A regenerative braking and hydraulic braking collaborative control method for new energy vehicles

Abstract

The application belongs to the technical field of new energy vehicles, and particularly relates to a regenerative braking and hydraulic braking collaborative control method for a new energy vehicle, which comprises the following steps: reading a current temperature of a power battery and a braking demand torque, calculating a battery temperature rise rate by using a sliding window mean difference method, predicting a remaining time and inversely calculating a regenerative braking torque ceiling prediction value; determining a torque gap based on the braking demand torque and the prediction value, mapping to the remaining time, issuing a pre-charge request and calculating a pre-charge target pressure when a trigger condition is met; obtaining a current actual available regenerative torque to calculate a hydraulic compensation amount, and applying a first-order low-pass filter for forward compensation; calculating an absolute error sliding mean of a prediction error, and adjusting a switching sensitivity coefficient to realize online correction when the absolute error sliding mean exceeds an upper limit of a tolerance band. The application compresses a transient braking force deficiency window and improves a safety margin of a braking process.

Description

Technical Field

[0001] This invention belongs to the field of new energy vehicle technology, specifically relating to a method for coordinated control of regenerative braking and hydraulic braking in new energy vehicles. Background Technology

[0002] New energy vehicles replace traditional internal combustion engines with electric drive systems. During braking, the drive motor can reverse to convert the vehicle's kinetic energy into electrical energy, which is then fed back to the battery—a process known as regenerative braking. To meet regulatory requirements for braking deceleration, the vehicle also retains a hydraulic friction braking system as a supplement. How to rationally distribute braking torque between these two braking systems is one of the core challenges in the chassis control of new energy vehicles.

[0003] Patent document CN108545071B discloses a regenerative braking control method that coordinates hydraulic and electric braking. This method includes acquiring current vehicle information via an onboard CAN network and onboard sensors; determining the current vehicle situation based on this information; determining the current situation based on a currently triggered speed-related controller; judging the participation of the braking source in the current situation; and formulating a braking strategy based on the current situation and the participation of the braking source. This solution comprehensively considers the coordinated control methods of hydraulic and electric braking in new energy vehicles under normal operating conditions, further optimizing the control method by comprehensively considering the control strategy under ABS triggering conditions of wheel lockup, the battery charging process, the maximum allowable braking torque of the motor by the battery, and the braking strategy when the vehicle speed is below the lower speed limit, thereby making the braking torque distribution more reasonable.

[0004] Existing collaborative control schemes typically use the battery state of charge (SOC) and the current motor speed as inputs. They determine the upper limit of the regenerative braking torque through a pre-calibrated static torque distribution table or rule-based threshold judgment, with any shortfall being supplemented by hydraulic braking. When the SOC is too high or the motor speed is below a certain threshold, the system directly switches to pure hydraulic braking mode. The entire distribution logic relies on a calibration database covering offline operating conditions.

[0005] Under continuous high-power regenerative braking conditions, such as on long slopes, the battery experiences a significant temperature rise due to the continuous receiving of charging current. This phenomenon causes the battery management system to tighten the upper limit of the acceptable charging current in real time, resulting in a dynamic decay of the regenerative braking torque ceiling during braking. Since existing static allocation tables cannot detect this temperature-driven capacity collapse, and the hydraulic braking system, after receiving a compensation request, must undergo a pressure-building process involving brake line filling and caliper clearance elimination (a pressure-building delay typically on the order of 100ms to 200ms), the combined effect creates a transient braking force deficiency window that cannot be filled by either side between the actual collapse of the regenerative braking torque ceiling and the effective establishment of the hydraulic torque. This directly threatens braking safety under high-speed or heavy-load conditions. Summary of the Invention

[0006] This invention provides a method for coordinated control of regenerative braking and hydraulic braking in new energy vehicles, in order to solve the technical problem in the prior art where battery temperature rise under continuous braking conditions causes the regenerative braking torque ceiling to dynamically collapse, while the hydraulic braking pressure build-up delay cannot timely fill the transient torque gap.

[0007] This invention provides a method for coordinated control of regenerative braking and hydraulic braking in new energy vehicles, comprising the following steps: S1, in response to a braking request activation, synchronously reading the current temperature of the power battery, the upper limit of the charging current corresponding to the current temperature, and the braking torque demand; calculating the battery temperature rise rate using the sliding window mean difference method based on the continuously sampled temperature sequence; predicting the remaining time required for the battery temperature to reach the upper limit of the thermal management temperature based on the battery temperature rise rate; and calculating the predicted value of the regenerative braking torque ceiling at that time by combining the upper limit of the charging current corresponding to the current temperature; S2, determining the equivalent deceleration loss corresponding to the torque gap based on the braking torque demand and the predicted value of the regenerative braking torque ceiling, and then calculating the margin. S3: When the remaining time meets the triggering conditions, a pre-pressure build-up request is issued, and the target pre-pressure build-up pressure is calculated; S4: When the regenerative braking torque ceiling enters the actual collapse stage, the current actual available regenerative torque is obtained, the hydraulic compensation amount is calculated based on the distribution relationship of the total braking torque, and the cutoff frequency is adaptively adjusted according to the current brake pedal force change rate, and a first-order low-pass filter is applied to the hydraulic compensation amount for positive compensation; S5: After the continuous braking condition ends, the predicted temperature rise trajectory is compared with the actual temperature trajectory, the absolute error sliding mean of the prediction error is calculated, and when the absolute error sliding mean exceeds the upper limit of the tolerance band, the adjustment step size is determined to correct the switching sensitivity coefficient of the sliding window online.

[0008] Its effect is that by advancing the prediction time of the regenerative braking torque ceiling to before the temperature rise triggers the capacity collapse, the timing misalignment between the collapse event and the hydraulic pressure build-up delay is effectively eliminated, and the window of insufficient transient braking force is significantly compressed, thereby significantly improving the safety margin of the braking process under high-speed and heavy-load conditions.

[0009] Furthermore, the battery temperature rise rate is calculated using the sliding window mean-difference method based on the temperature sequence obtained from continuous sampling, including:

[0010] Obtain the short-time standard deviation of the temperature sampling sequence and the sensor's nominal accuracy;

[0011] When the short-time standard deviation is greater than twice the sensor's nominal accuracy, extend the sliding window length.

[0012] When the short-time standard deviation is no greater than twice the nominal accuracy of the sensor, the sliding window length is reduced.

[0013] The battery temperature rise rate is finally obtained by averaging the temperature difference results of adjacent sampling points using a sliding window of a certain length.

[0014] Its effect is that, through adaptive window filtering based on the temperature rise rate, the system can maintain stable tracking of the real temperature rise trend in both noise-dominated and sudden operating condition scenarios, thereby improving the reliability of torque ceiling prediction.

[0015] Furthermore, the remaining time required for the battery temperature to reach the upper limit of the thermal management temperature is predicted based on the battery temperature rise rate, including:

[0016] Obtain the upper limit of thermal management temperature provided by the static configuration parameters of the battery management system;

[0017] Calculate the difference between the upper limit of the thermal management temperature and the current temperature;

[0018] Divide the difference by the battery temperature rise rate to get the remaining time.

[0019] Its effect is as follows: relying on the upper limit temperature of battery thermal management calibrated by the battery management system and the real-time filtered temperature rise rate, the remaining time for the battery to reach the temperature protection threshold is obtained by dividing the temperature difference by the temperature rise rate. The battery temperature rise trend is transformed into a time-domain predictive indicator that can be used for timing judgment, intuitively representing the arrival time of regenerative torque decay, providing a quantitative time basis for early triggering of hydraulic pre-pressure, and realizing the advance prediction of regenerative torque collapse events.

[0020] Furthermore, based on the predicted values ​​of the braking demand torque and the regenerative braking torque ceiling, the equivalent deceleration deficit corresponding to the torque gap is determined, and then the margin time is calculated, including:

[0021] The difference between the braking demand torque and the predicted ceiling value of the regenerative braking torque is calculated and divided by the product of the vehicle's equivalent mass and the effective radius of the wheel to obtain the equivalent deceleration loss.

[0022] Obtain the maximum acceptable speed deviation for the vehicle;

[0023] Divide the maximum speed deviation by the equivalent deceleration loss to obtain the margin time.

[0024] Its effect is that by converting the torque gap into an equivalent deceleration deficit and mapping it to the margin time, the intervention timing can be adaptively adjusted under different vehicle speeds, loads and road adhesion conditions, thus taking into account both braking safety and the service life of the hydraulic system.

[0025] Furthermore, when the triggering conditions are met within the remaining time, a pre-pressure build-up request is issued, and the target pre-pressure build-up pressure is calculated, including:

[0026] Obtain the pressure build-up delay reference for the hydraulic braking system;

[0027] When the remaining time is less than or equal to the sum of the pressure build-up delay baseline and the margin time, the triggering condition is determined to be met and a pre-pressure build-up request is issued.

[0028] Obtain the conversion coefficient between hydraulic pressure and clamping force;

[0029] The difference between the braking demand torque and the predicted ceiling value of the regenerative braking torque is divided by the product of the hydraulic and clamping force conversion coefficient and the effective radius of the wheel to finally obtain the pre-built pressure target pressure.

[0030] Furthermore, the hydraulic compensation amount is calculated based on the distribution relationship of the total braking torque, including:

[0031] Obtain the current actual available regenerative torque reported in real time by the motor controller;

[0032] The hydraulic compensation amount is obtained by subtracting the current available regenerative torque from the braking torque requirement.

[0033] Furthermore, the cutoff frequency is adaptively adjusted based on the current rate of change of brake pedal force, including:

[0034] Obtain the upper and lower bounds of the cutoff frequency, as well as the boundary values ​​of the rate of change of pedal force corresponding to smooth deceleration and emergency braking conditions;

[0035] Calculate the ratio of the difference between the current rate of change of brake pedal force and the lower limit boundary value;

[0036] A linear mapping is performed between the upper and lower bounds based on the difference ratio, and the cutoff frequency is finally obtained.

[0037] Its effect is that, through adaptive adjustment of the cutoff frequency, the hydraulic compensation during the transition period ensures response speed under emergency braking conditions and suppresses pedal vibration under smooth deceleration conditions, thereby improving the driver's control experience during the braking force switching process.

[0038] Further, the moving average of the absolute error of the prediction error is calculated, including:

[0039] Obtain the total number of sampling points during this braking process;

[0040] Calculate the absolute error between the predicted temperature rise trajectory and the actual temperature trajectory at each sampling point;

[0041] The absolute error is summed up and then divided by the total number of sampling points to obtain the moving average of the absolute error.

[0042] Furthermore, when the absolute error moving average exceeds the upper limit of the tolerance band, the adjustment step size is determined to correct the switching sensitivity coefficient of the sliding window online, including:

[0043] Obtain the maximum prediction error recorded in historical braking conditions, as well as the physical upper and lower bounds of the window length;

[0044] Calculate the percentage by which the absolute error moving average exceeds the upper limit of the tolerance band;

[0045] Multiply the amplitude ratio by the difference between the physical upper and lower bounds to obtain the adjustment step size;

[0046] The switching sensitivity coefficient is adjusted by adjusting the step size, and finally the online correction is completed.

[0047] Furthermore, the current temperature of the power battery, the upper limit of the charging current corresponding to the current temperature, and the braking torque required are read simultaneously, including: collecting the current temperature, the upper limit of the charging current corresponding to the current temperature, and the braking torque required within the same control cycle.

[0048] The beneficial effects are: after each continuous braking, the filter adaptive parameters are corrected online, which can automatically compensate for the thermal characteristic drift caused by battery aging, and ensure the stable and reliable prediction accuracy of battery temperature rise and regenerative braking torque ceiling throughout the entire life cycle of the vehicle; moreover, this solution is completely based on the electronic control software logic, without the need to make any changes to the braking system hardware, and can be directly installed on existing vehicle electronic control platforms, making it more versatile and practical for engineering. Attached Figure Description

[0049] Figure 1 This is a flowchart of a method for coordinated control of regenerative braking and hydraulic braking in new energy vehicles.

[0050] Figure 2This is a comparison diagram showing the adaptive adjustment of the low-pass filter cutoff frequency in the hydraulic compensation stage of this invention. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] An embodiment of the regenerative braking and hydraulic braking coordinated control method for new energy vehicles provided by this invention:

[0053] like Figure 1 As shown, the method for coordinated control of regenerative braking and hydraulic braking in new energy vehicles includes the following steps:

[0054] S1 calculates the temperature rise rate and predicts the torque ceiling.

[0055] In an optional embodiment, in response to a braking request activation, the controller synchronously reads the current temperature of the power battery at a fixed sampling period of no more than 10ms. Current measured charging current The upper limit of charging current corresponding to the current temperature output by the battery management system. and braking torque requirements The four signals are acquired within the same control cycle, avoiding false rate bias caused by channel sampling misalignment.

[0056] Based on the temperature sequence obtained from continuous sampling, the controller uses the sliding window mean-difference method to calculate the battery temperature rise rate. The existing basic first-order difference formula is:

[0057] ;

[0058] Indicates the basic single-step battery temperature rise rate. Indicates the battery temperature during the current cycle. This indicates the battery temperature in the previous cycle.

[0059] Because temperature sensor readings inevitably experience periodic electrical interference during continuous braking, directly subtracting adjacent samples would amplify the noise component between them, causing high-frequency fluctuations in the rate estimate. To improve the basic formula, a sliding window mean is introduced, resulting in the window mean difference relationship:

[0060] ;

[0061] in Sampling frequency, The length of the sliding window. Indicates working backwards. The battery temperature over a single cycle. This relationship is constructed based on the fundamental formula in a single step. The single difference extension on is to the nearest The step difference results are averaged to make the short-period measurement noise cancel each other out during the averaging process, thus preserving the ability to track the true temperature rise trend.

[0062] Furthermore, based on the short-time standard deviation of the temperature sampling sequence With sensor nominal accuracy Determine the ratio relationship between them The possible values ​​of , where Exceed This means that the noise contribution in the observed fluctuations is on par with the upper limit of the sensor's accuracy. Time (of which) To switch the sensitivity coefficient (initial calibration value of 2), indicating that the current sampling sequence is dominated by noise, the processor will... Extend to cover preset noise suppression duration The corresponding number of samples is denoted as For example, You can take 500ms; when When the signal is stable, the processor will... Shrink to cover preset tracking response time The corresponding number of samples is denoted as For example, You can take 100ms.

[0063] In obtaining stability Later, when When the temperature is below the preset minimum temperature rise threshold, the current temperature is determined to be in a quasi-steady state, and the subsequent pre-pressure build-up process is not triggered; the controller maintains the normal distribution mode. When the temperature exceeds this threshold, the battery temperature is predicted to reach the upper limit of the thermal management temperature based on the following relationship. Required remaining time :

[0064] ;

[0065] in Provided by the static configuration parameters of the battery management system.

[0066] Then Substitute the temperature and charging current upper limit calibration curves provided by the battery management system. To obtain the upper limit of the charging current at the predicted time. Based on the current motor speed and torque characteristics, the predicted ceiling value of the regenerative braking torque at that time is calculated. This predicted value serves as the core input for subsequent steps. It is updated on a rolling basis with each new sample in every control cycle to ensure that subsequent trigger decisions are always based on the latest temperature rise trend.

[0067] A robust estimate of the battery temperature rise rate is achieved by using adaptive window mean difference filtering, and it is transformed into a time-domain prediction of the regenerative braking torque ceiling. This provides a reliable physical input for the advanced calculation of the subsequent pressure build-up timing, making up for the deficiency of existing static allocation tables in that they cannot perceive the temperature rise process.

[0068] S2, calculate the equivalent deceleration missing amount and issue a pre-build pressure request.

[0069] In an optional embodiment, since the hydraulic braking system requires three sequential physical processes—solenoid valve opening, brake fluid filling, and caliper gap elimination—from the controller issuing a pressure increase request to the caliper actually generating an effective clamping force, the total delay of this process is denoted as... During the vehicle off-line calibration phase, step requests are applied to the hydraulic actuators under different temperature and pipeline pressure conditions, and the response time of the torque sensor is recorded. The median delay under each condition is taken as the nominal value of the system and stored in the non-volatile storage area of ​​the controller as the pressure build-up delay reference.

[0070] In response to The pre-pressure build-up process is triggered when the following conditions are met:

[0071] ;

[0072] in The margin time characterizes the maximum acceptable speed deviation of the vehicle under the current operating conditions if the transient torque gap continues to act. The corresponding time window. The requirements are determined comprehensively based on the vehicle braking comfort calibration requirements and the distance safety requirements. For example, The value can be 2 km / h; The calculation formula is as follows:

[0073] ;

[0074] in The equivalent deceleration deficit corresponding to the torque gap under the current operating condition is determined by the following relationship:

[0075] ;

[0076] in For the equivalent mass of the whole vehicle, The effective radius of the wheel, The braking torque is required. Because... It updates on a rolling basis with each control cycle, making It changes in real time, thus It also dynamically follows. The larger the torque gap, the more likely the vehicle is under high-speed, heavy-load conditions. The larger, The smaller the value, the earlier the triggering condition is met, thus ensuring a safety margin.

[0077] It should be noted that there are many other ways to estimate the road surface adhesion coefficient in this field. Those skilled in the art can choose different methods according to actual needs, such as using the wheel slip ratio output of the vehicle's existing electronic stability system or anti-lock braking system. When the estimated road surface adhesion coefficient is low, it indicates that the vehicle is on a low-adhesion road surface, at which point the processor will... The lower limit of its calibration range is taken to further advance the triggering time and ensure a safety margin on low-adhesion road surfaces.

[0078] Furthermore, the pre-built target pressure is calculated based on the predicted torque gap. :

[0079] ;

[0080] in The hydraulic and clamping force conversion coefficient is determined by the brake's geometric parameters and friction coefficient, ensuring a precise match between the pre-built pressure target and the impending torque gap.

[0081] Through By issuing pre-pressure requests in advance, the hydraulic system is pressurized and ready to respond when the regenerative braking torque ceiling actually begins to collapse, thus reducing the transient torque gap window from its original state. With the magnitude compressed to near zero, it can adaptively adjust the intervention timing under different vehicle speeds, loads, and road surface adhesion conditions, balancing braking safety and the service life of the hydraulic system.

[0082] S3, adjust the cutoff frequency filter positive compensation.

[0083] In an optional embodiment, in response to the ceiling entering the actual collapse phase, the controller enters a dual-channel real-time allocation mode. It acquires the current actual available regenerative torque reported in real-time by the motor controller. Effective torque feedback actually established with the hydraulic system ,in Constrained by motor speed, bus voltage, and real-time current limits of the battery management system, and updated in each control cycle. Based on the pressure sensor readings, both signals are refreshed in real time at the control cycle level.

[0084] Based on the principle of hard constraint conservation, the distribution relationship of the total braking torque is as follows:

[0085] ;

[0086] Hydraulic compensation In each control cycle, positive compensation is performed in real time based on the actual reduction in regenerative torque. Since the hydraulic system's backlash elimination has been completed during the pre-pressure build-up phase, the hydraulic system is now in a backlash-free standby state, responding... The incremental adjustment delay is only the pressure fine-tuning delay, thus ensuring the total braking torque. Follow closely throughout This avoids torque depression.

[0087] To prevent high-frequency vibrations in the hydraulic compensation amount from being transmitted to the driver via pedal torque, Apply a first-order low-pass filter based on the current rate of change of brake pedal force. Adaptive adjustment of cutoff frequency The calculation relationship is as follows:

[0088] ;

[0089] in and These are the upper and lower bounds of the cutoff frequency, respectively. Take the lower limit of the frequency of pedal vibration that the driver can perceive, for example, 2Hz can be selected; The upper bound of the effective response bandwidth of the hydraulic actuator in the braking system is taken, for example, 20Hz can be selected. and These are the boundary values ​​of the rate of change of pedal force corresponding to smooth deceleration and emergency braking conditions, respectively, for example. 50 N / s can be taken. 300 N / s can be used.

[0090] because and There is a linear mapping relationship between them, when Exceeding When the range is reached, the processor will Each limited to or The larger this value, the more urgent the driver's intention to press the pedal. The higher the value, the wider the response bandwidth of the hydraulic compensation, and the faster the braking force follows the speed; the smaller the value, the smoother the pedaling action. The lower the value, the more thoroughly high-frequency vibration components are filtered out, resulting in a smoother pedal feel.

[0091] In response to the regenerative braking torque, the ceiling collapses and reaches a new temperature-constrained steady state. As the system stabilizes, the dual-channel allocation ratio becomes fixed. At this point, the system exits the transitional dynamic adjustment mode and enters a steady-state collaborative working state, and the hydraulic compensation amount no longer changes significantly with the control cycle.

[0092] By combining the hard constraint conservation allocation principle with the adaptive low-pass filter of the cutoff frequency, the braking torque is compensated without gaps during the transition period of regenerative torque collapse. At the same time, the pedal feel quality under different pedaling conditions is taken into account, and the problem of braking force depression and pedal vibration that can be perceived by the driver during the torque switching process in the existing solution is eliminated.

[0093] S4 calculates the moving average of the absolute error to achieve online correction.

[0094] In an optional embodiment, in response to the end of each continuous braking condition, the controller performs a retrospective verification of the temperature rise rate prediction model. This involves analyzing the predicted temperature rise trajectory during braking. Actual temperature trajectory recorded by the battery management system Perform time-by-time comparisons and calculate the moving average of the absolute error of the prediction error. :

[0095] ;

[0096] in This represents the total number of sampling points during this braking process.

[0097] Next, With the upper limit of the tolerance zone Comparison, among which According to the sensor's nominal accuracy Determined by multiplying by a preset multiplier, denoted as For example, 3 can be chosen. When Exceeding When this occurs, it is determined to be model drift, triggering a correction; when Not exceeding In such cases, no adjustments are made to avoid overreacting to normal fluctuations.

[0098] In response to Determine the current temperature rise rate filter window The adaptive parameters are offset, at which point the controller's sensitivity coefficient to switching is affected. Perform small-step adjustments. Determine the adjustment step size based on the extent to which the error exceeds the tolerance band. :

[0099] ;

[0100] in This represents the maximum prediction error recorded in historical braking conditions. and These represent the upper and lower physical bounds of the window length, respectively. A larger value indicates a more severe prediction bias and a deeper degree of model drift. The step size... The larger the value, the stronger the parameter correction; the smaller the value, the closer the deviation is to the tolerance band boundary, resulting in a smaller step size and a more conservative correction, avoiding repeated fluctuations of the parameter in the critical range. Switching Sensitivity Coefficient The corrected value is ,in and Corresponding to the normalized range based on window length.

[0101] It should be noted that the object of the correction is the switching sensitivity coefficient. Instead of directly modifying the temperature sensor calibration value, the correction process does not affect the original temperature signal link of the battery management system. Furthermore, the system automatically reverts to the initial calibration value in case of correction failure, ensuring engineering safety. Subsequently, the corrected parameters are written to the controller's non-volatile memory area so that they can be directly used as the initial configuration parameters for temperature rise rate estimation upon the next power-on.

[0102] As battery aging increases internal resistance, the heat dissipation power at the same current also increases, leading to a systematic drift in thermal characteristics compared to a new battery. Without online correction, the temperature rise prediction based on factory calibration parameters will continue to be lower as aging progresses, causing the pre-voltage build-up trigger time to gradually lag, eventually resulting in a reappearance of transient torque gaps. Online correction allows the vehicle to automatically track and calibrate itself according to changes in thermal characteristics caused by battery aging during long-term operation, thereby maintaining the prediction accuracy within a reliable range.

[0103] Thus, by backtracking verification based on the mean of absolute error and parameter correction with adaptive step size, the prediction accuracy of the thermal model is self-maintained throughout its entire life cycle, enabling the entire collaborative control scheme to maintain effective prediction and proactive response capabilities against torque ceiling collapse throughout the entire battery aging process.

[0104] like Figure 2 As shown in the figure, the area filled by the cross lines represents the cutoff frequency range when the existing method adopts a fixed segmentation strategy, and the two horizontal dashed lines are its upper and lower boundaries; the solid line is the adaptive linear mapping curve of the present invention based on the rate of change of pedal force. It maintains a low cutoff frequency in the steady region (0~50N / s), monotonically increases with the rate of change of pedal force in the linear mapping region (50~300N / s), and saturates to the maximum value in the emergency region (above 300N / s), thus realizing continuous adaptive matching between the filtering bandwidth and braking demand.

[0105] The above are all preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A method for coordinated control of regenerative braking and hydraulic braking in a new energy vehicle, characterized in that, Includes the following steps: S1, In response to the braking request activation, the current temperature of the power battery, the upper limit of the charging current corresponding to the current temperature, and the braking torque demand are read synchronously. Based on the temperature sequence obtained by continuous sampling, the battery temperature rise rate is calculated using the sliding window mean difference method. Based on the battery temperature rise rate, the remaining time required for the battery temperature to reach the upper limit of the thermal management temperature is predicted. Combined with the upper limit of the charging current corresponding to the current temperature, the predicted value of the regenerative braking torque ceiling at that time is calculated. S2, Based on the braking torque demand and the predicted value of the regenerative braking torque ceiling, the equivalent deceleration missing amount corresponding to the torque gap is determined, and then the margin time is calculated. When the remaining time meets the triggering condition, a pre-warning is issued. S3, when the regenerative braking torque ceiling enters the actual collapse stage, obtain the current actual available regenerative torque, calculate the hydraulic compensation amount based on the distribution relationship of the total braking torque, and adaptively adjust the cutoff frequency according to the current brake pedal force change rate, and apply a first-order low-pass filter to the hydraulic compensation amount for positive compensation; S4, after the continuous braking condition ends, compare the predicted temperature rise trajectory with the actual temperature trajectory, calculate the absolute error sliding mean of the prediction error, and when the absolute error sliding mean exceeds the upper limit of the tolerance band, determine the adjustment step size to correct the switching sensitivity coefficient of the sliding window online.

2. The method for coordinated control of regenerative braking and hydraulic braking in new energy vehicles according to claim 1, characterized in that, The battery temperature rise rate is calculated using the sliding window mean-difference method based on the temperature sequence obtained through continuous sampling, including: Obtain the short-time standard deviation of the temperature sampling sequence and the sensor's nominal accuracy; When the short-time standard deviation is greater than twice the sensor's nominal accuracy, extend the sliding window length. When the short-time standard deviation is no greater than twice the nominal accuracy of the sensor, the sliding window length is reduced. The battery temperature rise rate is finally obtained by averaging the temperature difference results of adjacent sampling points using a sliding window of a certain length.

3. The method for coordinated control of regenerative braking and hydraulic braking in new energy vehicles according to claim 1, characterized in that, Predict the remaining time required for the battery temperature to reach the upper limit of the thermal management temperature based on the battery temperature rise rate, including: Obtain the upper limit of thermal management temperature provided by the static configuration parameters of the battery management system; Calculate the difference between the upper limit of the thermal management temperature and the current temperature; Divide the difference by the battery temperature rise rate to get the remaining time.

4. The method for coordinated control of regenerative braking and hydraulic braking in new energy vehicles according to claim 1, characterized in that, Based on the predicted values ​​of braking demand torque and regenerative braking torque ceiling, the equivalent deceleration deficit corresponding to the torque gap is determined, and then the margin time is calculated, including: The difference between the braking demand torque and the predicted ceiling value of the regenerative braking torque is calculated and divided by the product of the vehicle's equivalent mass and the effective radius of the wheel to obtain the equivalent deceleration loss. Obtain the maximum acceptable speed deviation for the vehicle; Divide the maximum speed deviation by the equivalent deceleration loss to obtain the margin time.

5. The method for coordinated control of regenerative braking and hydraulic braking in new energy vehicles according to claim 1, characterized in that, When the remaining time meets the triggering conditions, a pre-pressure build-up request is issued, and the target pre-pressure build-up pressure is calculated, including: Obtain the pressure build-up delay reference for the hydraulic braking system; When the remaining time is less than or equal to the sum of the pressure build-up delay baseline and the margin time, the triggering condition is determined to be met and a pre-pressure build-up request is issued. Obtain the conversion coefficient between hydraulic pressure and clamping force; The difference between the braking demand torque and the predicted ceiling value of the regenerative braking torque is divided by the product of the hydraulic and clamping force conversion coefficient and the effective radius of the wheel to finally obtain the pre-built pressure target pressure.

6. The method for coordinated control of regenerative braking and hydraulic braking in new energy vehicles according to claim 1, characterized in that, The hydraulic compensation is calculated based on the distribution formula of the total braking torque, including: Obtain the current actual available regenerative torque reported in real time by the motor controller; The hydraulic compensation amount is obtained by subtracting the current available regenerative torque from the braking torque requirement.

7. The method for coordinated control of regenerative braking and hydraulic braking in new energy vehicles according to claim 1, characterized in that, The cutoff frequency is adaptively adjusted based on the current rate of change of brake pedal force, including: Obtain the upper and lower bounds of the cutoff frequency, as well as the boundary values ​​of the rate of change of pedal force corresponding to smooth deceleration and emergency braking conditions; Calculate the ratio of the difference between the current rate of change of brake pedal force and the lower limit boundary value; A linear mapping is performed between the upper and lower bounds based on the difference ratio, and the cutoff frequency is finally obtained.

8. The method for coordinated control of regenerative braking and hydraulic braking in new energy vehicles according to claim 1, characterized in that, Calculate the moving average of the absolute error of the prediction error, including: Obtain the total number of sampling points during this braking process; Calculate the absolute error between the predicted temperature rise trajectory and the actual temperature trajectory at each sampling point; The absolute error is summed up and then divided by the total number of sampling points to obtain the moving average of the absolute error.

9. The method for coordinated control of regenerative braking and hydraulic braking in new energy vehicles according to claim 1, characterized in that, When the absolute error moving average exceeds the upper limit of the tolerance band, the adjustment step size is determined to correct the switching sensitivity coefficient of the sliding window online, including: Obtain the maximum prediction error recorded in historical braking conditions, as well as the physical upper and lower bounds of the window length; Calculate the percentage by which the absolute error moving average exceeds the upper limit of the tolerance band; Multiply the amplitude ratio by the difference between the physical upper and lower bounds to obtain the adjustment step size; The switching sensitivity coefficient is adjusted by adjusting the step size, and finally the online correction is completed.

10. The method for coordinated control of regenerative braking and hydraulic braking in new energy vehicles according to claim 1, characterized in that, Synchronously read the current temperature of the power battery, the upper limit of the charging current corresponding to the current temperature, and the braking torque required, including: completing the acquisition of the current temperature, the upper limit of the charging current corresponding to the current temperature, and the braking torque required within the same control cycle.

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