balanced and arbitrated energy feedback intensity is then sent to the hybrid vehicle's infotainment system for energy recovery operation. First, determining the battery state constraints yields the real-time load-bearing capacity parameters of the battery system, providing crucial foundational data support for the visualization and interaction of the energy recovery system. Determining the battery state constraints allows the infotainment system to clearly display the battery's real-time operating status and remaining recovery potential in the visualization interface. For example, the battery's load-bearing capacity can be intuitively presented through color gradients or percentage progress bars. When the driver observes that high-power recovery may cause the battery to overheat or overcharge, they can adjust their driving style in advance to avoid the abruptness caused by the system forcibly reducing the recovery intensity. At the same time, the recovery intensity suggestions given by the infotainment system based on the battery state constraints help the driver understand the operating boundaries of the energy recovery system and make more appropriate operational decisions when braking in a curve, achieving a harmonious unity between human and machine operation. Then, determining the vehicle speed constraints yields the optimal braking strategy parameters under curve conditions, thus providing visualization synchronization between driving intentions and system behavior. By creating the necessary conditions and determining vehicle speed constraints, the vehicle's infotainment system can overlay and display the expected deceleration trajectory and energy recovery intensity trends on the navigation interface. For example, it can visually demonstrate the recommended recovery intensity for different sections using dynamic arrows or gradient color bands. When the driver observes the braking pattern predicted by the system, they can adjust the pedal pressure in advance or choose a more suitable entry line to avoid emergency braking or excessive deceleration. At the same time, speed constraints based on vehicle dynamics calculations ensure that the visual prompts are highly consistent with the vehicle's actual braking performance, eliminating the common problem of discrepancies between displayed information and actual operating conditions in traditional systems, and significantly improving the driver's accuracy in predicting system behavior. In summary, based on the above scheme, a visual interaction between driving intentions and energy recovery strategies can be achieved in hybrid vehicles during cornering. Attached Figure Description

[0043] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0044] Figure 1 This is an exemplary flowchart of an energy feedback control method for a new energy vehicle infotainment system according to some embodiments of this application;

[0045] Figure 2 This is a schematic diagram of the process for implementing balanced arbitration according to some embodiments of this application;

[0046] Figure 3 This is a schematic diagram of the structure of the feedback control unit according to some embodiments of this application;

[0047] Figure 4 This is a schematic diagram of the structure of a computer device for implementing an energy feedback control method for a new energy vehicle infotainment system, according to some embodiments of this application. Detailed Implementation

[0048] To better understand the technical solution of this application, the technical solution of this application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0049] refer to Figure 1 The figure is an exemplary flowchart of an energy feedback control method for a new energy vehicle infotainment system according to some embodiments of this application. The energy feedback control method for the new energy vehicle infotainment system mainly includes the following steps:

[0050] In step 101, after the energy management display mode is activated in the vehicle system of the hybrid vehicle, the driving status information of the hybrid vehicle is monitored, and then the battery information and vehicle motion parameters of the hybrid vehicle are extracted from the driving status information.

[0051] In practical implementation, temperature data is collected in real time through a network of temperature sensors distributed throughout the battery module. The overall temperature of the battery pack is calculated using the arithmetic mean method as the battery temperature. A composite estimation method combining the ampere-hour integration method and the open-circuit voltage method is used. First, real-time charging and discharging current is collected through current sensors, and the relative charge is obtained through integration. Then, the battery is calibrated based on the terminal voltage when the battery is at rest to obtain the battery's state of charge. By recording the historical number of charge and discharge cycles, depth, and temperature stress, combined with the capacity decay curve obtained from offline detection, a weighted algorithm based on an empirical model is used to calculate the battery's health status. The weighted calculation result is then used as the battery's health status. The speed sensor collects the rotational speed signals of the four wheels. After the ESP system removes slippage interference, the average effective wheel speed is taken and converted into the vehicle speed as the current vehicle speed. The MEMS acceleration sensor directly measures the longitudinal acceleration, and the data is fused with the synchronous reference motor torque change rate and braking pressure signal to obtain the vehicle acceleration. The angle sensor or stroke sensor installed at the brake pedal shaft converts the mechanical displacement into an electrical signal as the vehicle's brake pedal opening. Thus, the combination of battery temperature, state of charge, health status, current vehicle speed, acceleration, and brake pedal opening is used as the driving status information of the hybrid vehicle.

[0052] It should be noted that, in this application, the hybrid vehicle is a hybrid electric vehicle that integrates a fuel engine and an electric motor; the vehicle system is an intelligent interactive display control system based on multi-source data fusion; battery temperature refers to the average temperature value of the power battery pack under the current operating environment, which can reflect the thermal state of the battery system; state of charge characterizes the percentage of the battery's current remaining usable charge relative to its total capacity; health status reflects the degree of decay of the battery's current actual capacity relative to its initial capacity, which can affect the power boundary of energy recovery; the vehicle's current speed is the instantaneous speed of the vehicle; the vehicle's acceleration refers to the rate of change of the vehicle's velocity in the direction of travel, which can be used to determine driving intentions; and the vehicle's brake pedal opening represents the proportion of the driver's brake pedal travel, which can reflect the intensity of braking demand.

[0053] In some embodiments, extracting the battery information and vehicle motion parameters of the hybrid vehicle from the driving status information can be achieved by the following steps:

[0054] The battery temperature, state of charge, health status, current vehicle speed, acceleration, and brake pedal opening are obtained from the driving status information.

[0055] Battery information for hybrid vehicles is determined by battery temperature, state of charge, and state of health.

[0056] The vehicle motion parameters of the hybrid vehicle are determined by the current vehicle speed, acceleration, and brake pedal opening.

[0057] It should be noted that, in this application, vehicle motion parameters are a set of kinematic parameters reflecting the real-time operating state of the vehicle; battery information is a set of key parameters reflecting the real-time state of the hybrid vehicle's power battery system. Specifically, firstly, the battery temperature, state of charge, health status, current vehicle speed, acceleration, and brake pedal opening are obtained from the driving state information. Then, determining the hybrid vehicle's battery information using the battery temperature, state of charge, and health status can be achieved by using the set of battery temperature, state of charge, and health status as the hybrid vehicle's battery information. Finally, the set of current vehicle speed, acceleration, and brake pedal opening is used as the hybrid vehicle's vehicle motion parameters.

[0058] In step 102, when the battery charge value in the battery information is lower than the feedback threshold of the hybrid vehicle, the cumulative feedback time of the battery energy in the hybrid vehicle is determined, and the battery state constraint of the battery energy feedback intensity in the hybrid vehicle is determined by combining the cumulative feedback time with the battery temperature, state of charge and health status in the battery information.

[0059] It should be noted that, in this application, the feedback threshold refers to the state of charge (SOC) threshold set in the hybrid vehicle battery management system that allows for dynamic adjustment of energy recovery intensity. The setting of the feedback threshold needs to comprehensively consider multiple parameters such as battery health, temperature conditions, and cycle life, and is determined using a dynamic adaptive algorithm. The base threshold is typically set in the 65% SOC range (for lithium iron phosphate batteries) or 55% (for ternary lithium batteries), and is increased by 4% for every 5% decrease in battery health. When the battery temperature exceeds 45°C, temperature compensation is activated, and the threshold is decreased by 9% for every 5°C increase. Simultaneously, a historical cycle count weighting factor is introduced, increasing the threshold by 2% for every additional 500 cycles. This threshold is dynamically adjusted in 0.5% increments through collaborative calculation between the vehicle battery management system and the vehicle controller to ensure maximum recovery efficiency while protecting the battery.

[0060] In some embodiments, determining the cumulative energy recovery time of the battery in a hybrid vehicle can be achieved using the following steps:

[0061] When the energy feedback mode is activated, a timer is started to record the current feedback time, thus obtaining the duration of each energy feedback cycle.

[0062] The cumulative energy return time of the battery in the hybrid vehicle is determined by all durations.

[0063] It should be noted that, in this application, the cumulative feedback time refers to the sum of the durations of all energy recovery of the hybrid vehicle battery within a specified working cycle. In specific implementation, firstly, when the energy recovery mode is activated, a timer is started to record the current feedback time. The duration of each energy recovery can be obtained in the following way: when the energy recovery function activation signal is triggered, the 32-bit high-precision timer built into the vehicle system starts timing. The timer clock source uses an independent crystal oscillator with a time resolution of 1 millisecond. During the energy recovery process, the timer runs continuously and records the cumulative time value. When the vehicle system detects the energy recovery exit condition (e.g., the battery is fully charged, the driver presses the accelerator, or a malfunction occurs), the timer immediately pauses and stores the current duration in non-volatile memory. Thus, the cumulative time value in each energy recovery is used as the duration of the energy recovery, and the duration of each energy recovery can be obtained. This feedback time refers to the duration of a single energy recovery process, which is the time interval from the moment the energy recovery mode is activated to the moment it exits the mode. This parameter reflects the continuity of energy recovery operations and is used to assess the battery's continuous workload. The cumulative energy recovery time of the battery in the hybrid vehicle can be determined by summing all durations. Specifically, the vehicle system maintains an independent accumulation register, automatically adding this value after each recovery time recording. The accumulated value is automatically backed up to a protected storage area every hour to prevent accidental loss. An automatic reset mechanism is also set up; when the battery is detected as fully charged or the vehicle has been off for more than a set time (default 1 hour), the accumulated value is automatically reset, and the value accumulated in the register is used as the cumulative energy recovery time of the battery in the hybrid vehicle.

[0064] In some embodiments, the battery state constraint for determining the battery energy feedback intensity in a hybrid vehicle by combining the cumulative feedback time with the battery temperature, state of charge, and health status in the battery information can be implemented using the following steps:

[0065] The basic constraint coefficients for determining the battery energy feedback intensity are determined based on the battery temperature, state of charge, and state of health information in the battery information.

[0066] Determine the attenuation factor of the cumulative feedback time on the battery energy feedback intensity;

[0067] The battery state constraints for determining the battery energy feedback intensity in hybrid vehicles are determined by the attenuation factor and the basic constraint coefficient.

[0068] It should be noted that, in this application, the battery state constraint refers to the maximum allowable feedback intensity threshold of the battery system, which directly limits the upper limit of the motor's feedback power; the basic constraint coefficient is a proportional coefficient reflecting the theoretical maximum feedback capability of the battery under the current temperature, state of charge, and health conditions, and the value of the basic constraint coefficient ranges from 0 to 1. This basic constraint coefficient can characterize the basic limitation of the battery's own characteristics on the energy recovery intensity; the attenuation factor represents the degree of influence of the cumulative feedback time on the attenuation of the battery's feedback capability, and the value of the attenuation factor ranges from 0 to 1. This attenuation factor reflects the performance degradation characteristics of the battery under continuous working conditions.

[0069] In specific implementation, firstly, the basic constraint coefficients for determining the battery energy feedback intensity based on the battery temperature, state of charge, and health status in the battery information can be achieved in the following way: A three-dimensional lookup table is built into the hybrid vehicle's infotainment system. Using battery temperature, state of charge, and health status as input indices, the real-time collected battery temperature is mapped to standardized temperature ranges (e.g., every 5°C). The state of charge is graded at 5% intervals, and the health status is graded at 10% intervals. The basic coefficient value corresponding to the current state is calculated using a cubic spline interpolation algorithm as the basic constraint coefficient for the battery energy feedback intensity. Then, the cumulative feedback time is determined as the effect on the battery energy feedback intensity. The attenuation factor can be implemented as follows: Initialize an exponential attenuation model, obtain the battery attenuation rate from the battery manual of the hybrid vehicle as the basic attenuation rate parameter in the exponential attenuation model, and monitor the cumulative feedback time in real time. For every second increase, recalculate the attenuation factor using the exponential attenuation model to obtain the attenuation factor of the cumulative feedback time on the battery energy feedback intensity. Finally, the battery state constraint of the battery energy feedback intensity in the hybrid vehicle can be determined by the attenuation factor and the basic constraint coefficient as follows: The product of the basic constraint coefficient and the attenuation factor is used as the battery state constraint of the battery energy feedback intensity in the hybrid vehicle.

[0070] In step 103, the safe entry speed of the hybrid vehicle is calculated based on the vehicle motion parameters and the curve radius in the road information. During the vehicle braking process before entering the curve, the energy feedback intensity is gradually increased based on the entry distance of the hybrid vehicle until the current speed of the hybrid vehicle is less than the safe entry speed, thereby determining the vehicle speed constraint of the battery energy feedback intensity of the hybrid vehicle after the current entry into the curve.

[0071] In some embodiments, calculating the safe entry speed of a hybrid vehicle into a curve based on the vehicle motion parameters and the curve radius in the road information can be achieved using the following steps:

[0072] Obtain the road surface adhesion coefficient and the curve radius from the road information of the road where the hybrid vehicle is traveling;

[0073] The maximum entry speed of the hybrid vehicle into a curve is determined based on the road surface adhesion coefficient and the curve radius.

[0074] The safety margin of the hybrid vehicle is set by the aforementioned vehicle motion parameters;

[0075] The safe cornering speed of the hybrid vehicle is determined based on the safety margin and the maximum cornering speed.

[0076] It should be noted that in this application, the safe entry speed is the actual control value after the maximum entry speed is corrected for the safety margin; the road surface adhesion coefficient is a dimensionless parameter reflecting the maximum static friction capability between the tire and the road surface; the curve radius represents the radius of curvature of the curve on which the vehicle's trajectory is located, and the smaller the value, the sharper the curve; the maximum entry speed refers to the theoretical limit speed at which the vehicle can safely pass through the curve under ideal conditions; and the safety margin is a buffer coefficient set to ensure driving safety.

[0077] In specific implementation, firstly, obtaining the road surface adhesion coefficient and the curve radius in the road information of the hybrid vehicle's driving road can be achieved in the following way: Establish a road surface feature database, automatically match the adhesion coefficient benchmark value of typical road surfaces based on GPS positioning, and then fine-tune it in real time using tire force sensors. The fine-tuned adhesion coefficient benchmark value is used as the road surface adhesion coefficient of the hybrid vehicle's driving road. Secondly, obtain the curve geometry parameters in advance using high-precision map data, and perform real-time verification in conjunction with the lane curvature identified by the forward-looking camera. The real-time verified curve geometry parameters are used as the curve radius in the road information. Thirdly, determining the maximum entry speed of the hybrid vehicle based on the road surface adhesion coefficient and the curve radius can be achieved in the following way: Take the square root of the product of the road surface adhesion coefficient, the curve radius, and the gravitational acceleration (default 9.8 m / s²) as the maximum entry speed of the hybrid vehicle. This process is based on the principle of centripetal force balance in circular motion, indicating that when the vehicle is driving in a curve, the centrifugal force (the balance equation of circular motion) is generated by the tire and the... The maximum static friction force balance of the road surface is determined by solving the equilibrium equation of circular motion, from which the mathematical expression for the maximum cornering speed is derived. Then, the safety margin of the hybrid vehicle can be set using the vehicle motion parameters in the following way: the safety margin is directly obtained from the vehicle's infotainment system. In other embodiments, the vehicle can dynamically adjust this safety margin, automatically reducing it when sharp turns, load changes, or tire wear are detected. The infotainment system maintains multi-level safety strategies, using a higher safety margin (default 0.85) in Sport mode and a more conservative margin (default 0.75) in Comfort mode. Finally, the safe cornering speed of the hybrid vehicle can be determined based on the safety margin and the maximum cornering speed by using the product of the maximum cornering speed and the safety margin as the safe cornering speed of the hybrid vehicle.

[0078] In some embodiments, gradually increasing the energy feedback intensity based on the hybrid vehicle's entry distance during vehicle braking before entering a curve can be achieved using the following steps:

[0079] Obtain the entry distance of the hybrid vehicle into the curve, and obtain the current vehicle speed from the vehicle motion parameters;

[0080] The deceleration curve of the hybrid vehicle before entering the curve is determined by the entry distance, the current vehicle speed, and the safe entry speed.

[0081] Under the premise of ensuring the coordination of the braking system, the gradient for increasing the energy feedback intensity is determined based on the deceleration curve before entering the curve, and then the gradient is used to gradually increase the energy feedback intensity of the hybrid vehicle before entering the curve.

[0082] It should be noted that, in this application, the energy feedback intensity before entering the curve refers to the quantitative index of the braking torque generated by the motor as a generator during the braking phase of the hybrid vehicle as it approaches the curve; the boost gradient refers to the rate of change of the energy feedback intensity with time or distance; and the deceleration curve describes the acceleration trend of the vehicle as it decelerates from its current speed to a safe entry speed.

[0083] In specific implementation, firstly, obtaining the hybrid vehicle's entry distance into the curve and acquiring the current vehicle speed from the vehicle's motion parameters can be achieved as follows: Determine the starting coordinates of the curve using high-precision map matching technology, calculate the real-time distance using GPS positioning and an inertial navigation system as the hybrid vehicle's entry distance, and acquire the current vehicle speed from the vehicle's motion parameters. Secondly, determining the hybrid vehicle's deceleration curve before entering the curve using the entry distance, the current vehicle speed, and the safe entry speed can be achieved as follows: Based on uniformly accelerated kinematics formulas, the system establishes a deceleration demand model, solves for the optimal deceleration curve in real time, and uses the solution as the hybrid vehicle's deceleration curve before entering the curve. Finally, ensuring the coordination of the braking system, determining the energy feedback intensity enhancement gradient based on the deceleration curve before entering the curve, and then using the enhancement gradient to gradually increase the hybrid vehicle's energy feedback intensity before entering the curve can be achieved as follows: Based on the deceleration curve... The system calculates the target braking force in real time, prioritizing regenerative braking provided by the electric motor, and precisely adjusts the negative torque output through the motor controller. Based on the remaining cornering distance and the current speed difference, the system dynamically adjusts the rate of increase in energy regenerative braking intensity. Specifically, it uses the remaining cornering distance and the current speed difference to match a progressive enhancement strategy from the vehicle controller's strategy mapping table. Initially, the regenerative braking intensity is increased with a small gradient, and the adjustment range is gradually increased as the vehicle approaches the curve. This strategy mapping table is a relationship mapping table composed of energy enhancement strategies corresponding to cornering distance and speed difference based on historical data statistics. During the adjustment process, the vehicle controller continuously monitors the driver's braking request and intelligently distributes the electric motor power and hydraulic braking force through the brake-by-wire system to ensure that the total braking force accurately responds to the pedal input. When the motor's regenerative braking capability is limited by the battery status, the vehicle controller automatically connects friction braking to supplement it, maintaining linear consistency in the brake pedal force, and ultimately achieving a smooth transition of vehicle speed to the safe cornering range while maximizing energy recovery efficiency.

[0084] It should be noted that, in this application, the specific calculation process for calculating the target braking force in real time based on the deceleration curve is as follows: the planned deceleration value is multiplied by the product of the vehicle's curb weight and rotational mass conversion factor to obtain the theoretical target braking force. This calculation process needs to be updated in real time. Considering the impact of vehicle load changes on mass, the actual vehicle mass can be estimated by using a suspension height sensor or drive motor load current. At the same time, the system will combine the current road slope information from the inertial measurement unit to compensate and correct the braking force to ensure consistent deceleration effect under different slope conditions.

[0085] In some embodiments, the vehicle speed constraint for determining the battery energy feedback intensity of the hybrid vehicle after the current cornering can be implemented in the following way: the final energy feedback intensity of the hybrid vehicle before the current cornering is used as the vehicle speed constraint for the battery energy feedback intensity of the hybrid vehicle after the current cornering. It should be noted that, in this application, the vehicle speed constraint refers to the upper limit threshold set for the battery energy feedback intensity from the perspective of vehicle driving safety and handling stability.

[0086] In step 104, the battery energy feedback intensity of the hybrid vehicle in the curve is balanced and arbitrated by the battery state constraint and vehicle speed constraint of the battery energy feedback intensity, and the balanced and arbitrated energy feedback intensity is sent to the hybrid vehicle's vehicle system for energy recovery operation.

[0087] In some embodiments, the battery energy feedback intensity of the hybrid vehicle in a curve is balanced and arbitrated by battery state constraints and vehicle speed constraints, with reference to... Figure 2 The diagram is a schematic flowchart of a balanced arbitration process in some embodiments of this application. The balanced arbitration process in this embodiment can be implemented using the following steps:

[0088] In step 1041, a balance value for the battery energy feedback intensity is determined by the battery state constraint and the vehicle speed constraint of the battery energy feedback intensity.

[0089] In step 1042, the balance value is used to perform power balancing on the battery energy feedback intensity of the hybrid vehicle in the curve, to obtain the balance arbitration value of the battery energy feedback intensity of the hybrid vehicle in the curve.

[0090] It should be noted that in this application, the balance arbitration value is the energy feedback intensity execution value that simultaneously meets the dual requirements of battery protection and vehicle control; the balance value is the minimum energy feedback intensity initially determined after comprehensively considering the battery system's withstand capability and vehicle driving safety. This balance value is located between the battery state constraint and the vehicle speed constraint, reflecting the system's preliminary coordination result for the two types of constraints.

[0091] In specific implementation, firstly, determining the balance value of the battery energy feedback intensity through the battery state constraint and vehicle speed constraint can be achieved in the following way: the minimum value between the battery state constraint and the vehicle speed constraint is taken as the balance value of the battery energy feedback intensity. Then, the balance value is used to perform power balancing on the battery energy feedback intensity of the hybrid vehicle in a curve, and the balance arbitration value of the battery energy feedback intensity of the hybrid vehicle in a curve can be obtained in the following way: the difference between the battery state constraint and the vehicle speed constraint is calculated as the arbitration quantity. This arbitration quantity represents the degree of difference between the battery system's tolerance and the vehicle's driving safety requirements. When the vehicle is detected to be approaching its stability limit, the weight of the driver-side constraint is automatically increased. The vehicle system has a built-in mapping table of the influence of the arbitration quantity on the battery energy feedback intensity. Therefore, the mapping table of the influence of the arbitration quantity on the battery energy feedback intensity can be obtained from the center console of the hybrid vehicle. The correction value corresponding to the arbitration quantity is selected from the mapping table, and then the sum of the correction value and the balance value is taken as the balance arbitration value of the battery energy feedback intensity of the hybrid vehicle in a curve.

[0092] Furthermore, in another aspect of this application, in some embodiments, this application provides a new energy vehicle in-vehicle infotainment system, which includes a feedback control unit, as referenced. Figure 3 The figure is a schematic diagram of the structure of a feedback control unit according to some embodiments of this application. The feedback control unit includes a monitoring module 201, a processing module 202, and an execution module 203, which are described below:

[0093] The monitoring module 201 in this application is mainly used to monitor the driving status information of the hybrid vehicle after the energy management display mode is activated in the vehicle system of the hybrid vehicle, and then extract the battery information and vehicle motion parameters of the hybrid vehicle from the driving status information.

[0094] Processing module 202, in this application, is used to determine the cumulative feedback time of battery energy in the hybrid vehicle when the charge value in the battery information is lower than the feedback threshold of the hybrid vehicle, and to determine the battery state constraint of the battery energy feedback intensity in the hybrid vehicle by combining the cumulative feedback time with the battery temperature, state of charge and health status in the battery information.

[0095] It should be noted that the processing module 202 is also used to calculate the safe entry speed of the hybrid vehicle into the curve based on the vehicle motion parameters and the curve radius in the road information. During the vehicle braking process before entering the curve, the energy feedback intensity is gradually increased based on the entry distance of the hybrid vehicle into the curve until the current speed of the hybrid vehicle is less than the safe entry speed into the curve, thereby determining the vehicle speed constraint of the battery energy feedback intensity of the hybrid vehicle after the current curve entry.

[0096] The execution module 203 in this application is mainly used to balance and arbitrate the battery energy feedback intensity of the hybrid vehicle in the curve through the battery state constraint and vehicle speed constraint of the battery energy feedback intensity, and send the balanced and arbitrated energy feedback intensity to the hybrid vehicle's vehicle system for energy recovery operation.

[0097] The foregoing has detailed examples of the new energy vehicle infotainment system and energy feedback control method provided in the embodiments of this application. It is understood that the corresponding device, in order to achieve the above functions, includes hardware structures and / or software modules corresponding to the execution of each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed by hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0098] In some embodiments, this application also provides a computer device, the computer device including a memory and a processor, the memory for storing a computer program, and the processor for calling and running the computer program from the memory, so that the computer device executes the energy feedback control method of the new energy vehicle in-vehicle system described above.

[0099] In some embodiments, reference Figure 4 The dashed lines in the figure indicate that the unit or module is optional. This figure is a structural schematic diagram of a computer device for implementing an energy feedback control method for a new energy vehicle infotainment system according to an embodiment of this application. The energy feedback control method for a new energy vehicle infotainment system described in the above embodiments can be achieved through… Figure 4 The computer device shown is used to implement this, and the computer device includes at least one processor 301, a memory 302 and at least one communication unit 305. The computer device may be a terminal device, a server or a chip.

[0100] Processor 301 can be a general-purpose processor or a special-purpose processor. For example, processor 301 can be a central processing unit (CPU), which can be used to control computer devices, execute software programs, and process data from software programs. The computer device may also include a communication unit 305 for inputting (receiving) and outputting (transmitting) signals.

[0101] For example, the computer device may be a chip, and the communication unit 305 may be the input and / or output circuit of the chip, or the communication unit 305 may be the communication interface of the chip, which may be a component of a terminal device, network device or other device.

[0102] For example, the computer device may be a terminal device or a server, and the communication unit 305 may be a transceiver of the terminal device or the server, or the communication unit 305 may be a transceiver circuit of the terminal device or the server.

[0103] The computer device may include one or more memories 302 storing a program 304. The program 304 can be executed by a processor 301 to generate instructions 303, causing the processor 301 to execute the method described in the above method embodiments according to the instructions 303. Optionally, the memory 302 may also store data (such as a target audit model). Optionally, the processor 301 may also read data stored in the memory 302, which may be stored at the same storage address as the program 304, or it may be stored at a different storage address than the program 304.

[0104] The processor 301 and memory 302 can be configured separately or integrated together, for example, integrated on the system on chip (SOC) of the terminal device.

[0105] It should be understood that each step of the above method embodiment can be completed by hardware logic circuits or software instructions in the processor 301. The processor 301 can be a CPU, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, such as discrete gate, transistor logic devices, or discrete hardware components.

[0106] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0107] For example, in some embodiments, this application also provides a computer-readable storage medium storing instructions or code that, when executed on a computer, cause the computer to implement the energy feedback control method of the new energy vehicle infotainment system described above.

[0108] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0109] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. An energy feedback control method for a new energy vehicle infotainment system, characterized in that, Includes the following steps: After the energy management display mode is activated in the vehicle system of the hybrid vehicle, the driving status information of the hybrid vehicle is monitored, and then the battery information and vehicle motion parameters of the hybrid vehicle are extracted from the driving status information. When the battery charge value in the battery information is lower than the feedback threshold of the hybrid vehicle, the cumulative feedback time of the battery energy in the hybrid vehicle is determined. The battery state constraint of the battery energy feedback intensity in the hybrid vehicle is determined by combining the cumulative feedback time with the battery temperature, state of charge and health status in the battery information. The safe entry speed of the hybrid vehicle is calculated based on the curve radius in the vehicle motion parameters and road information. During the vehicle braking process before entering the curve, the energy feedback intensity is gradually increased based on the entry distance of the hybrid vehicle until the current speed of the hybrid vehicle is less than the safe entry speed. Then, the vehicle speed constraint of the battery energy feedback intensity of the hybrid vehicle after entering the curve is determined. The battery energy feedback intensity of the hybrid vehicle in a curve is balanced and arbitrated by the battery state constraint and vehicle speed constraint of the battery energy feedback intensity, and the balanced and arbitrated energy feedback intensity is sent to the hybrid vehicle's vehicle system for energy recovery operation.

2. The method as described in claim 1, characterized in that, Extracting battery information and vehicle motion parameters from the driving status information specifically includes: The battery temperature, state of charge, health status, current vehicle speed, acceleration, and brake pedal opening are obtained from the driving status information. Battery information for hybrid vehicles is determined by battery temperature, state of charge, and state of health. The vehicle motion parameters of the hybrid vehicle are determined by the current vehicle speed, acceleration, and brake pedal opening.

3. The method as described in claim 1, characterized in that, Determining the cumulative energy return time of the battery in a hybrid vehicle specifically includes: When the energy feedback mode is activated, a timer is started to record the current feedback time, thus obtaining the duration of each energy feedback cycle. The cumulative energy return time of the battery in the hybrid vehicle is determined by all durations.

4. The method as described in claim 1, characterized in that, The battery state constraints for determining the battery energy feedback intensity in a hybrid vehicle by combining the cumulative feedback time with the battery temperature, state of charge, and health status in the battery information specifically include: The basic constraint coefficients for determining the battery energy feedback intensity are determined based on the battery temperature, state of charge, and state of health information in the battery information. Determine the attenuation factor of the cumulative feedback time on the battery energy feedback intensity; The battery state constraints for determining the battery energy feedback intensity in hybrid vehicles are determined by the attenuation factor and the basic constraint coefficient.

5. The method as described in claim 1, characterized in that, Calculating the safe cornering speed of a hybrid vehicle based on the vehicle motion parameters and the cornering radius in the road information specifically includes: Obtain the road surface adhesion coefficient and the curve radius from the road information of the road where the hybrid vehicle is traveling; The maximum entry speed of the hybrid vehicle into a curve is determined based on the road surface adhesion coefficient and the curve radius. The safety margin of the hybrid vehicle is set by the aforementioned vehicle motion parameters; The safe cornering speed of the hybrid vehicle is determined based on the safety margin and the maximum cornering speed.

6. The method as described in claim 1, characterized in that, During the vehicle braking process before entering a curve, the energy feedback intensity is gradually increased based on the curve entry distance of the hybrid vehicle, specifically including: Obtain the entry distance of the hybrid vehicle into the curve, and obtain the current vehicle speed from the vehicle motion parameters; The deceleration curve of the hybrid vehicle before entering the curve is determined by the entry distance, the current vehicle speed, and the safe entry speed. Under the premise of ensuring the coordination of the braking system, the gradient for increasing the energy feedback intensity is determined based on the deceleration curve before entering the curve, and then the gradient is used to gradually increase the energy feedback intensity of the hybrid vehicle before entering the curve.

7. The method as described in claim 1, characterized in that, The balancing and arbitration of the battery energy feedback intensity of hybrid vehicles in curves through battery state constraints and vehicle speed constraints specifically includes: The balance value of the battery energy feedback intensity is determined by the battery state constraint and the vehicle speed constraint of the battery energy feedback intensity. The aforementioned balance value is used to perform power balancing on the battery energy feedback intensity of the hybrid vehicle in a curve, thereby obtaining the balance arbitration value of the battery energy feedback intensity of the hybrid vehicle in a curve.

8. The method as described in claim 1, characterized in that, The hybrid vehicle is a hybrid electric vehicle that integrates a fuel engine and an electric motor.

9. The method as described in claim 1, characterized in that, The vehicle infotainment system is an intelligent interactive display and control system based on multi-source data fusion.

10. A vehicle infotainment system for a new energy vehicle, the vehicle infotainment system including a feedback control unit, characterized in that, The feedback control unit includes: The monitoring module is used to monitor the driving status information of the hybrid vehicle after the energy management display mode is activated in the vehicle system of the hybrid vehicle, and then extract the battery information and vehicle motion parameters of the hybrid vehicle from the driving status information. The processing module is used to determine the cumulative feedback time of battery energy in the hybrid vehicle when the battery charge value in the battery information is lower than the feedback threshold of the hybrid vehicle, and to determine the battery state constraint of the battery energy feedback intensity in the hybrid vehicle by combining the cumulative feedback time with the battery temperature, state of charge and health status in the battery information. The processing module is also used to calculate the safe entry speed of the hybrid vehicle into a curve based on the vehicle motion parameters and the curve radius in the road information. During the vehicle braking process before entering the curve, the energy feedback intensity is gradually increased based on the entry distance of the hybrid vehicle into the curve until the current speed of the hybrid vehicle is less than the safe entry speed into the curve, thereby determining the vehicle speed constraint of the battery energy feedback intensity of the hybrid vehicle after the current entry into the curve. The execution module is used to balance and arbitrate the battery energy feedback intensity of the hybrid vehicle in the curve by means of battery state constraints and vehicle speed constraints of the battery energy feedback intensity, and send the balanced and arbitrated energy feedback intensity to the hybrid vehicle's vehicle system for energy recovery operation.

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