Optimization of vehicle stability and steering during a regenerative braking event

Abstract

Method (100) for optimizing the behavior of a vehicle (10) with multiple road wheels (15F, 15R) and a regenerative braking capability designed for electronic braking of the vehicle (10) during an active regenerative braking (RBE) event, wherein the method (100) comprises: measuring (104) a set of inertial data of the vehicle (10), comprising a rotational speed (NF, NR) of each road wheel (15F, 15R), an input steering angle (θS) of the vehicle (10), a longitudinal and lateral acceleration (ay, ax) of the vehicle (10), and an actual yaw rate (RACTUAL) of the vehicle (10) during the active RBE; calculating (106, 108, 110, 112) a set of vehicle behavior data using the set of inertial data, which comprises determining a wheel slip rate of the road wheels. (15F, 15R), a vehicle speed (V) (10), a vehicle acceleration vector (VAV) and a target yaw rate (RDES) are calculated;the input steering angle (θS) of the vehicle (10), the wheel slip rate of the road wheels (15F, 15R) and the speed (V) of the vehicle (10) are compared with associated calibrated threshold data (113, 114, 116), the vehicle acceleration vector (VAV) is compared with an associated VAV holding point and the target yaw rate (RDES) is compared with the actual yaw rate (RACTUAL) in order to determine a deviation with reference to the corresponding calibrated threshold data for the input steering angle (θS), the wheel slip rate of the road wheels (15F, 15R), the speed (V) of the vehicle (10), the vehicle acceleration vector (VAV) and the target yaw rate (RDES);a maximum regenerative braking torque (RBT) is calculated, which includes applying a multiplier (M1, M2, M3, M4) ranging from 0 to 1 to the input steering angle (θS) of the vehicle (10), the wheel slip rate of the road wheels (15F, 15R), the speed (V) of the vehicle (10) and the vehicle acceleration vector (VAV) (121, 122, 124, 126), where the value of the respective multiplier (M1, M2, M3, M4) corresponds to the respective calculated deviation; a resulting yaw rate error value (ER) is calculated as a function of the target yaw rate (RDES) and the actual yaw rate (RACTUAL) (128); and the maximum RBT is calculated as a function of the input steering angle (θS) of the vehicle (10), the wheel slip rate of the road wheels (15F, 15R), the speed (V) of the vehicle (10) and the vehicle acceleration vector (VAV) to which the respective multiplier (M1, M2, M3, M4) has been applied, and the resulting yaw rate error value (ER) (130);and the maximum RBT is automatically applied during the active RBE (132).

Description

TECHNICAL AREA The present invention relates generally to a method and a device for optimizing vehicle stability and steering behavior during an active regenerative braking event. BACKGROUND OF THE INVENTION Some vehicle concepts selectively utilize multiple energy sources to improve overall fuel economy and reduce levels of certain vehicle emissions. For example, a hybrid electric vehicle, or HEV, incorporates a rechargeable energy storage system (ESS), typically designed as a rechargeable battery or battery pack with a relatively high energy density. The HEV may also include an internal combustion engine running on gasoline, diesel, or an alternative fuel. Other vehicle concepts may alternatively use a fuel cell and / or another power source instead of, or in conjunction with, an internal combustion engine to further reduce vehicle emissions and improve the vehicle's range. In some HEV concepts, the vehicle's drive wheels remain continuously connected to the final drive to enable regenerative braking, providing a relatively efficient means of capturing useful and otherwise wasted braking energy. As is known in engineering, an electric motor / generator can be selectively operated in such a way that the device is allowed to act as a generator during an active regenerative braking event. When the electric motor / generator acts as a generator, it recharges the ESS while applying negative torque to the drive wheels and / or the driveshaft, thus electronically decelerating the HEV. The electric motor / generator can equally selectively operate as an electric motor, drawing stored electrical energy from the ESS as needed to power the HEV. In a HEV equipped with an anti-lock braking system (ABS), a traction control system (TCS), and / or electronic stability control (ESC), vehicle stability and steering response can be improved using any or all of these systems. However, during an active regenerative braking event in an HEV, the regenerative braking torque is simply applied to the wheels rotating on a common axis, which may slip on a surface with a low coefficient of friction. Depending on which set of front or rear wheels slips, the overall stability and / or steering response of the HEV may be affected.Although ABS, TCS and ESC can all assist the HEV in a rapid recovery from such a slide, it may be more desirable to primarily prevent or suppress the occurrence of slides. German patent DE 10 2006 046 093 A1 discloses a braking system and method for braking a hybrid vehicle. The system comprises a regenerative brake and a service brake (friction brake). A vehicle stability control system, similar to an ESP system, determines vehicle dynamic parameters such as lateral acceleration, yaw rate, and vehicle speed. Based on these parameters, a predetermined maximum regenerative braking force is calculated. The regenerative braking is controlled so that the braking force it applies does not exceed this calculated maximum value. The aim is to prevent regenerative braking from causing vehicle instability (understeer or oversteer) in the first place. Any additional braking required by the driver is handled by the service brakes. Factors used to determine the maximum permissible regenerative braking force include vehicle speed, steering wheel angle, and a measured yaw rate. DE 11 2006 001 908 T5 describes a method and a device for controlling a vehicle with multiple, individually driven wheel motors to improve cornering behavior. Understeer or oversteer of the vehicle is actively corrected. For this purpose, a yaw rate error is determined, which represents the deviation between a commanded yaw rate (based on the steering angle) and the actually measured yaw rate. Based on this yaw rate error, a desired yaw moment is calculated. The corrective yaw moment is generated by selectively and individually adjusting the drive or brake torque of the individual wheel motors. For example, the torque for the inside wheels in a curve is controlled differently than for the outside wheels in a curve to stabilize the vehicle. The control system distinguishes whether the vehicle is in drive, energy recuperation (braking), or coasting mode. SUMMARY OF THE INVENTION Consequently, a method and a device for use in a vehicle possessing regenerative braking capability as described above are provided. The method is executed automatically by the device during an active regenerative braking event (RBE). Signals transmitted or relayed by various inertial sensors are used as input signals to an electronic control unit or controller, which in turn calculates, selects, or otherwise determines a maximum regenerative braking torque (RBT) that can be applied during the active RBE without causing the vehicle to understeer or oversteer.A driver-commanded total braking torque, or OBT, ordered by a driver or operator of the vehicle during active RBE, is provided by assigning the driver-commanded OBT to the calculated maximum RBT and a conventional friction braking torque, or FBT, where the calculated maximum RBT ranges from a theoretical maximum value or unlimited value down to a zero value, depending on the values ​​of the various input signals. Within the scope of the invention, the inertial sensors can include a steering angle sensor, acceleration measuring devices designed to measure the linear lateral and longitudinal accelerations of the vehicle, wheel speed sensors connected to each of the vehicle's road wheels, and / or a brake input sensor for detecting the OBT commanded by a driver. Measurements from the inertial sensors are compared with an associated set of calibrated thresholds to determine an associated multiplier and / or a resulting error value for each measurement, the multiplier and / or the resulting error values ​​being used to adjust the magnitude of the calculated maximum RBT to be applied during active RBE. In particular, the method comprises collecting or measuring a set of inertial data during the active RBE, calculating a set of vehicle behavior data using this set of inertial data, and comparing the calculated set of vehicle behavior data with an associated set of calibrated threshold data to determine or calculate the maximum RBT. The method also includes automatically applying the calculated maximum RBT during the active RBE. The vehicle comprises a chassis, at least one electric motor / generator used to apply the calculated maximum RBT during an active RBE, and a friction braking system to provide friction braking torque (FBT). The vehicle also includes a set of inertial sensors for measuring a set of chassis inertia data and a controller that incorporates an algorithm for calculating a set of vehicle behavior data using this chassis inertia data. The controller determines the maximum RBT by comparing the vehicle behavior data with an associated set of threshold data and automatically applies the maximum RBT during the active RBE. A control system that can be used with the vehicle optimizes steering behavior and stability during the active RBE described above. The control system includes sensors for measuring a set of chassis inertia data, comprising a brake sensor connected to a brake input device and used to detect driver-initiated total braking torque (OBT); a steering angle sensor connected to a steering input device and used to detect a steering angle from which a steering angle rate can be calculated; and / or one or more acceleration sensors used to measure linear acceleration of the vehicle's chassis about a longitudinal and / or lateral axis. Using the chassis inertia data, the control system calculates a maximum regenerative braking torque (RBT) and automatically applies the maximum RBT during active RBE. The foregoing features and advantages and other features and advantages of the present invention will be readily apparent from the following detailed description of the best ways of carrying out the invention when read in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS Fig. 1 is a schematic illustration of an exemplary hybrid electric vehicle or HEV according to the invention; Fig. 2 is a schematic perspective view of the vehicle of Fig. 1; Fig. 3 is a table describing a set of sensor input data for the controller that can be used with the vehicle of Fig. 1 and Fig. 2; and Fig. 4 is a schematic flowchart describing a control algorithm or control method that can be used with the vehicle of Fig. 1 and Fig. 2. DESCRIPTION OF PREFERRED EXECUTION FORMS With reference to the various figures, in which the same reference numerals denote identical or similar components in the different figures, and beginning with Fig. 1, a vehicle 10 is shown as an exemplary hybrid electric vehicle or HEV, although the vehicle 10 can be configured within the scope of the invention as any vehicle that has regenerative braking capability. The exemplary vehicle 10 comprises an energy conversion system or machine (E) 12, an electrical storage system (ESS) 19, and at least one electric motor / generator (M / G) 17. The machine 12 can be connected to a transmission (T) 14 for driving, either directly or, as shown, via a hydrodynamic torque converter arrangement (TC) 24 or via another torque transmission mechanism, such as a clutch (not shown).The vehicle 10 comprises an electronic control unit or controller 32 with an algorithm or method 100 for brake control, as described below with reference to Fig. 4. The controller 32, in a broad sense, describes a distributed or centralized control module which, in addition to a brake control module, can also include such control modules and capabilities as may be necessary for operating the vehicle 10 in the desired manner. This means that the controller 32 can also include any or all of: a machine control module, a transmission control module, a battery stack control module, a transmission inverter module, etc. When configured in this way, the controller 32 can provide overarching control and coordination of the aforementioned controllers. For the sake of simplicity, the controller 32 is shown as a single device, although separate controllers can also be used within the scope of the invention. The controller 32 can be configured as a general-purpose digital computer, generally comprising a microprocessor or central processing unit, a read-only memory (ROM), a random-access memory (RAM), an electrically programmable read-only memory (EPROM), a high-speed clock, analog-to-digital (A / D) and digital-to-analog (D / A) circuits, and input / output (I / O) circuits and devices, as well as suitable signal conditioning and buffering circuits. Each set of algorithms present in or accessible to the controller 32, including the algorithm or method 100 of the invention, is stored in the ROM and is executed to provide the respective functions of each controller present. The ESS 19 can be configured as one or more batteries, although other electrical and / or electrochemical energy storage devices capable of storing and releasing electrical power within the scope of the invention may be used. The ESS 19 can be dimensioned based on factors including regenerative braking requirements, application issues related to typical road gradients and temperatures, and drive requirements such as emissions, power assistance, and electric driving range. Generally, the ESS 19 is a relatively high-voltage direct current (DC) device coupled, via adequately constructed and routed DC wiring, to a (not shown) geared inverter module, as understood by those skilled in the art. Still referring to Fig. 1, the machine 12 within the scope of the invention can, for example, be configured as an internal combustion engine for gasoline, diesel, biodiesel, ethanol, or another type. The machine 12, however configured, is capable of generating a sufficient quantity or level of machine torque to rotate an output or drive shaft of the HEV 10, which ultimately rotates or powers, as required, a respective set of front and / or rear drive axles 21, 22. In this way, the HEV 10 can be driven via a set of drive wheels 15F, 15R, where, with respect to the normal passenger orientation in the vehicle 10, F is designated as "front" and R as "rear". The vehicle 10 can include a front and rear differential 20F and 20R, respectively, which allows the drive axles 21 and 22 to rotate independently at different speeds on each side of the vehicle 10. This means that the front differential 20F can allow a rotational speed N1Fan on one side of the vehicle 10 and a potentially different rotational speed N2Fan on the other side. Similarly, the rear differential 20R can allow a rotational speed N1Ran on one side of the vehicle 10 and a potentially different rotational speed N2Ran on the other side. The motor / generator 17 can operate alternately as a power supplier or as a power generator. When operating as an electric motor or power supplier, the motor / generator 17, which may comprise a single unit or multiple units depending on the vehicle 10 design, will supply power to the transmission 14. When the motor / generator 17 operates as a generator, it will receive electrical power from the transmission 14. The controller 32 is designed to transfer or distribute electrical energy from the motor / generator 17 to the ESS 19 for recharging the ESS 19, and / or to distribute the electrical energy from the ESS 19 to another (not shown) electrical power unit, which at that time is operating as an electric motor. The vehicle 10 comprises a conventional electromechanical or hydraulic friction braking system 37, such as a fluid-operated disc and / or drum brake system, positioned near each drive wheel 15F, 15R and designed to provide a friction braking torque (FBT) which can be augmented by an electronic / regenerative braking torque or RBT. When a driver or operator of the vehicle 10 depresses a brake input device (B) 11, such as a brake pedal, to input a force and displacement describing a driver-commanded overall braking torque (OBT), the friction braking system 37 decelerates the vehicle 10 by a combination of the FBT and the RBT, as described below. Still referring to Fig. 1, the vehicle 10 is also equipped with a plurality of wheel speed sensors (S) 30A, which can measure the wheel speed data, i.e., N1F, N1R, N2F, and N2R, and can also determine a slip level between the wheels 15F, 15R, and a road surface 50. A vehicle speed can be calculated by the controller 32 using the wheel speed data, i.e., N1F, N1R, N2F, and N2R, as described above. The front axle 21 can be divided into two independently rotating sides by the front differential 20F, and the rear axle 22 can be divided into two independently rotating sides by the rear differential 20R. Each wheel 15F, 15R has the potential to slip relative to the road surface 50. Therefore, in Fig.1 the rotational speeds of the wheels 15F, 15R are each represented as N1F and N2F for the possibly different rotational speeds of the two sides of the front axle 21 and as N1R and N2R for the possibly different rotational speeds of the two sides of the rear axle 22. The controller 32 receives input signals from various points on the vehicle 10, including but not limited to: machine torque, machine speed, electric motor torque and direction, throttle or accelerator pedal position or request, etc. The controller 32 also receives a set of inertial data, which may include driver-commanded OBT applied to the brake input device 11 and measured by a brake input sensor 30B, as well as wheel speeds from the sensors 30A described above. The vehicle 10 also includes a steering column 18 and a steering input device 16, such as a steering wheel, used to steer the drive wheels 15F. The steering input device 16 and / or the steering column 18 are connected to a steering angle sensor 30C, which provides a steering angle θS, a further element of the set of inertial data from which a steering angle rate can be readily calculated. Finally, a set of acceleration measuring devices 30D measures or detects a linear acceleration (a) of the vehicle 10 along its transverse and / or longitudinal axes X, Y, as described below with reference to Fig. 2, and a gyroscope device or yaw rate sensor 30E measures or detects a yaw rate (R) of the vehicle 10 with respect to its vertical or Z-axis, as also described below with reference to Fig. 2.The signals NR, NF, OBT, θS, a and R are collected from the respective sensors 30A-E and forwarded as a set of input signals to the controller 32 via a hard-wired or wireless connection. With reference to Fig. 2, the vehicle 10 of Fig. 1 has three primary axes X, Y, and Z. The X-axis here denotes the transverse axis of the vehicle 10, while the Y- and Z-axes denote the longitudinal and vertical axes of the vehicle 10, respectively. As shown in Fig. 2 and described above, the vehicle 10 comprises a plurality of inertial sensors, including the sensors 30A-30E of Fig. 1. With reference specifically to the sensors 30D, these devices are configured as accelerometers and serve to measure the dynamic linear acceleration of the vehicle 10 along its respective X- or Y-axis. A sensor 30E, such as a gyroscope, can be positioned on the vertical or Z-axis of the vehicle 10, with the sensor serving to detect or measure an actual yaw rate (RACTUAL) of the vehicle 10 as an additional element of the set of inertial data described above. With reference to Fig. 3, Table 40 describes in general terms a set of sensor input data supplied by sensors 30A-30E to the controller 32 of Fig. 1. Within the scope of the invention, the method 100 of Fig. 3 is executed only during a threshold braking event, i.e., during an active and continuous regenerative braking event (RBE); otherwise, the braking of the vehicle 10 is controlled as directed or commanded by the controller 32 using a standard or general brake control algorithm (not shown). As shown in Table 40, sensor 30A transmits the signals NF and NR to the controller 32, where the values ​​for these measurements are temporarily stored or recorded. Sensor 30B measures the total braking torque (OBT) commanded by a driver (see Fig. 1). Sensor 30C measures the steering angle (θS). The sensors 30D measure the linear acceleration (aX,Y) of the vehicle 10 of Fig.Figure 1 and Figure 2 represent the respective transverse (X-axis) and longitudinal (Y-axis) directions of the vehicle 10 of Figure 2. Finally, the sensor 30E measures the angular velocity or actual yaw rate (RACTUAL) of the vehicle 10 about its vertical or Z-axis, with the output of the sensor 30E being provided in degrees per second or radians per second. Using the sensor input signals from sensors 30A-E, the controller 32 can calculate various vehicle behavior characteristics during an active RBE and, based on these values, can calculate a maximum RBT, referred to below as RBTMAX, as described below with reference to Fig. 4. The controller 32 of Fig. 1 can selectively reduce the RBT ultimately applied during an active RBE by setting the value of RBTMAX to any value between zero and the theoretical maximum value permissible or possible based on the specific design of the engine / generator 17 and the ESS 19 of Fig. 1.In other words, input signals from some or all of the sensors 30A-E are used as sensor inputs to the controller 32, depending on the specific vehicle characteristic curve being determined, to determine a maximum size of an RBT that can be applied during the regenerative braking event or RBE without causing the vehicle 10 of Fig. 1 and Fig. 2 to oversteer or understeer. During normal braking operations, the maximum value, or RBTMAX, calculated by the controller 32 is expected to be essentially equal to the theoretical maximum value. However, during some braking events, such as an active ABS event on a surface with a low coefficient of friction or under other threshold braking conditions, the calculated value of RBTMAX may be smaller, down to and including zero. In the event that a zero value is applied to RBTMAX, all the requested or required braking, as determined by the OBT commanded by a driver in Fig. 1, can be provided by the friction braking system 37 using the friction braking torque, or FBT.The controller 32 can therefore selectively modify the value of RBTMAX from a zero value up to the theoretical maximum value depending on the measured and / or calculated vehicle behavior data. With reference to Fig. 4, the algorithm or method 100 of Fig. 1 is shown in more detail. Starting with step 102, method 100 comprises detecting, measuring, or otherwise determining the presence of an active regenerative braking (RBE) event. If an active RBE is detected, method 100 proceeds to step 104. In step 104, a set of inertial information or data is measured using the sensors 30A-E shown in Figures 1 and 2, as described above. Specifically, sensors 30A transmit signals describing the wheel speeds N1F, N2F, N1R, N2R; sensor 30B measures a force and / or displacement describing a driver-commanded total braking torque (OBT); sensor 30C measures the input steering angle (θS); sensors 30D measure the linear acceleration (aX,Y) of the vehicle 10; and sensor 30E measures the angular velocity or actual yaw rate (RACTUAL) of the vehicle 10. After measuring the set of chassis inertial data, procedure 100 proceeds simultaneously to steps 106, 108, 110, and 112. In step 106, method 100 comprises calculating a first set of vehicle behavior data, i.e., a wheel slip rate of wheels 15F, 15R relative to the road surface 50 of Fig. 1, as described above and simply abbreviated as 'slip' in Fig. 4. As a person skilled in the art understands, the wheel slip can be calculated using the measured wheel speeds NF and NR and the calculated vehicle speed V (see step 108). Method 100 then proceeds to step 114. In step 108, the procedure involves calculating a second set of vehicle behavior data, i.e., a speed V of vehicle 10 from Fig. 1, using the measured wheel speeds NF, NR, as described above. The procedure then proceeds to step 116. In step 110, the procedure involves calculating a third set of vehicle behavior data, i.e., a vehicle acceleration vector (VAV) for vehicle 10 of Fig. 1. Step 110 can be achieved using the measured linear accelerations (aX, aY) as described above. The procedure then proceeds to step 118. In step 112, the procedure involves calculating a fourth set of vehicle behavior data, namely a target yaw rate RDES for vehicle 10 of Fig. 1. As a person skilled in the art understands, a target yaw rate RDES can be calculated using the steering angle θS and the calculated vehicle speed V from step 108. The procedure then proceeds to step 120. In step 113, the steering angle θS measured in step 104 is compared with an associated steering angle threshold value, a calibrated value that may be stored in a lookup table readily accessible to the controller 32, or that may be calculated or determined otherwise. Since a person skilled in the art recognizes that a steering angle rate can be calculated from the measured steering angle θS, step 113 can also be performed by comparing the calculated steering angle rate with a steering angle rate threshold value. For simplicity, only the steering angle θS is shown in Fig. 4. If the steering angle θS or the calculated steering angle rate from step 104 exceeds the calibrated threshold value, the procedure 100 proceeds to step 121. Otherwise, the procedure 100 proceeds to step 123. In step 114, the wheel slip rate or slip calculated in step 106 is compared to an associated slip threshold, a calibrated value that may be stored in a lookup table readily accessible to controller 32, or that may be calculated or determined by other means. If the slip calculated in step 106 exceeds the calibrated threshold, procedure 100 proceeds to step 122. Otherwise, procedure 100 proceeds to step 123. In step 116, the calculated vehicle speed V from step 116 is compared to one of two associated vehicle speed thresholds, a calibrated value for a high speed and a low speed, which may be stored in a lookup table accessible to controller 32, or which may be calculated or determined otherwise. If the vehicle speed V calculated in step 116 exceeds the associated calibrated vehicle speed threshold, procedure 100 proceeds to step 124. Otherwise, procedure 100 proceeds to step 123. In step 118, the calculated vehicle acceleration vector (VAV) from step 118 is compared to an associated VAV threshold or VAV breakpoint, a calibrated value that can be stored in a lookup table accessible to Controller 32, or that can be calculated or determined otherwise. If the vehicle velocity vector (VAV) calculated in step 118 exceeds the calibrated VAV threshold or breakpoint, procedure 100 proceeds to step 126. Otherwise, procedure 100 proceeds to step 123. In step 120, the calculated target yaw rate (RDES) from step 120 is compared with the actual yaw rate RACTUAL, which was detected or measured by sensor 30E in Fig. 2 as part of step 104. If the actual yaw rate RACTUAL exceeds the calculated target yaw rate (RDES), procedure 100 continues to step 128. Otherwise, procedure 100 continues to step 123. In step 121, the measured steering angle θSan can be forwarded to or output from a table stored in or accessible to controller 32. A multiplier M1, ranging from 0 to 1, is then selected, with the exact value depending on the deviation between the measured steering angle θS and the calibrated threshold for that value. Once the multiplier M1 has been selected, procedure 100 continues to step 130. In step 122, the calculated slip from step 106 can be passed to or output to a table stored in or accessible to controller 32. A multiplier M2 is then selected, ranging from 0 to 1, with the exact value depending on the deviation between the calculated slip rate and the calibrated threshold for that value. Once the multiplier M2 has been selected, the procedure continues from step 100 to step 130. In step 123, the maximum regenerative braking torque, or RBTMAX, is set equal to the maximum theoretical value of the regenerative braking capability of the vehicle 10 shown in Fig. 1. This means that the value of RBTMAX is not limited by the procedure 100, so that any total braking torque (OBT) ordered by a driver is allocated to or distributed among a maximum available RBT, with any additional braking torque required being provided via the friction braking torque, or FBT, of the friction braking system 37. The procedure 100 is then terminated. In step 124, the calculated vehicle speed V from step 108 can be passed to or output from a table stored in or accessible to controller 32. A multiplier M3, ranging from 0 to 1, is then selected, its exact value depending on the deviation between the calculated vehicle speed and one of two calibrated thresholds for that speed. A first threshold can be used for a high speed, while a second threshold can be used for a low speed, with "high" and "low" being calibrated values. Once the multiplier M3 has been selected, procedure 100 continues to step 130. In step 126, the calculated vehicle acceleration vector (VAV) from step 110 can be passed to or output to a table stored in or accessible to controller 32. A multiplier M4, ranging from 0 to 1, is then selected, the exact value depending on the deviation between the calculated VAV and a calibrated VAV breakpoint (VAVBP). Once the multiplier M4 has been selected, procedure 100 continues to step 130. In step 128, a resulting yaw rate error value (ER) is calculated, where the resulting yaw rate error value (ER) is equal to the difference between the actual yaw rate (RACTUAL) detected by sensor 30E in Fig. 2 and the target yaw rate (RDES) determined in step 112. Procedure 100 then proceeds to step 130. In step 130, the method 100 uses all multipliers M1-M4 that were selected or calculated in steps 121, 122, 124, and 126 as described above, as well as the error value ER from step 128, and applies the multipliers and / or the error value ER to calculate a maximum regenerative braking torque (RBTMAX). The RBTMAX can be calculated or determined in various ways within the scope of the invention. The relative values ​​of the inertia values ​​measured in step 104 can be weighted equally or differently, depending on the intended concept of the vehicle 10. For example, the resulting wheel slip error (ES) from step 122 could be prioritized, thereby limiting the value for RBTMAX more aggressively when the resulting wheel slip error (ES) is calculated above a calibrated threshold. Such error value weighting can be used when the vehicle 10 is decelerating or braking on a surface with a relatively low coefficient of friction, such as when the road surface 50 of Fig. 1 is covered with ice or snow. Similarly, any of the other inertia values ​​can be weighted more or less heavily depending on the concept of the controller 32 and the vehicle 10 of Fig. 1, potentially influencing the choice of multipliers M1-M4.Alternatively, one can average all multipliers M1-M4 and the resulting wheel slip error (ES) to calculate an unweighted or weighted average multiplier and apply this value when calculating the value for RBTMAX. Although the best ways of carrying out the invention have been described in detail, those skilled in the field relating to this invention will recognize various alternative designs and embodiments for putting the invention into practice within the scope of the attached claims.

Claims

Method (100) for optimizing the behavior of a vehicle (10) with multiple road wheels (15F, 15R) and a regenerative braking capability designed for electronic braking of the vehicle (10) during an active regenerative braking (RBE) event, wherein the method (100) comprises: measuring (104) a set of inertial data of the vehicle (10), comprising a rotational speed (NF, NR) of each road wheel (15F, 15R), an input steering angle (θS) of the vehicle (10), a longitudinal and lateral acceleration (ay, ax) of the vehicle (10), and an actual yaw rate (RACTUAL) of the vehicle (10) during the active RBE; calculating (106, 108, 110, 112) a set of vehicle behavior data using the set of inertial data, which comprises determining a wheel slip rate of the road wheels. (15F, 15R), a vehicle speed (V) (10), a vehicle acceleration vector (VAV) and a target yaw rate (RDES) are calculated;the input steering angle (θS) of the vehicle (10), the wheel slip rate of the road wheels (15F, 15R) and the speed (V) of the vehicle (10) are compared with associated calibrated threshold data (113, 114, 116), the vehicle acceleration vector (VAV) is compared with an associated VAV holding point and the target yaw rate (RDES) is compared with the actual yaw rate (RACTUAL) in order to determine a deviation with reference to the corresponding calibrated threshold data for the input steering angle (θS), the wheel slip rate of the road wheels (15F, 15R), the speed (V) of the vehicle (10), the vehicle acceleration vector (VAV) and the target yaw rate (RDES);a maximum regenerative braking torque (RBT) is calculated, which includes applying a multiplier (M1, M2, M3, M4) ranging from 0 to 1 to the input steering angle (θS) of the vehicle (10), the wheel slip rate of the road wheels (15F, 15R), the speed (V) of the vehicle (10) and the vehicle acceleration vector (VAV) (121, 122, 124, 126), where the value of the respective multiplier (M1, M2, M3, M4) corresponds to the respective calculated deviation; a resulting yaw rate error value (ER) is calculated as a function of the target yaw rate (RDES) and the actual yaw rate (RACTUAL) (128); and the maximum RBT is calculated as a function of the input steering angle (θS) of the vehicle (10), the wheel slip rate of the road wheels (15F, 15R), the speed (V) of the vehicle (10) and the vehicle acceleration vector (VAV) to which the respective multiplier (M1, M2, M3, M4) has been applied, and the resulting yaw rate error value (ER) (130);and the maximum RBT is automatically applied during the active RBE (132). Method (100) according to claim 1, wherein the measuring (104) of a set of inertial data comprises measuring a rotation of the vehicle (10) with respect to a vertical axis (Z) of the vehicle (10). Method (100) according to claim 2, wherein calculating a set of vehicle behavior data comprises calculating (112) the target yaw rate (RDES) of the vehicle (10) using the input steering angle (θS). Method (100) according to claim 2, wherein calculating a set of vehicle behavior data comprises calculating (110) a vehicle acceleration vector (VAV) using the measured lateral acceleration (ax) and the measured longitudinal acceleration (ay). Method (100) according to claim 1, wherein the associated set of calibrated threshold data comprises the actual yaw rate (RACTUAL) of the vehicle (10), a threshold acceleration vector of the vehicle (10), a threshold speed of the vehicle (10), a threshold steering angle of the vehicle (10) and / or a threshold slip rate of the set of road wheels (15F, 15R). Method (100) according to claim 1, wherein the vehicle (10) comprises a friction braking system (37) for providing a friction braking torque (FBT), wherein the method (100) further comprises: determining a driver-commanded overall braking torque (OBT); and allocating the driver-commanded OBT between the maximum RBT and the FBT during the active RBE such that when the maximum RBT is zero, the driver-commanded OBT is provided only using the FBT. Vehicle (10) comprising: a chassis; a set of road wheels (15F, 15R) arranged with respect to the chassis; at least one electric motor / generator (17) used to apply a maximum regenerative braking torque (RBT) for electronic braking of the vehicle (10) during an active regenerative braking event (RBE); a friction braking system (37) used to provide a friction braking torque (FBT) for friction braking of the vehicle (10); a steering input device (16); a set of chassis inertia sensors (30A, 30B, 30C, 30D, 30E) used together to measure a set of chassis inertia data, which includes a rotational speed (NF, NR) of each road wheel (15F, 15R), an input steering angle (θS) of the steering input device (16), a The vehicle's acceleration value (ay, ax) (10) and actual yaw rate (RACTUAL) (10) are designed to include;and a controller (32) which is connected to and configured with the chassis inertia sensors (30A, 30B, 30C, 30D, 30E) to compute a set of vehicle behavior data using the set of chassis inertia data, wherein the set of vehicle behavior data includes a wheel slip rate of the road wheels (15F, 15R), a vehicle speed (V) (10), a vehicle acceleration vector (VAV), and a target yaw rate (RDES); wherein the controller (32) computes a resulting yaw rate error value (ER) as a function of the target yaw rate (RDES) and the actual yaw rate (RACTUAL);compares the input steering angle (θS) of the vehicle (10), the wheel slip rate of the road wheels (15F, 15R) and the speed (V) of the vehicle (10) with associated calibrated threshold data (113, 114, 116), compares the vehicle acceleration vector (VAV) with an associated VAV holdpoint and compares the target yaw rate (RDES) with the actual yaw rate (RACTUAL) to calculate a deviation for all data in the set of vehicle behavior data; applies a multiplier (M1, M2, M3, M4) ranging from 0 to 1 to each of the input steering angle (θS) of the vehicle (10), the wheel slip rate of the road wheels (15F, 15R), the speed (V) of the vehicle (10) and the vehicle acceleration vector (VAV), the value of the multiplier (M1, M2, M3, M4) corresponds to the respective calculated deviation;the maximum RBT as a function of the input steering angle (θS) of the vehicle (10), the wheel slip rate of the road wheels (15F, 15R), the speed (V) of the vehicle (10) and the vehicle acceleration vector (VAV) to which the respective multiplier (M1, M2, M3, M4) has been applied, and the resulting yaw rate error value (ER); and automatically applies the calculated maximum regenerative RBT using the at least one electric motor / generator (17) during active RBE. Vehicle (10) according to claim 7, wherein the controller (32) serves to determine a driver-commanded overall braking torque (OBT) using a sensor (30B) of the set of chassis inertia sensors (30A, 30B, 30C, 30D, 30E) and to assign the driver-commanded OBT between the maximum RBT and the FBT during the active RBE. Vehicle (10) according to claim 7, wherein the chassis has a transverse axis (X) and a longitudinal axis (Y), and wherein the set of chassis inertia sensors (30A, 30B, 30C, 30D, 30E) comprises: a first acceleration measuring device (30D) positioned on the transverse axis (X) to measure a lateral acceleration (ax) of the chassis as one element of the set of chassis inertia data; and a second acceleration measuring device (30D) positioned on the longitudinal axis (Y) to measure a longitudinal acceleration (ay) of the chassis as another element of the set of chassis inertia data. Vehicle (10) according to claim 9, wherein the set of chassis inertia sensors (30A, 30B, 30C, 30D, 30E) comprises a steering angle sensor (30C) designed to measure the input steering angle (θS). Vehicle (10) according to claim 10, wherein the controller (32) serves to calculate the target yaw rate (RDES) using the input steering angle (θS), to compare the target yaw rate (RDES) with a calibrated threshold yaw rate as an element of the set of associated threshold data, to determine the resulting yaw rate error (ER) and to calculate the maximum RBT using the resulting yaw rate error (ER). Vehicle (10) according to claim 7, wherein the controller (32) serves to calculate the slip rate of each road wheel of the set of road wheels (15F, 15R), to compare the slip rate with a calibrated threshold slip rate as an element of the set of associated threshold data, to determine a resulting slip rate error, and to automatically modify the requested RBT using the resulting wheel slip rate error. Control system for optimizing the steering behavior and stability of a hybrid electric vehicle (HEV) (10) during an active regenerative braking (RBE) event, wherein the HEV (10) has a chassis, a brake input device (11), multiple road wheels (15F, 15R), a steering input device (16), and a regenerative braking capability, wherein the control system comprises: multiple sensors (30A, 30B, 30C, 30D, 30E) which together serve to measure a set of chassis inertia data, wherein the sensors (30A, 30B, 30C, 30D, 30E) include a brake sensor (30B) which is connected to the brake input device (11) and serves to detect an operator-commanded total braking torque (OBT), wheel speed sensors (30A) which measure the rotational speeds (NF, NR) of each of the multiple road wheels (15F, 15R), a gyroscope (30E) used to measure the actual yaw rate (RACTUAL) of the HEV (10), a steering angle sensor (30C),which is connected to the steering input device (16) and serves to detect an input steering angle (θS) of the HEV (10), and / or comprises at least one acceleration measurement device (30D) that serves to measure a linear acceleration (ay, ax) of the HEV (10) with respect to an axis (X, Y) of the chassis; a controller (32) in conjunction with the multiple sensors (30A, 30B, 30C, 30D, 30E); wherein the controller (32): calculates a set of vehicle behavior data using information from the wheel speed sensors (30A), the steering angle sensor (30C) and the at least one acceleration measurement device (30D); compares the input steering angle (θS) of the vehicle (10), the wheel slip rate of the road wheels (15F, 15R) and the speed (V) of the vehicle (10) with associated calibrated threshold data (113, 114, 116),compares the vehicle acceleration vector (VAV) with an associated VAV holdpoint and compares the target yaw rate (RDES) with the actual yaw rate (RACTUAL) to determine a respective deviation; applies a respective multiplier (M1, M2, M3, M4) with a value ranging from 0 to 1 to all data in the set of vehicle behavior data, the value of the multiplier (M1, M2, M3, M4) corresponding to the respective calculated deviation; calculates a resulting yaw rate error value (ER) as a function of the target yaw rate (RDES) and the actual yaw rate (RACTUAL); calculates a maximum regenerative braking torque (RBT) as a function of all data to which the respective multiplier (M1, M2, M3, M4) has been applied and the resulting yaw rate error value (ER); and automatically applies the calculated maximum RBT during active RBE. Control system according to claim 13, wherein the at least one acceleration measuring device (30D) comprises: a first acceleration measuring device (30D) for measuring a linear acceleration (ax) of the landing gear along a transverse axis (X) of the landing gear; and a second acceleration measuring device (30D) for measuring a linear acceleration (ay) of the landing gear along a longitudinal axis (Y) of the landing gear. Control system according to claim 13, wherein the HEV (10) comprises a friction braking system (37) for providing a friction braking torque (FBT); wherein the control system is for allocating a driver-commanded total braking torque (OBT) between the maximum RBT and the FBT during the active RBE such that when the maximum RBT is zero, the driver-commanded OBT is provided only using the FBT. Control system according to claim 13, wherein the set of calibrated threshold data is stored in a lookup table.

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