Method for operating a motor vehicle with a mixed braking system

Abstract

A mixed braking system comprises a regenerative braking system (regeneration) and a friction braking system, which together decelerate a motor vehicle. A method for operating the mixed braking system includes a vehicle control unit that receives a braking command with a corresponding brake torque request. From this brake torque request, the control unit determines a regenerative braking torque for the regenerative braking system and a friction braking torque for the friction braking system. From the friction braking torque and an estimated temperature of a rotating friction brake element, the control unit determines a temperature-dependent coefficient of friction, and from the friction braking torque and an estimated surface smoothness state of the friction braking system, it determines a smoothness-dependent coefficient of friction.A modified friction braking torque is calculated from a modified brake pressure coefficient, which is derived from the temperature-dependent and smoothness-dependent friction coefficients. The friction braking system applies this modified friction braking torque to decelerate / stop the vehicle.

Description

[0001] This description refers generally to braking systems for motor vehicles. In particular, aspects of this description relate to mixed friction and regenerative braking systems for one-pedal driving of electric vehicles.

[0002] Today's production vehicles, such as modern automobiles, are originally equipped with a powertrain that propels the vehicle and supplies power to its onboard electronics. In motor vehicles, for example, the powertrain typically consists of a drive motor that transmits the drive torque to the vehicle's drive system (e.g., differential, axles, camshafts, wheels, etc.) via an automatic or manual transmission. Historically, motor vehicles were powered by internal combustion engines (ICEs) because they were readily available, relatively lightweight, had a higher energy density, and were generally more efficient.Hybrid electric and fully electric vehicles (collectively referred to as "electric vehicles"), on the other hand, utilize alternative energy sources to power the vehicle, thus minimizing or eliminating reliance on a fossil fuel-based engine for traction. A fully electric vehicle (FEV), for example, completely forgoes an internal combustion engine and its associated peripheral powertrain components, relying instead on a rechargeable energy storage system (RESS) and a traction motor to propel the vehicle. Hybrid electric vehicle (HEV) powertrains, however, utilize multiple sources of traction to propel the vehicle, typically employing an internal combustion engine in conjunction with a battery- or fuel cell-powered traction motor.

[0003] Motor vehicles are generally equipped with a hydraulic, pneumatic, or electromechanical braking system, which is activated by the driver or—in the case of advanced driver assistance systems (ADAS) and autonomous vehicles—by an onboard control system to selectively decelerate and eventually stop the vehicle. The most common type of braking system used in modern passenger cars is a friction braking system, in which a hydraulically actuated piston brings a brake pad or shoe (the "friction brake element") into frictional engagement with a rotating drum or rotor (the "rotating brake element"). In disc brake systems, the piston moves back and forth within a caliper mounted on the steering knuckle, and the brake rotor is bolted to the spindle to rotate with the wheel assembly.The friction braking system converts the vehicle's kinetic energy into heat energy in the frictionally interlocking rotary and friction brake elements to slow down or stop the rotation of the corresponding wheel assembly. Some modern vehicles use a decentralized ("brake-by-wire") braking system, in which each wheel assembly contains a single motor-driven actuator, and a central brake control module activates the actuators individually to provide the desired braking force at that wheel.

[0004] In hybrid and fully electric vehicles, an electronic vehicle motion controller (VMC) can interpret the driver's accelerator and brake pedal positions to derive a desired axle torque. The VMC can then compare the driver's desired axle torque with the torque requirements of the advanced driver assistance system (ADAS) and the torque requirements for automatic vehicle interventions, such as overspeed protection, traction or stability control, regenerative braking, adaptive cruise control (ACC), etc. A final axle torque request is then sent by the VMC to a powertrain control module (PCM) or a brake control module (BCM) to assess how a combination of actuators, such as the motor, traction motor(s), transmission, friction brakes, etc., can respond.The VMC is intended to be used to achieve a final, desired axle torque. When the vehicle is moving forward and the driver takes their foot off the accelerator pedal (a "tilt maneuver"), the VMC can automatically apply negative axle torque to decelerate (brake) the vehicle. In electric vehicles, the desired negative axle torque can be generated by a "mixed braking system" by combining the negative motor torque with the vehicle's friction braking system.

[0005] German patent DE 10 2009 004 528 A1 describes a brake system control method that determines vehicle operating conditions, compares these conditions with a permissible range, and uses a neural network to predict an expected coefficient of friction when the conditions are within the range. When the conditions are outside the range, the method determines the required braking force using a constant coefficient of friction and calculates the required braking force using the expected coefficient of friction when the conditions are within the range. The vehicle operating conditions include vehicle speed, brake pressure, a modeled brake disc temperature, and an application state. The expected coefficient is multiplied by a constant or a calculated correction factor.A vehicle comprises a machine, a transmission and a braking system with a controller and an algorithm for predicting a coefficient of friction for two brake discs for calculating a hydraulic brake pressure and for applying the braking system using the hydraulic brake pressure.

[0006] US 2016 / 0039292A1 describes a brake ECU that stores a vehicle body deceleration when the braking mode is switched from a regenerative braking mode to a cooperative braking mode. The brake ECU stores a deceleration during a switch to a friction braking mode when the braking mode is changed from the cooperative to the friction braking mode while the brake application is held constant. The brake ECU calculates a deceleration ratio by dividing the deceleration by the regenerative braking factor and updates the deceleration ratio. The brake ECU corrects a target fluid pressure using this deceleration ratio.

[0007] It can be considered a task to specify an improved method for operating a motor vehicle with a mixed braking system.

[0008] The problem is solved by a method according to claim 1. The invention is defined by the claims. Furthermore, systems and vehicles that can be operated with the method are described.

[0009] This paper presents intelligent vehicle braking systems with associated control logic for learning and compensating for friction braking, methods for manufacturing and operating such systems, and electrically powered vehicles equipped with such vehicle braking systems for optimized one-pedal driving (OPD). As a non-restrictive example, a control protocol for a mixed vehicle braking system continuously estimates the current surface smoothness state of the friction brake and derives a friction brake compensation value for a corresponding brake clamping force to deliver a commanded deceleration. Many conventional vehicle braking systems compensate for friction variations with a single, “compromised” brake friction coefficient to provide a minimum acceptable system performance over the brake hardware lifecycle.In contrast, disclosed vehicle braking systems implement a thermal model of the friction brake, derive theoretical braking forces, and track real-time and commanded vehicle decelerations to estimate the surface smoothness state of the friction brakes. The estimated surface smoothness state is used to calculate a fitted coefficient of friction (Cf) dependent on the surface smoothness state. fb ) used; the electronic brake control module (EBCM) applies the adapted coefficient to convert the commanded braking request into a modified brake pressure coefficient (C). pb) to convert. This helps to minimize or eliminate uneven deceleration in friction brakes due to fluctuations in the coefficient of friction caused by the wear of pads and rotors. While the solutions presented here are not limited per se, they can be applied in particular to electrohydraulic and electromagnetic braking systems of electric vehicles.

[0010] Parts of this description relate to mixed vehicle braking systems, the control logic of the braking system, and feedback control methods for learning and compensating for friction brake wear. A method according to the invention for operating a motor vehicle with a mixed braking system is presented, which includes both a regenerative braking system (regeneration) and a friction braking system, which together brake one or more of the vehicle's road wheels. This representative method includes, in any order and in any combination with any of the options and features disclosed above and below: receiving, e.g., by a stationary or remote microcontroller, central processing unit, control module, logic device, integrated circuit (IC), or a network of processors / controllers / modules / devices (collectively, "vehicle control"), from a user input device (e.g., a touchscreen)., brake pedal) or a vehicle control module (e.g., ADAS module) sends a braking command with a corresponding total braking torque request to decelerate / stop the vehicle; determine, e.g., by the vehicle control unit from the total braking torque request, a regeneration braking torque for the regeneration braking system and a friction braking torque for the friction braking system; optionally estimate, e.g., by the vehicle control unit using the friction braking torque and an estimated temperature of a rotating friction brake element (e.g., drum or rotor), a temperature-dependent coefficient of friction; estimate, e.g., by the vehicle control unit using the friction braking torque and an estimated surface smoothness state of the friction braking system, a smoothness-dependent coefficient of friction; determine, e.g., by the vehicle control system, a modified brake pressure coefficient using the smoothness-dependent coefficient of friction and optionally the temperature-dependent coefficient of friction; determining a modified friction braking torque using the modified brake pressure coefficient; and instructing the friction braking system, e.g., by the vehicle control system, to apply the modified friction braking torque to one or more of the vehicle's road wheels.

[0011] Parts of this description also refer to computer-readable media (CRM) containing instructions for the controller to execute for providing learning and compensation functions for friction brakes in mixed vehicle braking systems. In one example, a non-volatile CRM stores instructions that can be executed by one or more vehicle controllers of a motor vehicle with a mixed braking system. These CRM-stored instructions, when executed, cause the vehicle controller(s) to perform operations, including: receiving a vehicle braking command with a total braking torque request for the motor vehicle from a user input device or a vehicle control module of the motor vehicle; determining a regenerative braking torque for the regenerative braking system and a friction braking torque for the friction braking system using the total braking torque request;Estimating a temperature-dependent coefficient of friction using the friction braking torque and an estimated temperature of a rotating friction brake element; determining a modified brake pressure coefficient using the temperature-dependent coefficient of friction and the smoothness-dependent coefficient of friction; determining a modified friction braking torque using the modified brake pressure coefficient; and instructing the friction brake system to apply the modified friction braking torque to the one or more road wheels of the motor vehicle.

[0012] Further parts of this description concern intelligent motor vehicles with optimized estimation of friction braking torque and optimized learning and compensation of friction brake wear for mixed braking systems, e.g., for one-pedal driving. As used herein, the terms "vehicle" and "motor vehicle" may be used interchangeably and synonymously to include any relevant vehicle platform, such as passenger cars, commercial vehicles, industrial vehicles, tracked vehicles, off-road vehicles and all-terrain vehicles (ATVs), motorcycles, agricultural equipment, aircraft, spacecraft, etc. In an example, a motor vehicle has a vehicle body with a passenger compartment, multiple road wheels attached to the vehicle body (e.g., via corner modules coupled to a unibody or body-on-frame chassis), and other standard original equipment.In electric vehicles, one or more electric drive motors operate alone (e.g., in FEV powertrains) or in conjunction with an internal combustion engine (e.g., in HEV powertrains) to selectively drive one or more of the wheels, thus propelling the vehicle forward. A mixed braking system is also fitted to the vehicle body, comprising a regenerative braking system and a friction braking system, which, in response to braking commands from a user input device or a vehicle control module, jointly decelerate one or more of the wheels.

[0013] To continue the discussion of the example above, the vehicle also has an in-vehicle or external controller programmed to communicate with the user input device and / or the vehicle control module to receive a vehicle braking command with a corresponding total braking torque request to decelerate / stop the vehicle. From the total braking torque request, the vehicle controller determines a regenerative braking torque for the regenerative braking system and a friction braking torque for the friction braking system. Using the friction braking torque and an estimated temperature of a rotating friction brake element, the controller can optionally estimate a temperature-dependent coefficient of friction. From the friction braking torque and an estimated surface smoothness state of the friction braking system, the controller estimates a smoothness-dependent coefficient of friction.Using the smoothness-dependent coefficient of friction and, optionally, the temperature-dependent coefficient of smoothness friction, a modified brake pressure coefficient is calculated; from the modified brake pressure coefficient, a modified friction braking torque is derived. The control unit then commands the friction braking system to apply the modified friction braking torque to one or more of the vehicle's road wheels and can simultaneously command the regenerative braking system to apply the regenerative braking torque to the one or more of the vehicle's road wheels.

[0014] For each of the described vehicles, procedures and CRM, determining the friction braking torque for the friction braking system may involve calculating an estimated total vehicle deceleration torque using the requested total braking torque and a drive deceleration torque of the vehicle's drive system, as well as calculating an estimated total vehicle deceleration force using the estimated total vehicle deceleration torque and a predefined radius of the vehicle's road wheels.Determining the friction braking torque may also involve calculating an estimated unprocessed vehicle deceleration using the estimated total vehicle deceleration force and a predefined mass of the vehicle, calculating an expected total vehicle deceleration using the estimated unprocessed deceleration and a road gradient compensation value, and extracting the friction braking torque from the expected total vehicle deceleration.

[0015] In all described vehicles, procedures, and CRMs, estimating the slip-dependent coefficient of friction can respond to the activation of a surface slip resistance learning mode. The surface slip resistance learning mode can be activated in response to the vehicle's current speed exceeding a minimum slip resistance speed threshold, a chassis check mode being inactive, a wheel slip control mode being inactive, and / or a spike braking procedure being inactive. In this case, instructing the friction braking system to apply the modified friction braking torque can occur in response to the activation of the surface slip resistance learning mode. Alternatively, the vehicle's control system can determine whether the braking command is a valid request for brake slip resistance reduction.If the vehicle braking command is not a valid braking request, the vehicle control system can, in response, instruct the friction braking system to apply the unchanged friction braking torque to the vehicle's road wheel(s). Conversely, if the vehicle braking command is a valid braking request, the vehicle control system can instruct the friction braking system to apply the modified friction braking torque.

[0016] For each of the described vehicles, procedures, and CRMs, a vehicle braking command can be considered a valid braking request if: an estimated total deceleration torque of the vehicle is greater than a predefined minimum torque threshold; a percentage of the estimated total deceleration torque of the vehicle applied by the friction braking system is greater than a predefined minimum threshold; and / or a deceleration force value of the vehicle braking command is greater than a predefined minimum force threshold. As a further option, the vehicle control system can respond to the vehicle braking command being a valid braking request by using a vehicle-integrated accelerometer (e.g., a speedometer).The system communicates with an inertial measurement unit (IMU) to obtain acceleration sensor data indicating the current (real-time) vehicle deceleration. The control unit can then estimate maximum and minimum expected vehicle decelerations in conjunction with the total braking torque requirement and determine the current operating state of the friction braking system based on these predicted maximum and minimum decelerations. In this case, the slip-dependent coefficient of friction can be selected from a lookup table based on the current operating state of the friction braking system.

[0017] For each of the described vehicles, procedures, and CRMs, the current operating state of the friction braking system can be described as follows: an underbraking state when the current vehicle deceleration is less than the minimum expected vehicle deceleration; an overbraking state when the current vehicle deceleration is greater than the maximum expected vehicle deceleration; or a rated braking state when the current vehicle deceleration is greater than the minimum expected vehicle deceleration and less than the maximum expected vehicle deceleration.As a further option, the smoothness-dependent coefficient of friction can be modified by a multiplier, which is set to a green smoothness value between 0 and 1 in response to the current operating state of the friction braking system, which is the underbraking state, a track smoothness value between 1 and 2 in response to the current operating state, which is the overbraking state, and a nominal smoothness value of 1 in response to the current operating state, which is the nominal braking state.

[0018] For each of the described vehicles, processes, and CRMs, estimating the smoothness-dependent coefficient of friction can involve calculating a smoothness energy analogue as a function of the vehicle's current speed, a predefined runtime time step, and the friction braking torque of the friction braking system. Another option is to calculate the smoothness work analogue when the estimated temperature of the rotating friction braking element exceeds a predefined minimum smoothness temperature. As a further option, estimating the smoothness-dependent coefficient of friction can involve incrementing a smoothness energy analogue by the smoothness energy analogue and determining the surface smoothness state of the friction braking system based on this smoothness energy analogue.Determining the surface smoothness state of the friction braking system can involve: setting the surface smoothness state to a track surface smoothness state in response to the smoothness energy analogue being greater than a track smoothness energy accumulation threshold; setting the surface smoothness state to a green surface smoothness state in response to the smoothness energy analogue being less than the nominal smoothness energy accumulation threshold; and setting the surface smoothness state to a nominal surface smoothness state in response to the smoothness energy analogue being greater than the nominal smoothness energy accumulation threshold and less than the track smoothness energy accumulation threshold. Fig. Figure 1 is a partially schematic side view of a representative motor vehicle with a friction braking system, a regenerative braking system and a network of in-vehicle controls, sensing devices and communication devices for providing a mixed braking system operation. Fig. Figure 2 is a flowchart representing a representative control protocol for a mixed vehicle braking system for learning and compensating for friction brake wear, which may correspond to non-volatile, memory-stored instructions that may be executed by a stationary or remote microcontroller, central processing unit, control module, programmable logic circuit or other integrated circuit (IC) device or network of circuits / modules / microcontrollers / IC devices (collectively, the “Controller”).

[0019] Referring to the drawings, where identical reference numbers refer to identical features in the different views, it is stated in Fig. Figure 1 shows a representative motor vehicle, generally designated 10, which for discussion purposes is shown here as an electric-powered sedan. The motor vehicle 10 shown—here also referred to simply as the “motor vehicle” or “vehicle”—is merely an exemplary application with which aspects of this description can be put into practice. Likewise, the implementation of the present concepts by a mixed vehicle braking system consisting of an electro-hydraulic disc brake system and an FEV traction motor should be understood as a non-limiting implementation of the disclosed features. It is understood that aspects of this description can be implemented for a variety of different mixed vehicle braking systems and can be incorporated into any logically relevant type of motor vehicle.Furthermore, only selected components of the motor vehicle and the vehicle braking system are shown and described in detail here. Nevertheless, the vehicles and systems described below may include numerous additional and alternative features and other available peripheral hardware for carrying out the various procedures and functions described.

[0020] The representative vehicle 10 of Fig. 1 is originally equipped with a vehicle telecommunications and information unit (“telematics”) 14 that communicates wirelessly, e.g., via a cellular network, satellite service, wireless modem, etc., with a remote cloud computing host service 24 (e.g., ONSTAR®). Some of the other vehicle hardware components 16 that are in Fig. The components shown in Figure 1, which are generally represented, include, as non-limiting examples, an electronic video display device 18, a microphone 28, one or more loudspeakers 30, and various user input controls 32 (e.g., buttons, rotary knobs, pedals, switches, touchpads, touchscreens, etc.). These hardware components 16 function, in part, as a human-machine interface (HMI), enabling the user to communicate with the telematics unit 14 and other components located in and away from the vehicle 10. For example, occupants can input verbal commands via a microphone 28; the vehicle 10 may be equipped with an integrated speech processing unit that uses audio filtering, processing, and analysis modules.Conversely, the loudspeaker 30 provides an acoustic output to a vehicle occupant and can either be a stand-alone loudspeaker for the telematics unit 14 or part of an audio system 22. The audio system 22 is connected to a network interface 34 and an audio bus 20 to receive analog information and reproduce it as sound via one or more loudspeaker components.

[0021] The telematics unit 14 is communicatively coupled to a network interface 34, suitable examples of which include twisted-pair / fiber optic Ethernet switches, parallel / serial communication buses, LAN (Local Area Network) interfaces, CAN (Controller Area Network) interfaces, and the like. The network interface 34 enables the vehicle hardware 16 to send and receive signals to each other and to various systems both on board and outside the vehicle body 12. This allows the vehicle 10 to perform various vehicle functions, such as modulating powertrain performance, activating friction and regenerative braking systems, controlling the vehicle steering, and other automated functions.For example, the telematics unit 14 can receive signals from a powertrain control module (PCM) 52, an ADAS module (Advanced Driver Assistance System) 54, an RBCM module (Regenerative Braking Control Module) 56, an FBCM module (Friction Braking Control Module) 58, an electronic brake control module (EBCM) 60 and various other vehicle ECUs, such as a transmission control module (TCM), an engine control module (ECM), a sensor system interface module (SSIM), a battery control module (BCM), a steering control module (SCM), etc.

[0022] As in Fig. As shown in Figure 1, the telematics unit 14 is an in-vehicle device that provides a range of services both individually and through its communication with other networked devices. This telematics unit 14 can generally consist of one or more processors 40, each of which can be implemented as a discrete microprocessor, an application-specific integrated circuit (ASIC), or a dedicated control module.The vehicle 10 can provide centralized vehicle control via a central processing unit (CPU) 36, which is operationally equipped with a real-time clock (RTC) 42 and one or more electronic storage devices 38, each of which can take the form of a CD-ROM, a magnetic disk, an IC device, a solid-state drive (SSD), a hard disk drive (HDD), a flash memory, a semiconductor memory (e.g., various types of RAM or ROM), etc.

[0023] Long-range communication (LRC) with remote devices outside the vehicle can be provided via one, more, or all of the cellular chipsets / components, navigation and positioning chipsets / components (e.g., GPS transmitters / receivers), or a wireless modem, all of which are shown together in Figure 44. Short-range wireless communication can be provided via an SRC device 46 (e.g., a Bluetooth® unit or an NFC transmitter / receiver), a DSRC component 48, and / or a dual antenna 50. The communication devices described above can provide data exchange as part of a periodic transmission in a vehicle-to-vehicle (V2V) or vehicle-to-everything (V2X) communication system, e.g.,Vehicle-to-infrastructure (V2I), vehicle-to-pedestrian (V2P), vehicle-to-device (V2D), vehicle-to-cloud (V2C), etc.

[0024] The CPU 36 receives sensor data from one or more sensing devices, which may employ, for example, photodetection, radar, laser, ultrasound, optics, infrared, or other suitable technologies, including short-range communication technologies (e.g., DSRC) or ultra-wideband (UWB) radio technologies, to execute an automated driving (AV / ADAS) operation or vehicle navigation service configured by the controller. According to the example shown, the vehicle 10 may be equipped with one or more digital cameras 62, one or more distance sensors 64, one or more vehicle speed sensors 66, one or more vehicle dynamics sensors 68, and the necessary filtering, classification, fusion, and analysis hardware and software for processing raw sensor data.The vehicle speed sensor(s) 66 can be a mechanical or electromagnetic transmission shaft sensor or an electronic wheel speed sensor for detecting vehicle speed. The vehicle dynamics sensor(s) 68 can be a single-axis or three-axis accelerometer, a yaw rate sensor, a tilt sensor, a steering angle sensor, a brake sensor, an inertial measurement unit (IMU), etc., to detect longitudinal and lateral acceleration, yaw, roll and / or pitch rates, steering angle, and other vehicle dynamics parameters. The type, arrangement, number, and interoperability of the distributed array of onboard sensors can be configured individually or collectively for a specific vehicle platform to achieve the desired level of automated vehicle operation.

[0025] To propel the motor vehicle 10, an electrified powertrain is provided to generate a tractive torque and deliver it to one or more of the vehicle's drive wheels 26. The powertrain is arranged in Fig. 1 represented by a rechargeable energy storage system (RESS), which may be in the form of a chassis-mounted traction battery pack 70 equipped with an electric traction motor (M) 78. The traction battery pack 70 generally consists of one or more battery modules 72, each containing a bundle of battery cells 74, such as lithium, zinc, nickel, or organosilicon cells of the pouch, can, or cylindrical type. One or more electric machines, such as traction motor / generator (M) units 78, draw electrical energy from the battery pack 70 and optionally supply electrical energy to it. A power inverter module (PIM) 80 electrically connects the battery pack 70 to the motor(s) 78 and modulates the transfer of electrical current between them. The battery pack 70 may include an integrated electronics package, such asa wireless cell monitoring unit (CMU) 76, which enables in-module management, cell scanning, etc.

[0026] The following discusses systems and methods for blending deceleration torques with a brake burn-in procedure where the energy accumulation / discharge of the friction brakes is actively monitored to derive a burn-in state for the friction brake component of a mixed vehicle braking system (e.g., Green Burnish, Street Burnish, Track Burnish, etc.). For example, a corresponding torque request and expected vehicle deceleration can be derived from a driver's braking command and compared with an actual vehicle deceleration measured by the vehicle's accelerometers. An expected smoothing state of the friction brake system is output by an energy accumulation model and compared with a predicted deceleration delta to confirm that the current smoothing state is directionally correct.Once this is confirmed, the brake system's control protocol adjusts the friction coefficient calibrations of the friction brake hardware to compensate for the surface smoothness condition. In this way, the vehicle's EBCM can reduce the likelihood of the mixed braking system delivering excessive deceleration (overbraking) or insufficient deceleration (underbraking) compared to a braking request commanded by the driver or ADAS.

[0027] The calibration values ​​for the brake friction coefficients and the corresponding compensation values ​​for the brake friction coefficients can be derived using virtual data for brake coloring, test bench data, data from vehicle testing on the racetrack, and data from road traffic. The coefficient calibrations can be adjusted for suitable operating temperatures, clamping forces, the time required for friction brake break-in, and corresponding values ​​before and after hardware break-in. fThe brake smoothing model can be implemented as part of a closed-loop control protocol that can be updated using data acquired from the vehicle. Inaccuracies in the input data, such as real-time deceleration from the IMU, state estimation from wheel / vehicle speeds and accelerations, and the brake rotor temperature model, can alter the brake smoothing model. Plausibility checks and calibration limits can be implemented to prevent the brake wear model from negatively impacting braking performance or misdirecting the response of the friction braking system.

[0028] Referring to the flowchart of Fig. 2 will be an improved method or control protocol for learning and compensating for friction brake wear for a braking system, such as the mixed vehicle braking system 102 of Fig. 2, of a motor vehicle, such as the electrically powered motor vehicle 10 of Fig. 1, generally described under 100 according to the aspects of the present description. Some or all of the in Fig. The processes shown in 2 and described in more detail below can represent an algorithm corresponding to non-volatile, processor-executable instructions stored, for example, in main or auxiliary memory or remote memory (e.g., in the vehicle's onboard storage device(s) 38 and / or the remote cloud computing service database 24). Fig. 1) are stored. These instructions can be, for example, stored by a microcontroller, a processor unit, a programmable logic circuit, a dedicated control module, or another module or device or network of controllers / modules / devices (e.g., vehicle CPU 36 and / or cloud host service 24 BO server-class computer of Fig. 1) to execute one or all of the functions described above and below that are related to the disclosed concepts. It should be acknowledged that the order of execution of the presented operating blocks can be changed, additional operating blocks can be added, and some of the operations described here can be modified, combined, or eliminated.

[0029] Procedure 100 can be connected to the START terminal block 101 of Fig. 2. Starting with stored, processor-executable instructions to initialize a closed-loop deceleration torque mixing protocol, the deceleration (reduction) contributions of a segment of the regenerative braking system 104 and a segment of the friction braking system 106 of the vehicle braking system 102 are modulated. This routine can be executed in real time, near real time, continuously, systematically, sporadically, and / or at predefined time intervals, e.g., every 10 or 100 milliseconds, while the vehicle 10 is in operation. Fig. 1. As another option, terminal block 101 can be initialized in response to a user command request (e.g., via the telematics input controls 14), a request from the resident vehicle control (e.g., from the CPU 36), or a broadcast request signal received from a centralized back-office (BO) vehicle service system (e.g., from the cloud host service 24). As a non-restrictive example, procedure 100 can be automatically initialized when a driver of the motor vehicle 10 applies a vehicle-specific brake pedal or when the ADAS module 54 issues a deceleration request, e.g., as part of an automated vehicle response during adaptive cruise control (ACC) or advanced collision avoidance (ACA). Upon completion of some or all of the steps described in Fig. In the two control processes shown, procedure 100 can continue to the END terminal block 129 and be temporarily terminated, or optionally return to terminal block 101 and run in a continuous loop.

[0030] Continuing from terminal block 101 to process block 103 for BRAKE COMMAND, procedure 100 can receive a vehicle braking command from a user input device or a vehicle control module to decelerate or stop the host vehicle. According to a non-restrictive example, a driver releases an accelerator pedal or applies a brake pedal to input a deceleration command for the vehicle. This deceleration control command may be accompanied or replaced by a speed change control command issued by a resident vehicle control unit, such as the ADAS module 54 of Fig. 1. After receiving the aforementioned vehicle control command(s) entered by the driver, commands executed by the controller can cause the EBCM 60 to, for example, identify a brake torque request from the vehicle-calibrated deceleration response table that corresponds to the speed change command entered by the driver and any accompanying speed change commands generated by the controller (e.g., a total brake torque request of 1000 Newton meters (Nm)). This acceleration table may contain an acceleration map file stored in memory and accessible to the controller, which represents a sequence of vehicle speeds and vehicle acceleration / deceleration values ​​with a corresponding sequence of positive / negative torque outputs.

[0031] The process 100 runs with the process block 105 REGEN TORQUE CAPACITY from Fig. 2 continues and determines a regenerative braking torque applied by the regenerative braking system 104 to achieve the total requested braking torque associated with the vehicle braking command received in process block 103. The regenerative braking torque capacity can be defined as the maximum available braking torque achievable by the host vehicle's powertrain actuator(s) under the vehicle's current operating conditions and the associated powertrain hardware limitations. As an example, and without limitation, the maximum available regenerative braking torque capacity can indicate the total regenerative braking torque that can be generated by the entire powertrain system at the time of a desired vehicle braking (e.g., a regenerative braking torque of 400 Nm). After determination, the vehicle's control system, e.g.,the EBCM 60, instructs the RBCM 56 to control the regeneration brake system 104 so that the regeneration brake torque is transferred to one or more road wheels of the vehicle to decelerate the vehicle as specified in process block 107 REGEN TORQUE APPLY.

[0032] In conjunction with process block 105, procedure 100 can execute process block 109 FRICTION TORQUE CAPACITY and simultaneously determine a friction braking torque applied by the friction braking system 106 to meet the total braking torque requirement associated with the vehicle braking command received in process block 103. The friction braking torque capacity can be derived by first calculating an estimated total vehicle deceleration torque (Nm) experienced by the host vehicle, e.g., as the mathematical sum of the total braking torque requirement determined in process block 103 and a total drive deceleration torque caused by the vehicle's drive system (e.g., predicted drivetrain resistance, predicted motor resistance, predicted transmission resistance, etc.).An estimated total vehicle deceleration force (N) can be calculated by mathematically dividing the estimated total vehicle deceleration torque by a radius of one or more of the host vehicle's road wheels, estimated by the manufacturer or the controller. An estimated unprocessed vehicle deceleration can then be calculated by mathematically dividing the estimated total vehicle deceleration force by a mass of the host vehicle, also estimated by the manufacturer or the controller. The estimated unprocessed vehicle deceleration can be mathematically subtracted from a road gradient compensation value to calculate an expected total vehicle deceleration. The friction braking torque capacity of process block 109 can be extracted from the expected total vehicle deceleration by accessing a special lookup table that maps the vehicle deceleration values ​​to their respective friction braking torque values.

[0033] With further reference to Fig. 2. The procedure 100 can proceed to process block 111 FRICTION BRAKE TEMP to estimate an operating temperature of a rotating friction brake element (e.g., brake drum or disc brake rotor) of the friction brake system 106. In a representative use case, a predefined thermal model can combine thermal models of rotor / drum wear, fatigue, driver load, etc., to estimate a current operating temperature of a brake rotor / drum of the friction brake system 106. This estimate can be based on the established physics of a brake lining being pressed against the rotor / drum by a hydraulic, pneumatic, or electromechanical actuator, as well as any associated core system constraints, such as ambient air temperature, current / initial estimate of the rotor / drum temperature (e.g.,(when switched on), thermal mass of the rotor / drum, specific heat capacity of the rotor / drum, coefficient of friction, torque, calibratable heating and cooling coefficients, etc.

[0034] In the TEMP FRICTION COEFFICIENT process block 113 of Fig. 2. Method 100 uses the torque of the friction brake output by process block 109 and the estimated operating temperature of the rotor / drum of the friction brake output by process block 111 to calculate a temperature-dependent coefficient of friction (C). ft ) to derive. Again, referring to the non-restrictive example of Fig. 1. The EBCM 60 can access a resident memory device 38 to retrieve a special lookup table (e.g., Table 1 below) that maps a range of rotor / drum temperature values ​​to corresponding coefficients of friction; the temperature-dependent coefficient of friction is extracted from this lookup table using the estimated temperature. Since the rotor / drum temperature typically changes much faster than the brake lining, the expected effect of the rotor / drum temperature usually occurs more quickly and over a shorter period. The balancing or weighting of the temperature-dependent and smoothness-dependent coefficients of friction compensators can be set during the calibration of the mixed brake system 102. The top row of Table 1 lists examples of estimated brake rotor temperatures, and the bottom row lists the respective coefficients of friction corresponding to the estimated temperatures. Table 1: Example of the temperature model outputs -200 -100 0 100 300 500 800 1200 1500 4.01 5.01 5.90 6.56 6.90 7.25 7.97 9.16 11.00

[0035] Before, concurrently with, or after performing a thermal learning model to derive a thermally based compensator, Procedure 100 performs a surface smoothness learning model to estimate a current surface smoothness state of the friction brake hardware and simultaneously adjust the coefficient of friction value used to internally convert an intended braking request into a friction brake clamping pressure / friction force. The illustrated smoothing learning model can begin with Decision Block 115, "VALID BRAKE APPLY," to determine whether a given vehicle braking command is considered a valid braking request (e.g., to verify that the braking request is suitable for smoothing purposes). A vehicle braking command can be classified as "valid" if: (1) an estimated total deceleration torque of the vehicle associated with the requested braking command exceeds a predefined minimum drag torque threshold (e.g. request for a total braking torque ≥ 850 Nm); (2) a percentage of the estimated total vehicle deceleration torque applied by the friction braking system to execute the requested braking command exceeds a predefined threshold for the minimum percentage of friction (e.g. percentage of applied friction braking ≥ 60%); and / or (3) a deceleration force associated with the requested braking command exceeds a predefined threshold for the minimum force (e.g. ≥ 0.2 G).

[0036] If it is determined that the vehicle braking command in question is not a valid braking request (Block 115=NO), the procedure 100 can, in response, exit the slipperiness learning model and instruct the FBCM 58 to control the friction braking system 106 to apply the unchanged friction braking torque to one or more of the vehicle's road wheels to decelerate the host vehicle, as specified in the FRICTION TORQUE APPLY process block 127. The FRICTION TORQUE APPLY process block 127 is designed to be executed substantially concurrently with the REGEN TORQUE APPLY process block 107.

[0037] If the vehicle braking command is determined to be a valid braking request (Block 115 = YES), Procedure 100 can proceed with the model learning smoothing and execute the actuator comparison check process (Block 117), evaluating the vehicle's available fast actuators that can be used to execute a commanded vehicle braking operation. In this example, EBCM 60 can implement feedback and forward inputs to match one or more powertrain "fast" actuators (e.g., engine friction, engine brake, transmission brake, etc.) with one or more friction brake actuators (e.g.,

[0038] Disc brake, drum brake, etc.) and optionally synchronize with one or more other vehicle actuators (e.g., active aviation equipment) to achieve a desired final braking torque. A final, modified friction braking torque can be calculated, for example, based on a commanded braking torque and a system regeneration capacity limited by the capacity limits of the drive actuators (e.g., battery power limits, motor / axle torque limits, etc.).

[0039] In conjunction with process block 117, procedure 100 can execute process block 119 BURNISH LEARNING MODEL to determine a surface smoothness state of the friction braking system 106 using an energy accumulation evaluation; this surface smoothness state is used to derive a compensation value for modifying the commanded output of the friction braking system 106. Procedure 100 can first determine whether or not to activate the model for learning the smoothing process. According to a non-restrictive example, the learning mode for the smoothing process can be activated in response to a finding that: (1) the current vehicle speed of the host vehicle exceeds a predefined minimum grinding speed threshold (e.g., the wheel speed sensor data indicates a real-time vehicle speed ≥ 35 mph); (2) A chassis test mode that can disable parts of the chassis control system, the autonomous vehicle (AV) system and some or all other ADAS systems when active is not currently active; (3) a wheel slip control mode (e.g. electronic stability control (ESC)) is currently inactive; and / or (4) A panic braking mode that can automatically activate the vehicle's anti-lock braking system (ABS) when the brake pedal is applied in a panic is not currently active.

[0040] Responding to the detection that the model for learning smoothing is disabled, procedure 100 can terminate the model for learning smoothing.

[0041] Once it has been determined that the slipperiness learning model is activated and the vehicle braking command is a valid slipperiness operation, the Procedure 100 can determine the current state of a friction brake (“Deceleration Delta Checker”) to ensure that the vehicle responds as expected with a modified friction braking torque. For example, the EBCM 60 can communicate via the SSIM with a vehicle-integrated accelerometer (e.g., a 3- or 6-DoF IMU module) to receive acceleration sensor data indicating the current (real-time) vehicle deceleration of the host vehicle. Simultaneously, the EBCM 60 can access a stored, vehicle-calibrated lookup table to retrieve a maximum expected vehicle deceleration and a minimum expected vehicle deceleration in conjunction with the modified braking torque request.

[0042] The current operating state of the friction braking system can be derived by comparing the vehicle's real-time deceleration value with the predicted maximum and minimum vehicle decelerations, for example, to determine whether it falls within a predetermined acceptable range. In this example, the current operating state of the friction braking system 106 ("Friction Braking State") can be reported as "Underbraking State"—less deceleration than expected—if the vehicle's current deceleration value is less than the minimum expected vehicle deceleration (for example, if "Underbraking State" is set to TRUE). Conversely, the current friction braking state can be reported as "Overbraking State"—more deceleration than expected—if the vehicle's current deceleration value is greater than the maximum expected vehicle deceleration (for example, by setting the Overbraking State to TRUE).On the other hand, the current friction braking condition can be reported as the "nominal braking condition" - within the range of expected deceleration - if the current deceleration value of the host vehicle is greater than the minimum expected vehicle deceleration and less than the maximum expected vehicle deceleration (e.g., setting the NOMINAL braking condition to TRUE).

[0043] Assessing the current state of the friction braking system helps determine whether the resulting total braking torque is greater or less than expected. The Deceleration Delta Checker can, in fact, act as a failsafe against the energy accumulation model, ensuring its correctness by preventing the algorithm from compensating for the coefficient value in the wrong direction (i.e., adding deceleration to an overbraking condition or subtracting deceleration from an underbraking condition). This safeguard helps the system compensate for the friction coefficient value correctly, improving an under- or overbraking situation by displaying a brake deceleration delta and reporting whether the total vehicle braking torque is too high or too low.The deceleration delta checker can also be used to accelerate or decelerate the learning and compensation of the energy accumulation model, if the direction is correct, e.g., proportionally to the difference between the actual deceleration and the expected deceleration. The state of smoothing can be implemented as a smoothness category, e.g., broken down and defined as described above, and can be implemented as a numerical value that is used as a multiplier against the static singular (traditional) coefficient of friction.

[0044] In BURNISH FRICTION COEFFICIENT process block 121 of Fig. 2. Method 100 estimates a smoothness-dependent coefficient of friction (C). fb) using the friction braking torque output in process block 109 and the estimated surface smoothness state of the friction braking system output in process block 119. To determine the smoothness-dependent coefficient of friction, procedure 100 can first determine whether or not to accumulate or decimalize an analog energy counter (smoothness counter). To accumulate the energy analog, a smoothness energy analog can be calculated in response to the following: (1) the smoothness learning model is activated; (2) the base vehicle's propulsion system is active; (3) the estimated temperature of the rotating friction brake element exceeds a predefined minimum burnish rotor temperature (“Burnish Rotor Temperature Achieved”); and (4) the vehicle brake command is a valid brake application (“Valid Brake Apply TRUE”).If these conditional statements are true, a smoothness-dependent coefficient of friction can be derived by calculating a smoothness energy analogue as a function of the current (real-time) vehicle speed of the host vehicle, a predefined runtime time step (e.g., 5.0 milliseconds (ms)), and the friction braking torque of the friction braking system; i.e., energy analogue = speed * time * friction braking torque. Procedure 100 can then report the calculated friction brake energy analogue and increment the grinding wheel energy analogue counter by the grinding wheel energy analogue. The system can accumulate the energy analogue value—representative of all the energy accumulated and converted by the friction braking system—over a predetermined number of valid brake actuations (e.g., 50 valid actuations).The system can also prohibit a negative energy analog value or "limit" the energy analog value as a protective measure to prevent the software from causing an error by accidentally exceeding the minimum or maximum limits of a signal declared in the CRM. If any of the conditional statements are false, the system can lower the energy analog value accordingly.

[0045] After incrementing or decrementing the smoothness counter, procedure 100 can set the surface smoothness state of the friction braking system to a track smoothness state that responds when the smoothness energy analog reading exceeds a preset track smoothness energy accumulation threshold ("Track Smoothing Active TRUE"). Conversely, the surface smoothness state can be set to a green surface smoothness state when the smoothness energy analog reading is below the smoothness energy accumulation threshold ("GREEN Surface Smoothness Active TRUE"). If the smoothness energy analog reading is approximately equal to or less than the track smoothness energy accumulation threshold, the surface smoothness state can be set to a nominal surface smoothness state ("NOMINAL Smoothing Active TRUE").As shown in Table 2, the smoothness-dependent coefficient of friction can be modified by a multiplier set to the following values: (1) a green smoothness value between 0 and 1 if the current operating state of the friction braking system is a green / underbraking state; (2) a track smoothness value between 1 and 2 if the current operating state of the friction braking system is a track / overbraking state; or (3) a nominal smoothness value of 1 if the current operating state is a nominal braking state. The top row of Table 2 lists the current surface smoothness state of the friction braking system, the middle row the surface smoothness state multiplier for each surface smoothness state, and the bottom row the corresponding smoothness-dependent coefficients of friction. Table 2: Example of Burnish Model Outputs GRÜN NOMINAL TRACK 0.80 0.85 0.90 0.95 1 1.05 1.10 1.15 1.20 10.81 13.52 15.90 17.70 18.6 19.50 21.50 24.70 29.65

[0046] The analog energy meter can function as an energy accumulation mechanism, quantifying the energy input into the friction brake hardware for processing purposes. The analog energy meter measures in Nm. 2The energy that can be measured can be compared to a "leaking bucket" that increases during valid friction braking (valid braking is used based on optimal rotor temperatures for smoothing), minimum pad clamping force (sufficient pressure to allow the transfer of pad material to the rotor (smoothing)), and continuous contact between pad and rotor (no ABS, ESC, etc.). As brake pad friction increases, the energy count rises accordingly. When the analog energy counter exceeds a calibratable threshold for green / road / track brake pad enumeration, a corresponding Boolean status for burn-in is set. At any time when the analog energy counter is not increasing, the counter may decrease by a small, calibratable amount to account for the gradual burn-in that naturally occurs over time.

[0047] To ensure that the energy accumulation model exhibits directional behavior, a cross-check of the lug-in behavior can be performed. If a green surface smoothness state is active and an overbraking condition is not active, procedure 100 can set a "Green Surface Smoothness State TRUE" flag and report this; conversely, procedure 100 can set a "Green Surface Smoothness State FALSE" flag if a green surface smoothness state is active and an overbraking condition is active. On the other hand, if a track smoothness state is active and an underbraking condition is not active, procedure 100 can set a "Track Smoothness TRUE" flag; if a track smoothness state is active and an underbraking condition is active, procedure 100 can set a "Track Smoothness FALSE" flag. Otherwise, procedure 100 can set and report a "Nominal smoothing TRUE" indicator.

[0048] An adaptive update process for the smoothing learning rate can be performed to adjust ("learn") the smoothing energy accumulation thresholds to compensate for repeated over- / undercompensation of the friction braking torque. For example, if an underbraking condition is marked as active for a predefined number of previous brake applications, and a green surface smoothness condition is not active for those applications (e.g., NO-GREEN-UNDER application count ≥ 50), procedure 100 can increase the green smoothness threshold. Similarly, if an overbraking condition is marked as active for a predefined number of previous brake applications, and track coloring is not active for those applications (e.g., NO-TRACK-OVER apply count ≥ 50), procedure 100 can decrease the track coloring threshold.

[0049] Using the temperature-dependent coefficient of friction (C) output by process block 113 ft ) and the smoothness-dependent coefficient of friction (C) output by process block 121 fb ) the procedure 100 can execute process block 123 MODIFIED CLAMP FORCE and a modified brake pressure coefficient (C pm ) determine and from this modified value determine a clamping force for the friction brake system 106. In a disc brake system, the braking force F b between the brake pads and the rotor a function of a tangential frictional force F n , which are known as F b= 2 × µ × F, where µ is the coefficient of friction between the pad and the disc. The clamping force of a brake caliper can be calculated as brake line pressure multiplied by the total piston area of ​​the caliper. In process block 125 BRAKE PRESSURE EVAL, procedure 100 can verify that the modified brake pressure coefficient is within the system-calibrated maximum and minimum pressure limits. Afterward, procedure 100 can complete the smoothing learning model and instruct FBCM 58 to control the friction brake system 106 so that the modified friction brake torque is applied to one or more of the vehicle's road wheels to decelerate the vehicle, as specified in process block 127 FRICTION TORQUE APPLY.

[0050] Aspects of this description can, in some embodiments, be implemented by a computer-executable program of instructions, such as program modules, commonly referred to as software applications or application programs, and executed by any controller or the controller variants described herein. Software can, in non-limiting examples, include routines, programs, objects, components, and data structures that perform specific tasks or implement specific types of data. The software can provide an interface that enables the computer to respond according to an input source. The software can also work in conjunction with other code segments to initiate a variety of tasks in response to received data, in conjunction with the source of the received data. The software can be stored on a variety of storage media, such as CD-ROM, magnetic disk, and semiconductor memory (e.g.,different types of RAM or ROM) are stored.

[0051] Furthermore, aspects of this description can be practiced with a wide variety of computer system and computer network configurations, including multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframes, and the like. Additionally, aspects of this description can be applied in distributed computing environments where tasks are performed by stationary and remote devices connected via a communication network. In a distributed computing environment, program modules can reside in both local and remote computer storage media, including storage devices. Therefore, aspects of this description can be implemented in conjunction with various hardware, software, or a combination thereof in a computer system or other processing system.

[0052] Each of the methods described herein can provide machine-readable instructions for execution by: (a) a processor, (b) a controller, and / or (c) any other suitable device. Each algorithm, software, control logic, protocol, or method disclosed herein can be embodied as software stored on a tangible medium, such as flash memory, solid-state drive (SSD), hard disk drive (HDD), CD-ROM, digital versatile disk (DVD), or other storage devices. Alternatively, the entire algorithm, control logic, protocol, or method, and / or portions thereof, can be executed by a device other than a controller and / or be embodied in firmware or dedicated hardware in an available manner (e.g.,implemented by an application-specific integrated circuit (ASIC), a programmable logic device (PLD), a field-programmable logic device (FPLD), discrete logic, etc.). Although specific algorithms are described with reference to the flowcharts and / or workflow diagrams presented here, many other methods can alternatively be used to implement the exemplary machine-readable instructions.

Claims

[1] Method (100) for operating a motor vehicle (10) with a mixed braking system (102), wherein the mixed braking system (102) comprises a regenerative braking system (104) and a friction braking system (106) designed to decelerate one or more road wheels (26) of the motor vehicle (10), wherein the method (100) comprises: Receiving a vehicle braking command with a total braking torque request for the motor vehicle (10) by a vehicle control unit from a user input device (32) or a vehicle control module; Determining a regeneration braking torque for the regenerative braking system (104) and a friction braking torque for the friction braking system (106) by the vehicle control using the total braking torque request; Estimating a smoothness-dependent coefficient of friction by the vehicle control system based on the friction braking torque and an estimated surface smoothness state of the friction braking system (106); Determining a modified brake pressure coefficient by the vehicle control system using the smoothness-dependent coefficient of friction; Determining a modified friction braking torque using the modified brake pressure coefficient; and Instructing the friction braking system (106) by the vehicle control unit to apply the modified friction braking torque to one or more road wheels (26) of the motor vehicle (10); characterized by , that the procedure (100) further includes: Determine whether the vehicle braking command is a valid braking request; wherein the vehicle braking command is determined to be a valid braking request if an estimated total vehicle deceleration torque is greater than a predefined minimum threshold torque, if the percentage of friction braking in the estimated total vehicle deceleration torque applied by the friction braking system (106) is greater than a predefined minimum threshold fraction and / or if a deceleration force magnitude of the vehicle braking command is greater than a predefined minimum threshold force magnitude; wherein the instruction to the friction braking system (106) to apply the modified friction braking torque responds to the vehicle braking command, which is the valid braking request; and Instructing the friction braking system (106) by the vehicle control to apply the friction braking torque to one or more road wheels (26) of the motor vehicle (10) when the vehicle braking command is not the valid braking request. [2] Method (100) according to claim 1, wherein determining the friction braking torque for the friction braking system (106) comprises: Calculating an estimated total vehicle deceleration torque using the total braking torque requirement and a drive deceleration torque of a motor vehicle drive system (10); and Calculating an estimated total vehicle deceleration force using the estimated total vehicle deceleration torque and a predefined radius of one or more road wheels (26). [3] Method (100) according to claim 2, wherein determining the friction braking torque for the friction braking system (106) further comprises: Calculating an estimated unprocessed vehicle deceleration using the estimated total vehicle deceleration force and a predefined mass of the motor vehicle (10); Calculating an expected total vehicle deceleration using the estimated unprocessed vehicle deceleration and a compensation value for road gradient; and Extracting the friction braking torque from the expected total vehicle deceleration. [4] Method (100) according to claim 1, wherein the estimation of the smoothness-dependent coefficient of friction responds to the activation of a smoothness learning mode, wherein the smoothness learning mode is activated in response to a current vehicle speed of the motor vehicle (10) that exceeds a threshold minimum speed. [5] Method (100) according to claim 1, further comprising: Receiving acceleration sensor data indicating the current vehicle deceleration of the motor vehicle (10) via the vehicle control system from an acceleration sensor of the motor vehicle (10) in response to the vehicle braking command, which is the valid braking request; Estimating the maximum and minimum expected vehicle decelerations associated with the total braking torque requirement of the vehicle braking command; and Determining a current operating state of the friction braking system (106) based on the maximum and minimum expected vehicle decelerations, wherein the slip-dependent coefficient of friction is selected from a lookup table based on the current operating state of the friction braking system (106). [6] Method (100) according to claim 5, wherein the current operating state of the friction brake system (106) is determined: A state of under-braking occurs when the actual vehicle deceleration is less than the minimum expected vehicle deceleration; An overbraking condition occurs when the current vehicle deceleration is greater than the expected maximum vehicle deceleration; and A nominal braking condition is present when the actual vehicle deceleration is greater than the minimum expected vehicle deceleration and less than the maximum expected vehicle deceleration. [7] Method (100) according to claim 6, wherein the smoothness-dependent coefficient of friction is modified by a multiplier which is set to a green smoothness value between 0 and 1 in response to the current operating state of the friction brake system (106), which is the underbraking state, a track smoothness value between 1 and 2 in response to the current operating state of the friction brake system (106), which is the overbraking state, and a nominal smoothness value of 1 in response to the current operating state, which is the nominal braking state. [8] Method (100) according to claim 1, wherein the estimation of the smoothness-dependent coefficient of friction comprises the calculation of a smoothness energy analogue as a function of a current vehicle speed of the motor vehicle (10), a predefined run-time time step and the friction braking torque of the friction braking system (106).

Images