Method for operating a motor vehicle with a decentralized braking system

Abstract

A method for operating a vehicle includes receiving brake sensor data indicating the measured actuator outputs of the brake actuators of a decentralized braking system. For each brake actuator, a vehicle controller calculates: a normalized corner output using the measured actuator output and a commanded target output for that brake actuator, and a weighted average using the normalized corner output of that brake actuator and a vehicle-calibrated weight value determined from the vehicle's current speed and steering angle.The control unit calculates a percentage actuator error as the absolute value of a mathematical difference between the weighted averages of the brake actuators and detects an actuator error when the percentage actuator error exceeds a vehicle-calibrated error deviation threshold, which is determined from the vehicle's current speed and steering angle. In response to the error percentage exceeding the error deviation threshold, the control unit commands the braking system to execute a braking action to correct the actuator error.

Description

[0001] This description refers generally to braking systems for motor vehicles. More specifically, aspects of this description relate to motor vehicles with adaptive decentralized braking systems.

[0002] Today's production vehicles, such as modern automobiles, are originally equipped with a powertrain that propels the vehicle and supplies 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, corner modules, wheels, etc.) via an automatic or manual transmission. In the past, motor vehicles were powered by internal combustion engines (ICEs) because these were readily available, relatively inexpensive, lightweight, and highly efficient. These engines include compression-ignition (CI) diesel engines, spark-ignition (SI) gasoline engines, two-, four-, and six-stroke engines, and rotary engines, to name just a few.Hybrid electric and fully electric vehicles (collectively referred to as "electrically powered vehicles"), on the other hand, use alternative energy sources to power the vehicle, thus minimizing or eliminating dependence on a fossil fuel-based engine for traction.

[0003] Motor vehicles are generally equipped with a hydraulic, pneumatic, or electromechanical braking system, which is operated by the driver or the vehicle's control unit to selectively slow down and ultimately stop the vehicle during everyday use. The most common type of braking system 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 contact with a rotating brake caliper or drum (the "rotating brake element"). In this way, the friction braking system converts the vehicle's kinetic energy into heat energy from the frictionally interlocking rotating and friction-locking brake elements to slow down / stop the rotation of the corresponding wheel assembly.Some motor vehicles today use a decentralized ("brake-by-wire") braking system, in which a single motor-driven actuator is installed in each wheel assembly and a central control unit individually controls the actuators to generate the desired braking force at that wheel.

[0004] DE 100 15 225 A1 relates to a method for determining a consolidated input variable for a vehicle control system from at least two redundantly recorded variables, which has a high level of fault tolerance.

[0005] DE 10 2017 116 196 A1 describes methods and systems for detecting faults in a sensor and for reconstructing an output signal without using the faulty sensor.

[0006] It can be considered an objective to provide a method for operating a motor vehicle with a decentralized braking system in which system errors in the braking system can be detected heuristically. This objective is achieved by the subject matter of claim 1.

[0007] The following section presents intelligent brake control systems with associated control logic that provide corner performance monitoring of a brake actuator output for decentralized vehicle braking systems, methods for manufacturing and operating such brake control systems, and motor vehicles equipped with such brake control systems. A representative example introduces an intelligent brake control system and a method for the heuristic detection of system faults in a decentralized brake-by-wire (BBW) system before an undesired longitudinal or lateral vehicle event occurs. Brake system fault detection can be achieved by comparing deviations between the detected brake actuator responses and the commanded target actuator outputs from higher-level controllers for each individual brake actuator.Upon detection of a fault, the system and procedure can, in response, identify and initiate an appropriate remedy for the fault within the braking system in order to maintain proper brake distribution and thus stable vehicle operation.

[0008] Using feedback control, the vehicle's brake control system can provide a reliable mechanism for detecting a decentralized brake actuator that is not delivering the braking torque commanded by the controller. To identify an actuator exhibiting "malfunction," the system can monitor each individual brake corner to assess its impact on longitudinal and lateral dynamic behavior during braking. This detection mechanism can help identify the actuator(s) that have the greatest influence on a potentially hazardous driving scenario. To maximize the detection range, the faulty brake actuator detection mechanism can be designed to use unitless, normalized corner actuator outputs.In this way, the corner monitoring mechanism can remain active during heterogeneous braking events, including the activity of the anti-lock braking system (ABS), electronic stability control (ESC), adaptive cruise control (ACC), etc., where the commanded target forces or pressures may differ between the individual corner actuators. The presented corner behavior monitoring methods can be applied to any four-wheeled vehicle using decentralized brake-by-wire actuators, including those employing a mix of electromechanical and electrohydraulic brake actuators, as well as to vehicles using regenerative braking and those offering autonomous vehicles (AVs) and advanced driver assistance systems (ADAS) as braking maneuvers.

[0009] Aspects of this description relate to intelligent brake control systems, stored vehicle control protocols, and vehicle control logic for providing corner performance monitoring of the brake actuator output for decentralized vehicle braking systems.

[0010] The inventive method for operating a motor vehicle with a vehicle body, several road wheels attached to the vehicle body, and a decentralized braking system with several brake actuators, each of which can be actuated to brake one of the road wheels, comprises the following: receiving sensor data indicating a measured actuator output of each of the brake actuators from each of several sensors that are operationally attached to the brake actuators; calculating, via a vehicle control system for each of the brake actuators, a normalized corner output using the measured actuator output and a respective commanded target actuator output for the brake actuator;wherein the multiple brake actuators comprise front-left (FL), front-right (FR), rear-left (RL) and rear-right (RR) brake actuators, and wherein calculating the normalized corner output comprises calculating normalized FL, FR, RL and RR corner outputs for the FL, FR, RL and RR brake actuators respectively; wherein receiving the sensor data indicating the measured actuator outputs comprises receiving a force feedback value and a pressure feedback value for each of the FL, FR, RL and RR brake actuators, and wherein calculating the normalized corner output further comprises receiving a target force value and a target pressure value for each of the FL, FR, RL and RR brake actuators;Calculate, via vehicle control, for each of the brake actuators, a weighted average using the normalized corner output of the brake actuator and a vehicle-calibrated weight value determined from a current vehicle speed and / or a current vehicle steering angle; calculate, via vehicle control, an actuator error percentage as an absolute value of a mathematical difference between the weighted averages of the brake actuators; detect, via vehicle control, an actuator error if the actuator error percentage is greater than a vehicle-calibrated error deviation threshold determined from the current vehicle speed and / or the current vehicle steering angle;and instructing the decentralized braking system, a vehicle steering system and / or a vehicle powertrain system via the vehicle control system, in response to the determination that the actuator failure percentage is greater than the vehicle-calibrated failure deviation threshold, to perform a vehicle-calibrated action to correct the actuator failure.

[0011] According to one embodiment, the method comprises, in any order and in any combination with any of the options and features disclosed above and below: receiving, e.g., via a resident or remote microcontroller, a control module, a programmable logic device, or a network of controllers / modules / devices (collectively, "controller"), from multiple brake torque sensors operationally mounted on the brake actuators, sensor data indicating measured actuator outputs of the brake actuators; calculating, e.g., via the vehicle controller, for each brake actuator, a normalized corner output using the measured actuator output and a commanded target output for that brake actuator; calculating, e.g.,via the vehicle control system for each brake actuator to calculate an overall system average, left / right lateral averages and / or front / rear longitudinal averages, a weighted average using the normalized corner output of that brake actuator and a vehicle-calibrated weight value retrieved from a lookup table stored in memory based on the current speed and / or steering angle of the vehicle; calculating, e.g., via the vehicle control system, an actuator (lateral, longitudinal, overall system) error percentage as an absolute value of a mathematical difference between the weighted averages of the brake actuators; detecting, e.g.,via the vehicle control system, of an actuator fault, when the actuator fault percentage exceeds a vehicle-calibrated fault deviation threshold, retrieved from a lookup table stored in memory based on the vehicle's current speed and / or steering angle; and instructing, e.g., via the vehicle control system responding to the determination that the actuator fault percentage exceeds the vehicle-calibrated fault deviation threshold, that the decentralized braking system, the vehicle steering system, and / or the vehicle powertrain perform a vehicle-calibrated action to compensate for or otherwise correct the actuator fault.

[0012] As an application of the method according to the invention, computer-readable media (CRM) are provided that contain instructions for the controller to monitor and adjust the brake actuation performance for decentralized vehicle braking systems. In one example, a non-transient CRM stores instructions that can be executed by one or more processors of a motor vehicle controller. The motor vehicle has multiple wheels and a decentralized braking system with multiple brake actuators, each capable of braking one of the wheels. When executed by the processor(s), the CRM-stored instructions cause the vehicle controller to perform operations, including: receiving sensor data indicating a measured actuator output from each of the brake actuators, from each of several sensors operationally mounted on the brake actuators;Calculate a normalized corner output for each of the brake actuators using the measured actuator output and a respective commanded target actuator output for the brake actuator; determine a vehicle-calibrated weight value from a current vehicle speed and / or a current vehicle steering angle; calculate a weighted average for each of the brake actuators using the normalized corner output of the brake actuator and the vehicle-calibrated weight value; calculate an actuator error percentage as an absolute value of a mathematical difference between the weighted averages of the brake actuators; determine a vehicle-calibrated error deviation threshold from the current vehicle speed and / or the current vehicle steering angle; detect an actuator error if the actuator error percentage is greater than the vehicle-calibrated error deviation threshold;and instructing the decentralized braking system, in response to the determination that the actuator failure percentage is greater than the vehicle-calibrated failure deviation threshold, to execute a vehicle-calibrated braking action to correct the actuator failure.

[0013] As an application of the method according to the invention, motor vehicles are provided that are equipped with decentralized braking systems and heuristic systems for monitoring and providing feedback on cornering behavior. As used herein, the terms "vehicle" and "motor vehicle" can be used interchangeably and synonymously to include any relevant vehicle platform, such as passenger cars, commercial vehicles, industrial vehicles, off-road vehicles and all-terrain vehicles (ATVs), motorcycles, agricultural equipment, aircraft, spacecraft, etc. In one example, a motor vehicle comprises a vehicle body with a passenger compartment, several wheels attached to the vehicle body (e.g., via corner modules coupled to a unit-body or body-on-frame chassis), and other standard original equipment.A drive unit, which may be a traction motor and / or an internal combustion engine, is located within the vehicle body and drives the wheel(s) to propel the vehicle. A decentralized braking system with multiple independently actuated brake actuators is also mounted on the vehicle body to slow down and / or stop the vehicle. A brake sensor (e.g., a sensor for the force, pressure, or current of the corner brake actuator) is functionally mounted on each brake actuator and can actively monitor the braking torque delivered by that actuator in real time.

[0014] Continuing the discussion from the previous example, the vehicle is also equipped with a built-in or remote controller programmed to communicate with each brake sensor to receive data indicating a measured actuator output from that brake actuator. Using the measured actuator output and a corresponding commanded target output for that brake actuator, the vehicle controller calculates a normalized corner output for each brake actuator. The vehicle controller then determines a vehicle-calibrated weight value based on the vehicle's current speed and / or steering angle, while simultaneously calculating a weighted average for each brake actuator (e.g.,(to calculate the overall system average, the left / right lateral average, and / or the front / rear longitudinal average) using the normalized corner output of the brake actuator and the vehicle-calibrated weighting value. The vehicle control system then calculates a percentage actuator error (lateral, longitudinal, overall system) as an absolute value of a mathematical difference between the weighted averages of the brake actuators and determines a vehicle-calibrated error deviation threshold, e.g., based on the current speed and / or steering angle of the vehicle.If the percentage of actuator errors exceeds the error deviation threshold, the control system identifies one or more actuator errors and then commands the decentralized braking system, the vehicle steering system and / or the vehicle powertrain system to perform a vehicle-calibrated action to correct the actuator error(s).

[0015] According to one embodiment, the vehicle's decentralized braking system can include front left (FL), front right (FR), rear left (RL), and rear right (RR) brake actuators for braking the respective FL, FR, RL, and RR wheels. In this case, calculating a normalized corner output can include calculating the respective normalized FL, FR, RL, and RR corner outputs for the FL, FR, RL, and RR brake actuators. As a further option, the sensor data received from the vehicle's brake sensors can include a force feedback value and a pressure feedback value for each brake actuator. In this case, calculating the normalized corner output can also include receiving a target force value and a target pressure value for each brake actuator. Calculating the normalized corner outputs can identify an actuator type for each brake actuator (e.g., electro-hydraulic vs. hydraulic).electromechanical) and the merging of the force feedback value and the pressure feedback value (e.g. neglecting the zero information) based on the actuator type for this brake actuator to derive a merged feedback value for each brake actuator.

[0016] According to one embodiment, the calculation of a weighted average can include calculating a right-side weighted average for the FR and RR brake actuators based on the normalized FR and RR corner outputs, and calculating a left-side weighted average for the FL and RL brake actuators based on the normalized FL and RL corner outputs. In this case, the actuator error percentage can include a percentage lateral error, calculated as the absolute value of the mathematical difference between the right-side weighted average and the left-side weighted average. An actuator error can be detected and flagged if the percentage lateral error exceeds a vehicle-calibrated lateral deviation threshold.As an additional option, the weighted average calculation can include calculating a front weighted average for the FR and FL brake actuators based on the normalized FR and FL corner outputs, and a rear weighted average for the RR and RL brake actuators based on the normalized RR and RL corner outputs. In this case, the actuator failure percentage can include a longitudinal failure percentage, calculated as the absolute value of the mathematical difference between the front weighted average and the rear weighted average. An actuator failure can be detected and flagged if the longitudinal failure percentage exceeds a vehicle-calibrated longitudinal deviation threshold.

[0017] According to one embodiment, the calculation of a weighted average can include the calculation of a full system average for all FL, FR, RL, and RR brake actuators based on all normalized FL, FR, RL, and RR corner outputs. In this case, the actuator failure percentage includes a system failure percentage, which is calculated as the absolute value of the mathematical difference between the overall system average and a target overall system average. An actuator failure can be detected and flagged if the system failure percentage exceeds a vehicle-calibrated overall deviation threshold.

[0018] According to one embodiment, the vehicle control system can respond to the detection of an actuator fault by determining, based on the calculated normalized corner outputs and the calculated weighted averages, which of the brake actuators is the most faulty actuator (e.g., the highest measured deterioration). As a further option, the vehicle control system can actively receive / retrieve the weight value from a stored calibration lookup table and receive / retrieve the error deviation threshold from the same or a different stored calibration lookup table. In this case, the vehicle control system can update a weight and threshold data set to include the received / retrieved vehicle-calibrated weight value and the vehicle-calibrated error deviation threshold.The vehicle control system can also actively receive / retrieve data about the current vehicle speed, the current vehicle steering angle, and the target actuator output data. In this case, the control system can update a signal data set within a defined time range to include the current vehicle speed, the current vehicle steering angle, the commanded target actuator outputs, and the measured actuator outputs. Fig. Figure 1 is a partially schematic side view of a representative motor vehicle with a decentralized braking system and a network of vehicle-side controls, sensor devices and communication devices to provide a corner performance of a brake actuator output according to the aspects of the present description. Fig. Figure 2 is a flowchart illustrating a representative vehicle control protocol for heuristic polygonal performance monitoring of a brake actuator output for a decentralized vehicle braking system, which may correspond to stored instructions that can be executed by a stationary or remote microcontroller, control module, logic circuit or other integrated circuit (IC) device or network of circuits / modules / microcontrollers / IC devices (collectively, “Control”), according to the aspects of the disclosed concepts. Fig. Figure 3 is a flowchart that represents a representative normalization protocol for the normalization of brake actuator outputs of a decentralized vehicle braking system, according to aspects of the disclosed concepts. Fig. Figure 4 is a flowchart illustrating a representative weighting and averaging protocol for deriving weighted longitudinal and transverse average values ​​for a decentralized vehicle braking system according to aspects of the disclosed concepts. Fig. Figure 5 is a flowchart that represents a representative fault detection protocol for identifying faulty actuators in a decentralized vehicle braking system, according to aspects of the disclosed concepts.

[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 as 10, which is presented here for discussion purposes as an electric sedan. The depicted motor vehicle 10 – also referred to here simply as the “motor vehicle” or “vehicle” – is merely an exemplary application with which aspects of this description can be put into practice. Similarly, the implementation of the present concepts for the depicted vehicle braking system should be understood as a non-restrictive implementation of the disclosed features. It is understood that the aspects and features of this description can also be implemented for other 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 performing the various procedures and functions described below.

[0020] The representative vehicle 10 of Fig. 1 is originally equipped with a vehicle telecommunications and information unit (“telematics”) 14, which communicates wirelessly, e.g. via a mobile network, a satellite service, a wireless modem, etc., with a remote cloud computing host service 24 (e.g. ONSTAR). ® ) communicates. Some of the other vehicle hardware components 16, which are in Fig. The components generally represented in Figure 1 include, as non-limiting examples, an electronic video display device 18, a microphone 28, audio speakers 30, and various user input controls 32 (e.g., buttons, 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, the occupants can input verbal commands via the microphone 28; the vehicle 10 may be equipped with an integrated speech processing unit that uses audio filtering, processing, and analysis modules. Conversely, the speaker 30 provides acoustic output to a vehicle occupant and may be either a standalone speaker for the telematics unit 14 or part of an audio system 22.The audio system 22 is connected to a network connection 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 automatic functions.For example, the telematics unit 14 can exchange signals with a powertrain control module (PCM) 52, an ADAS (Advanced Driver Assistance System) module 54, an electronic battery control module (EBCM) 56, a steering control module (SCM) 58, a brake system control module (BSCM) 60 and various other vehicle ECUs, such as a transmission control module (TCM), an engine control module (ECM), a sensor system interface module (SSIM), 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 be composed of one or more processors 40, each of which can be 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 connected to 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 integrated circuit, a solid-state drive (SSD), a hard disk drive (HDD), flash memory, 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 transceivers), 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 device). ® -unit or an NFC transceiver), 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) communication system or a vehicle-to-general communication system (V2X), 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 devices that use, 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 perform an automated driving (AV / ADAS) operation or a vehicle navigation service. According to the example shown, the motor vehicle 10 can 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 in the form of 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, 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 individually or collectively adapted to a specific vehicle platform to achieve the desired level of automated vehicle operation.

[0025] To propel the motor vehicle 10, an electrified powertrain can generate a tractive torque and deliver it to one or more of the vehicle's drive wheels 26. The powertrain is 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 connected to an electric drive motor (M) 78. The traction battery pack 70 generally comprises 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 drive motor / generator (M) units 78, draw electrical energy from the battery pack 70 and optionally supply electrical energy to it. An 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 vehicle 10 may initially be equipped with a decentralized brake-by-wire braking system 82, comprising a central controller (e.g., BSCM 60) for receiving and processing a braking request from a vehicle operator (e.g., driver or AV / ADAS control module) and discrete corner control modules for modulating a braking force applied to each of the vehicle's wheels. As with any vehicle-side system, routine and continuous use of the decentralized braking system can lead to normal or irregular wear of the individual brake actuators. A heuristic procedure for monitoring braking performance at multiple corners is presented below, which can be used to assess the effects of deteriorated brake actuation in a curve on the vehicle's dynamics during a braking maneuver.The corner performance monitoring method can enable a rapid system response to deteriorating brake actuator performance, predict undesired yaw and deceleration behavior caused by a deteriorating actuator, and detect when the braking system exceeds predefined operating thresholds, regardless of the physical hardware (e.g., electro-hydraulic, electro-pneumatic, electro-mechanical). A further potential advancement is the ability to identify the most severely faulty actuator(s), which can be determined by combining the following three components: (1) overall system balance – total braking deviation from expected output across the entire vehicle; (2) longitudinal balance – front-to-rear braking deviation from expected output; and (3) lateral balance – side-to-side braking deviation from expected output.

[0027] The corner performance monitoring method allows for the evaluation of the individual contributions of each corner actuator to the overall braking and dynamic behavior of the vehicle, which is not normally possible with centralized hydraulic braking systems. Furthermore, the method can assess braking system behavior during highly dynamic events where individual wheel slip control is active. A heuristic approach can be used to identify faults in individual actuators of the decentralized braking system that may contribute to unexpected or abnormal vehicle operation during braking. Systematic corner performance monitoring can be enhanced by the ability to recall a predefined system response or to actively derive an appropriate system response to address deterioration or failure of individual actuators.The presented corner performance monitoring protocols can be used as a diagnostic or detection tool for evaluating brake data and for system development.

[0028] Referring to the flowchart of Fig. 2 An improved method or control protocol for corner performance monitoring of a brake actuator output of a vehicle braking system, such as the decentralized braking system 82 of Fig. 2, of a motor vehicle, such as motor vehicle 10 of Fig. 1, according to the aspects of the present description generally described in 200. Some or all of the in Fig. The operations shown in Figure 2 and described in more detail below can represent an algorithm corresponding to non-transitory, processor-executable instructions that may be stored, for example, in main or auxiliary memory or in remote memory (e.g., in the resident storage device 38 and / or in the remote database of the cloud computing service 24). Fig. 1) are stored. These instructions can be stored, for example, by an electronic controller, a processing unit, a dedicated control module, a logic circuit, or another module or device or network of controllers / modules / devices (e.g., CPU 36, processor(s) 40 and / or BSCM 60 of Fig. 1) to execute one or all of the functions described above and below that are connected with the disclosed concepts. It should be acknowledged that the order of execution of the presented operation blocks can be changed, that additional operation blocks can be added, and that some of the operations described here can be modified, combined, or omitted.

[0029] Procedure 200 begins at starting block 201 of Fig. 2 with processor-executable instructions stored in memory for initializing a control protocol for a decentralized braking system 82 of a motor vehicle 10. This routine can be initialized in real time, near real time, continuously, systematically, sporadically, and / or at predefined time intervals, e.g., every 10 or 100 milliseconds during the operation of the motor vehicle 10. As another option, the start block 201 can be initialized in response to a user command request (e.g., via the telematics input controls 14), a request from the resident control of the vehicle (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, the procedure 200 can be automatically initialized in response to a driver of the motor vehicle 10 pressing a brake pedal in the vehicle or otherwise transmitting a deceleration request via a suitable user input controller 32. Upon completion of some or all of the steps described in . Fig. In the two control processes shown, procedure 200 can continue to end block 243 and be temporarily terminated, or it can optionally return to block 201 and run in a continuous loop.

[0030] Moving from block 201 to the DYNAMIC SIGNAL UPDATE data input block 203, procedure 200 can execute instructions to update the signals received from the brake system's corner actuators and the vehicle's speed and dynamic sensors. This may involve, for example, a resident or remote vehicle control unit—the BSCM 60 alone or in conjunction with the CPU 36 and / or the PCM 52—using the individual front left (FL), front right (FR), rear left (RL), and rear right (RR) brake sensors 86. FL , 86 FR , 86 RL and 86 RR , which are operationally located on the individual brake actuators 84 FL , 84 FR , 84 RL and 84 RR of the brake system 82 are attached to receive sensor data, which provides a measured actuator output for each brake actuator 84 FL , 84 FR , 84 RL , 84 RR Display. The brake sensors 86FL , 86 FR , 86 RL and 86 RR They can adopt any suitable design, including pressure sensors, force transducers, electrical current sensors, etc. Simultaneously, the vehicle control unit can communicate with one or more of the vehicle speed sensors 66 and one or more of the vehicle dynamics sensors 68 to retrieve a current (real-time) vehicle speed and a current (real-time) vehicle steering angle. Finally, the BSCM 60 can coordinate with the PCM 52 to communicate with an in-vehicle BBW brake pedal to receive a braking request from the driver and derive a commanded target actuator output for each brake actuator 84. FL , 84 FR , 84 RL , 84 RRto derive. Once the new signals are collected, the vehicle's control system can update a signal data set within a defined time range to record the vehicle's current speed, steering angle, commanded target actuator outputs, and measured actuator outputs.

[0031] Before, concurrently with, or after the execution of data input block 203, procedure 200 can execute the WEIGHTING AND THRESHOLD UPDATE data input block 205 to update vehicle-calibrated weighting values ​​and vehicle-calibrated error deviation thresholds used for subsequent weighted average calculations and actuator fault detection. The vehicle-calibrated weighting values ​​and error deviation thresholds are intended to be derived in real time from the vehicle's control system or from a back-office (BO) vehicle host server, such as the cloud computing service 24 from Fig. 1. However, according to the example shown, procedure 200 executes the LOOKUP TABLE data block 207 and calls a (first) calibration lookup table for weight values, which is stored in a read-accessible memory (e.g., in a resident device 38), to retrieve a vehicle-calibrated weight value. Similarly, the vehicle control can simultaneously call a (second) calibration lookup table for deviation thresholds from the resident RAM to retrieve a vehicle-calibrated error deviation threshold. The deviation threshold lookup table can be part of the aforementioned weight value lookup table or different from it. As explained further below, the vehicle-calibrated weight value and the error deviation threshold can be selected based on the current vehicle speed and the current vehicle steering angle.After retrieval, the weighting value and the error deviation threshold can be stored in a weight and threshold data set in the cache memory.

[0032] The procedure 200 of Fig. 2 can proceed from data input block 205 to the NORMALIZED CORNER OUTPUT subroutine 209 to calculate a set of normalized corner outputs from the corner outputs measured by the sensor, based on the commanded target values ​​of the braking system. As discussed further below in the discussion of Fig. As explained in section 3, the vehicle control system can provide a normalized corner output for each brake actuator 84. FL , 84 FR , 84 RL , 84 RR using the measured actuator output, which is derived from its brake sensor 86 FL , 86 FR , 86 RL and 86 RRis provided, and calculates the respective commanded target actuator output for this brake actuator, which is retrieved in data input block 203. After calculating the normalized corner outputs, procedure 200 executes the WEIGHTED AVERAGE subroutine 211 to calculate a weighted overall average (system average), weighted longitudinal averages (front and rear axles), and weighted transverse averages (left and right sides). As discussed below in the discussion of Fig. As explained in section 4, the vehicle control system can calculate a weighted average for all and / or selected pairs of brake actuators 84. FL , 84 FR , 84 RL , 84 RR calculate using the normalized corner output of this brake actuator and the vehicle-calibrated weight value stored in the cache memory, which is selected using the vehicle's current speed and steering angle.

[0033] After normalizing the corner outputs and calculating the corresponding weighted averages, Procedure 200 can perform the LATERAL DEVIATION process block 213, the LONG-TERM DEVIATION process block 215, and the TOTAL SYSTEM DEVIATION process block 217 to determine the side-to-side, front-to-back, and overall deviations of the braking system from a nominal "healthy" system. As explained further below in the section on Fig. As discussed in section 5, the longitudinal, lateral, and total deviations can be represented by corresponding actuator error percentages, which are calculated by the vehicle control system as an absolute value of a mathematical difference between corresponding weighted averages of the brake actuators. To perform a side-by-side comparison of the weighted lateral averages of the vehicle braking system, process block 211 can, for example, calculate a right-side weighted average for the FR and RR brake actuators. FR and 84 RR based on the normalized FR and RR corner outputs as well as a left-hand weighted average for the FL and RL brake actuators 84 FL and 84 RLbased on the normalized FL and RL corner outputs. Simultaneously, in process block 213, a percentage page error is calculated as the absolute value of the mathematical difference between the right- and left-weighted averages.

[0034] To perform a front-to-rear comparison of the weighted lateral averages of the vehicle braking system, process block 211 can calculate both a front-side weighted average for the FR and FL brake actuators 84 FR and 84 FL based on the normalized FR and FL corner outputs as well as a reverse weighted average for the RR and RL brake actuators 84 RR and 84 RLbased on the normalized RR and RL corner outputs. A longitudinal error percentage is calculated simultaneously in process block 215 as the absolute value of the mathematical difference between the weighted front and rear averages. Likewise, process block 211 can calculate an overall system average for all four brake actuators 84 FR , 84 FL , 84 RR and 84 RL based on all normalized FL, FR, RL, and RR corner outputs. A percentage system error can then be calculated in process block 217 as the absolute value of the mathematical difference between the overall system average and a target overall system average.

[0035] After determining one, more, or all of the above-mentioned brake system deviations, Procedure 200 can execute LATERAL DEVIATION Decision Block 219, LONG-TERM DEVIATION Decision Block 221, and TOTAL SYSTEM DEVIATION Decision Block 223 to determine whether a brake actuator is faulty (e.g., excessively deteriorated, defective, damaged, failed, etc.). In each case, a fault may be indicated if the calculated actuator fault percentage is greater than the corresponding vehicle-calibrated fault deviation threshold. As a non-restrictive example, Decision Block 219 determines whether the percentage lateral fault exceeds the vehicle-calibrated lateral deviation threshold. If it does not (Block 219 = NO), Procedure 200 can loop back to Data Input Block 203.If, however, the percentage of lateral deviation exceeds the lateral deviation threshold (Block 219=YES), Procedure 200 executes the LATERAL DEVELOPMENT data storage block 225 in response and sets a marker in memory indicating that a fault is likely present in either a port or starboard brake actuator, as indicated by the detected lateral deviation. Procedure 200 then executes the LATERAL FAILURE decision block 231 to determine whether the detected lateral deviation has reached the level of a failed actuator (e.g., whether the detected lateral deviation exceeds a lateral fault threshold). If this is not the case (Block 231=NO), Procedure 200 can loop back to data input block 203.If a failed actuator is detected (Block 231=YES), procedure 200 can execute the predefined BUNDLE & ANALYZE process block 237 in response.

[0036] With further reference to Fig. In step 2, decision block 221 determines whether the longitudinal error percentage exceeds the threshold for the vehicle-calibrated longitudinal deviation. If this is not the case (block 221=NO), procedure 200 can return to data input block 203 in a loop. If, on the other hand, the longitudinal error percentage exceeds the threshold for the longitudinal deviation (block 221=YES), procedure 200 can, in response, execute the LONGITUDINAL DEVIATION data storage block 227 and place a marker in memory indicating that a fault is likely in either a front or a rear corner actuator, as indicated by the detected front-to-back deviation. Procedure 200 then executes decision block 233 on a longitudinal error to determine whether the detected front-to-back deviation has reached the level of a failed actuator (e.g.,The detected longitudinal deviation exceeds a longitudinal error threshold. If this is not the case (Block 233=NO), procedure 200 can return to data input block 203 in a loop. If a failed actuator is detected (Block 233=YES), procedure 200 can execute the predefined process block 237 in response.

[0037] Decision block 223 determines whether the overall system error percentage exceeds a vehicle-calibrated threshold for the overall system deviation. If it does not (block 223=NO), procedure 200 can loop back to data input block 203. However, if the system error percentage exceeds the system deviation threshold (block 223=YES), procedure 200 can execute the SYSTEM DEVIATION data storage block 229 and place a marker in memory indicating that a fault is likely present in some or all corner actuators, as indicated by the detected system deviation. Procedure 200 then executes the SYSTEM FAILURE decision block 235 to determine whether the detected system deviation has reached the level of a systemic actuator fault (e.g., whether the detected system deviation exceeds a system fault threshold).If this is not the case (Block 235=NO), procedure 200 can return to data input block 203 in a loop. If a failed actuator is detected (Block 235=YES), procedure 200 can execute the predefined process block 237 in response.

[0038] After detecting one or more faulty actuators in the braking system, procedure 200 can automatically execute the predefined BUNDLE & ANALYZE process block 237 to summarize, store, and analyze the results of the fault detection process and attempt to determine the most faulty actuator based on this information. For example, if the lateral deviation analysis indicates deteriorated brake actuation on the port side of vehicle 10 (e.g., causing induced yaw) and the longitudinal deviation analysis indicates deteriorated brake actuation on the front axle of vehicle 10 (e.g., causing a loss of deceleration), procedure 200 can determine that the front left brake actuator 84 is the most faulty actuator. FL the most deteriorated / defective of the four brake actuators 84 FL , 84 FR , 84 RL , 84 RRThe results of the analysis performed in the predefined process block 237 can be stored in resident memory in the SAVE RESULTS data storage block 239. In the BRAKE SYSTEM MODULATION process block 241, the procedure can adapt the vehicle control to maintain vehicle stability. For example, the vehicle control can automatically respond to the detection that a percentage actuator failure exceeds its error deviation threshold by instructing the decentralized braking system 82 to execute a vehicle-calibrated braking action to correct the detected actuator failure.

[0039] In Fig. Figure 3 shows a representative normalization protocol / procedure 300, which is incorporated into procedure 200 of Fig. 2 for normalizing the corner outputs of the brake actuators 84 FL , 84 FR , 84 RL , 84 RRof the decentralized vehicle braking system 82. As indicated above, normalized corner outputs can be derived from the current values ​​of the brake actuator target clamping forces, the current values ​​of the achieved clamping forces, and the updated signals for the weight function and the deviation threshold parameters. Normalization can be achieved in part by dividing the actuator's feedback response by the target pressure or target force for that actuator. Normalizing the corner outputs allows the algorithm to be independent of the brake corner output units (e.g., newtons or pounds-force for electromechanical brake actuators, or bar for electrohydraulic brake actuators) by providing a dimensionless value. In practice, the procedure can be 300 of Fig. 3 must be executed four times, once for each of the brake actuators 84 FL , 84 FR , 84 RL , 84 RR .

[0040] With further reference to Fig. 3. The procedure 300 can provide a force feedback value (e.g., for an electromechanical actuator) for a specific curve (e.g., FL brake actuator 84). FL ) received in process block 301, while a pressure feedback value (e.g. for an electrohydraulic actuator) for the specific curve (e.g. FL brake actuator 84) FL ) can be received in process block 303. Simultaneously, a target force value for the designated curve can be received in process block 305 (e.g., if electromechanical), while a target pressure value for the designated curve can be received in process block 307 (e.g., if electrohydraulic). Process block 309 of Fig. Block 3 combines the input values ​​from blocks 301 and 303, while process block 311 combines the input values ​​from blocks 305 and 307. During a "combination," either pressure feedback from a hydraulic actuator or clamping force feedback from a mechanical actuator is used. For example, if the curve in question represents an electromechanical actuator, the pressure feedback value can be set to "zero," and the clamping force feedback value can be shifted by the combination function. For each brake actuator 84 FL , 84 FR , 84 RL , 84 RR A combined feedback value is output by a first merging function in process block 309, by combining the force feedback value and the pressure feedback value based on the actuator type for this brake actuator. Similarly, for each brake actuator 84 FL , 84 FR , 84RL , 84 RR A second merging function in process block 311 outputs a merged target value by merging the force target value and the pressure target value based on the actuator type for this brake actuator.

[0041] In process block 313, the aggregated feedback value from process block 309 is mathematically divided by the aggregated target value from process block 311. In process block 315, a single-digit numeric floating-point data type, which can be of the type "Float" or "Single (1)", is passed through the normalization function when a zero setpoint is output as the aggregated setpoint, in order to avoid a mathematical error in normalization log 300. In other words, if a setpoint is zero, no brake request has been received, and therefore no pressure / force feedback is generated. Thus, an error deviation should not be detected, and the normalization output can be set to 100%.The value output by process block 313 is fed into the multiplication operator 321, where it is multiplied by a set value of one hundred (100) output by process block 317 ("Single (100)") to convert the number into a percentage. For example, if the aggregated feedback value is 2000 psi and the aggregated target value is 2400 psi (2000 / 2400 = 0.8333 x 100 = 83.33), the normalized corner actuator output can be set to 83.3%. In process block 319, a set function assigns each normalized corner actuator output value a unique variable name that can be called in another function within the code.

[0042] Fig. 4 is a representative protocol / procedure 400 for weighting and averaging, which is incorporated into procedure 200 of Fig. 2 for deriving weighted longitudinal, transverse and overall average values ​​for the brake actuators 84 FL , 84 FR , 84RL , 84 RR of the decentralized vehicle braking system 82 can be integrated. Using this protocol 400, a weighted average can be calculated for each side of the vehicle (i.e., left and right corners), for each end of the vehicle (i.e., front and rear axle corners), and for the entire braking system (all four corners) using the four normalized signals provided by the normalization protocol 300. Fig. The weighting function parameter can be determined. As mentioned above, it can be retrieved from a calibratable lookup table, which can be calculated offline using real brake system data and simulation environments. Weighting and averaging can be performed to account for the different contributions of individual brake corners to the overall vehicle dynamics during various maneuvers.

[0043] In process blocks 401, 403, 405 and 407 of Fig. 4 The procedure 400 receives as inputs the normalized FR, FL, RR and RL corner output values ​​for the FR, FL, RR, RL brake actuators 84 FR , 84 FL , 84 RL , 84 RRA real-time vehicle speed value is received by procedure 400 in process block 409, and a real-time vehicle steering angle value is received in process block 411. A calibration table (CalTbl_C) is called in process block 413 to retrieve a vehicle-calibrated weight value corresponding to the vehicle's current speed and steering angle. Proceeding to process block 415, procedure 400 takes the vehicle-calibrated weight value as a weighting factor and takes the normalized value of each corner to determine (“AVG1”) a left or front weighted average of the left side or front end of vehicle 10 and a right or rear weighted average of the right side or rear end of vehicle 10. A right-side weighted average might be calculated, for example, as follows: AverageNormOutput=Wx(NormFronRightOutput+NormRearRightOutput)W+1 W = Weighting function (vehicle speed, vehicle steering angle)

[0044] A similar calculation can be performed to determine a weighted average for the left side, a weighted average for the front end, and a weighted average for the rear end. A full system comparison can be performed by calculating an overall average using all four normalized corner outputs and applying the same weighting factor as the other functions. The overall system weighted average can be compared to the unit value (1) to account for all wheels normalized against their targets. In process blocks 417 and 419, a set function assigns each weighted average a unique variable name that can be called in another function within the code.

[0045] Fig. 5 is a representative fault detection protocol / procedure 500, which is incorporated into procedure 200 of Fig. 2 can be integrated to replace faulty actuators in the brake actuators 84 FL , 84 FR , 84 RL , 84 RRto identify the decentralized vehicle braking system 82. The fault detection protocol 500 can determine whether the deviations from side to side, front to rear, and across the entire system brake exceed what can be considered a nominally healthy system and thus could lead to a vehicle hazard. Upon detection of an actuator fault, the faulty actuator(s) can be identified by providing the control system with appropriate information via predefined interfaces so that the system can modulate the actuator power to reduce it appropriately and simultaneously adjust the vehicle control to maintain vehicle stability.

[0046] With further reference to Fig.In process block 501, the right weighted average is received as the first input from procedure 500, and the left weighted average is received as the second input from procedure 500 in process block 503. In process block 505, a mathematical difference ("stumbling block") is calculated between the right and left weighted averages received in process blocks 501 and 503. In process block 507, an actuator error percentage is calculated as the absolute value of the mathematical difference between the weighted averages of the brake actuators from block 505. In process block 509, procedure 500 receives a real-time vehicle speed value, and in process block 511, a real-time vehicle steering angle value. In process block 513, a calibration table (CalTbl_C) is called to retrieve a vehicle-calibrated deviation threshold value corresponding to the current speed and steering angle of the vehicle.In process block 515, an actuator fault is detected if the actuator fault percentage is greater than the vehicle-calibrated fault deviation threshold. If a fault is detected, procedure 500 can issue a command for an improved braking system in process block 517 as a response.

[0047] Aspects of this description can, in some embodiments, be implemented by a computer-executable program with instructions, such as program modules, commonly referred to as software applications or application programs, and executed by a controller or the variants of the controller 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.

[0048] Furthermore, aspects of this description can be implemented 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 within a computer system or other processing system.

[0049] Each of the methods described herein may contain machine-readable instructions for execution by (a) a processor, (b) a controller, and / or (c) any other suitable processing device. Each algorithm, software, control logic, protocol, or method disclosed herein may be embodied as software stored on an accessible 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 parts thereof may 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 can be 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 for operating a motor vehicle (10) with a vehicle body (12), several road wheels (26) attached to the vehicle body and a decentralized braking system (82) with several brake actuators (84) which can each be actuated to brake one of the road wheels (26), wherein the method comprises: Receiving sensor data indicating a measured actuator output of one of the brake actuators (84) from each of several sensors (86) that are operationally attached to the brake actuators (84); Calculate, via a control (36) of the vehicle (10) for each of the brake actuators (84), a normalized corner output using the measured actuator output and a commanded target actuator output for the brake actuator (84); wherein the multiple brake actuators (84) comprise front-left (FL), front-right (FR), rear-left (RL) and rear-right (RR) brake actuators (84) and wherein calculating the normalized corner output comprises calculating normalized FL, FR, RL and RR corner outputs for the FL, FR, RL and RR brake actuators (84) respectively; wherein receiving the sensor data indicating the measured actuator outputs includes receiving a force feedback value and a pressure feedback value for each of the FL, FR, RL and RR brake actuators (84), and wherein calculating the normalized corner output further includes receiving a target force value and a target pressure value for each of the FL, FR, RL and RR brake actuators (84); Calculate, via the control (36) of the vehicle (10) for each of the brake actuators (84), a weighted average using the normalized corner output of the brake actuator (84) and a vehicle-calibrated weight value determined from a current vehicle speed and / or a current vehicle steering angle; Calculate, via the control (36) of the vehicle, an actuator error percentage as an absolute value of a mathematical difference between the weighted averages of the brake actuators (84); Detect, via the control (36) of the vehicle (10), an actuator fault when the actuator fault percentage is greater than a vehicle-calibrated fault deviation threshold determined from the current vehicle speed and / or the current vehicle steering angle; and Instructing the decentralized braking system (82), a vehicle steering system and / or a vehicle powertrain system via the control (36) of the vehicle (10) in response to the determination that the actuator fault percentage is greater than the vehicle-calibrated fault deviation threshold, to perform a vehicle-calibrated action to correct the actuator fault. [2] The method of claim 1, wherein the calculation of the normalized corner output further comprises: Determine, via the control (36) of the vehicle (10), an actuator type for each of the FL, FR, RL and RR brake actuators (84); and Determine, via the control (36) of the vehicle (10) for each of the FL, FR, RL and RR brake actuators (84), a summed feedback value by summarizing the force feedback value and the pressure feedback value based on the actuator type for the brake actuator (84). [3] Method according to claim 1, wherein the calculation of the weighted average comprises: Calculating a right-hand weighted average for the FR and RR brake actuators (84) based on the normalized FR and RR corner outputs; and Calculation of a left-sided weighted average for the FL and RL brake actuators (84) based on the normalized FL and RL corner outputs. [4] Method according to claim 3, wherein the actuator error percentage includes a lateral error percentage calculated as the absolute value of the mathematical difference between the right-side weighted average and the left-side weighted average, and wherein the actuator error detection includes the lateral error percentage that exceeds a vehicle-calibrated lateral deviation threshold. [5] Method according to claim 1, wherein the calculation of the weighted average comprises: Calculating a front-side weighted average for the FR and FL brake actuators (84) based on the normalized FR and FL corner outputs; and Calculating a backside weighted average for the RR and RL brake actuators (84) based on the normalized RR and RL corner outputs. [6] Method according to claim 5, wherein the actuator error percentage comprises a longitudinal error percentage calculated as the absolute value of the mathematical difference between the front-weighted average and the rear-weighted average, and wherein the actuator error detection comprises the longitudinal error percentage which exceeds a vehicle-calibrated longitudinal deviation threshold. [7] Method according to claim 1, wherein the calculation of the weighted average comprises calculating an overall system average for all FL, FR, RL and RR brake actuators (84) based on all normalized FL, FR, RL and RR corner outputs. [8] Method according to claim 7, wherein the actuator error percentage includes a system error percentage calculated as the absolute value of the mathematical difference between the overall system average and a target overall system average, and wherein the actuator error detection includes the system error percentage that exceeds a vehicle-calibrated overall deviation threshold.

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