Some electric power steering (EPS) systems use a torque sensor to determine driver-requested assist. If an event affects the functionality of the torque sensor, the system may not be able to provide full assist and revert to a reduced assist mode or loss of assist mode. When EPS is in normal operation, a torque sensor usually measures the driver intention. However, during a torque sensor failure, data representative of driver intention is unavailable.
According to one or more examples, a power steering system for providing motor torque assist command includes a rack torque estimation module that determines an estimated rack torque value based on a motor angle, and a motor velocity; a driver intent detection module that computes a disturbance torque scaling factor based on the estimated rack torque value; and a blend module that generates the motor torque assist command based on a scaled value of the estimated rack torque value using the disturbance torque scaling factor.
According to one or more examples, a method for providing motor torque assist command by a power steering system, includes determining a estimated rack torque value based on a motor angle, and a motor velocity; computing a disturbance torque scaling factor based on the estimated rack torque value; and generating the motor torque assist command based on a scaled value of the estimated rack torque using the disturbance torque scaling factor.
According to one or more examples, a power steering system for providing driver assistance torque includes a torque sensor configured to detect a driver torque signal from a handwheel of the power steering system; and a control module that, in response to the torque sensor operating without a failure, determines a first estimated rack torque value based on a motor angle, a motor velocity, and the driver torque signal; and generates a first motor torque assist command based on the first estimated rack torque value. The control module, in response to detecting a failure of the torque sensor, determines a second estimated rack torque value based on the motor angle, and the motor velocity (without the driver torque signal); computes a disturbance torque scaling factor based on the second estimated rack torque value; and generates a second motor torque assist command based on a scaled value of the second estimated rack torque value using the disturbance torque scaling factor.
The subject matter, which is regarded as the invention, is particularly pointed out and distinctly claimed in the claims at the conclusion of the specification. The foregoing and other features, and advantages of the invention are apparent from the following detailed description taken in conjunction with the accompanying drawings in which:
As used herein the terms module and sub-module refer to one or more processing circuits such as an application specific integrated circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and memory that executes one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality. As can be appreciated, the sub-modules described below can be combined and/or further partitioned.
The technical solutions described herein facilitate a power steering system in a vehicle, such as an automobile to provide an assisting force or torque so that a driver of the vehicle can provide lesser effort when turning a steering wheel of the vehicle when driving. Typically, the power steering system provides the assisting force based on a torque sensor that determines the driver requested assist. However, if the torque sensor is absent, disabled, or damaged, or in any other case of failure, the power steering system may not provide the assisting force, which will cause the driver to apply higher than usual torque to the steering. The technical solutions described herein solve such technical problems by computing the assisting force by determining an intention of the driver based on a rack force (kingpin torque) estimator module, without relying on the torque sensor. In one or more examples, the power steering system computes the assisting force as described herein in the background, and in response to detecting a failure of the torque sensor, the power steering system switches to using the assisting force as described herein.
Referring now to the Figures, where the invention will be described with reference to specific embodiments, without limiting same,
As shown in
A control module 40 receives the one or more sensor signals input from sensors 31, 32, 33, and may receive other inputs, such as a vehicle speed signal 34. The control module 40 generates a command signal to control the steering actuator motor 19 of the steering system 12 based on one or more of the inputs and further based on the steering control systems and methods of the present disclosure. The steering control systems and methods of the present disclosure apply signal conditioning and perform friction classification to determine a surface friction level 42 as a control signal that can be used to control aspects of the steering system 12 through the steering assist unit 18. The surface friction level 42 can also be sent as an alert to an ABS 44 and/or ESC system 46 indicating a change in surface friction, which may be further classified as an on-center slip (i.e., at lower handwheel angle) or an off-center slip (i.e., at higher handwheel angle) as further described herein. Communication with the ABS 44, ESC system 46, and other systems (not depicted), can be performed using, for example, a controller area network (CAN) bus or other vehicle network known in the art to exchange signals such as the vehicle speed signal 34.
The torque estimation module 220 may be a static tire torque estimator or a rolling tire torque estimator. Other examples may use any other technique to predict the rack torque, such as in an empirical manner, by using a lookup table, or by using a model based approach, and so on. The static tire motor torque estimator computes the rack torque 222 when the vehicle speed is below a predetermined level, such as less than or equal to 10 KPH, 15 KPH, 20 KPH, or any other such predetermined speed. The rolling tire motor torque estimator computes the rack torque 222 when the vehicle speed is above the predetermined level. In one or more examples, the control module 40 includes two separate rack torque estimator modules, a first static tire rack torque estimator and a second rolling tire rack torque estimator, which operate independently depending on the vehicle speed. Alternatively, the single rack torque estimation module 220 computes the rack torque 222 using a different algorithm depending on the vehicle speed. In one or more examples, the rack torque 222 may be estimated using more than two separate algorithms depending on the vehicle speed being in different ranges, such as 0-20 KPH, 20-40 KPH, 40-60 KPH, or the like. Additionally, or alternatively a measured rack torque (using strain gauge or other sensors) is used as an input for estimating the rack torque 222.
The control module 40 generates a motor torque assist command 225 based on the estimated rack torque 222. For example, the control module 40 may include a blend module 230 that uses one or more scaling factors to scale the estimated rack torque 222 to generate the motor torque assist command 225. The blend module 230 may be a multiplier in one or more examples. It is understood that a multiplier is just one example of the blend module 230 and that in one or more examples, the control module 40 may include additional, or alternative components to generate the motor torque assist command 225 based on the estimated rack torque 222. The motor torque assist command 225 causes the steering system 12 to apply a force to assist the driver that is driving the vehicle, by facilitating the driver to apply lesser force when turning/moving the handwheel 14.
In addition, the blend module 230 receives a disturbance torque scaling factor (Tdis-SF) 215 generated by the driver intent detection module 210 according the technical solutions described herein. The blend module 230 uses the disturbance torque scaling factor 215 to scale the assist command 225. In one or more examples, the blend module 230 uses the disturbance torque scaling factor 215 if the vehicle speed is below a predetermined threshold, such as 20 KPH. In one or more examples, the disturbance torque scaling factor 215 may have a value of 0 or 1. Thus, the disturbance torque scaling factor 215 may act as to either cancel the assist command 225 (when 0), or continue to apply the assist command as is (when 1). In one or more examples, the disturbance torque scaling factor 215 may have a value from a predetermined range, such as 0 to 1. The driver intent detection module 210 selects a value from the predetermined range based on a rate of change of a disturbance torque that the driver intent detection module 210 computes, as described herein.
The driver intent detection module 210 computes the Tdis-SF 215 using the estimated rack torque 222 as input. The driver intent detection module 210 computes a disturbance torque based on the signals from the sensors of the steering system 12, thus incorporating uncertainties Tuncertainty in the result. For example, as illustrated in
Further, the driver intent detection module 210 scales the inputs to the disturbance compute module 410 to match units of the hand-wheel coordinate system. For example, the driver intent detection module 210 uses a gain value defined as N_AM to scale the inputs, where N_AM is a ratio between motor rotation speed and handwheel (HW) rotation speed. In addition, the driver intent detection module 210 may use a constant term ‘eff’, which indicates a mechanical efficiency between the motor and rack. In one or more examples, as shown in
The disturbance torque modeler 510 may implement the extended state observer algorithm. The term extended state refers to the addition of unknown inputs to system states. In one approach, the system (e.g., the steering system 12) may contain between six to eight state variables, however it is understood any number of variables may be used as well. Some examples of state variables include, for example, position, and velocity. The extended state observer may be expressed by equation 1 as:
{circumflex over ({dot over (x)})}obs=Aobs{circumflex over (x)}obs+Bobsu+L(y−ŷ) (1)
where the cap or hat symbol “^” is used to indicate an estimated signal (e.g., a calculated or predicted system output), and the subscript “obs” indicates observed. Specifically, xobs refers to a state of the steering system 12, and contains state variables that represent values inside the steering system 12. The term {circumflex over (x)}obs refers to a calculated state of the steering system 12. The term {circumflex over ({dot over (x)})}obs represents the rate of change of the system state, or a state change (e.g., the differentiation of {circumflex over (x)}obs). The term u refers to system input. The term y refers to system output. The term Aobs refers to a system matrix, and determines how the current state (e.g., {circumflex over (x)}obs) affects the state change; {circumflex over ({dot over (x)})}obs. The term Bobs represents a control matrix, and determines how the system input u affects the state change {circumflex over ({dot over (x)})}obs. L represents the observer gain matrix, and determines how an error e between a measured system output y and a calculated system output ŷ affects the state change {circumflex over ({dot over (x)})}obs. Finally, the term Cobs (not expressed in equation 1) refers to an output matrix, and calculates system output ŷ using the calculated state {circumflex over (x)}obs.
Referring to
The Tdis modeler 510 includes a subtractor component 615 that receives the input y 502 and the estimated output ŷ 610 to compute the difference y-ŷ. The output difference is multiplied by the matrix L and passed to an adder 650. The adder 650 also receives the input u 505 after being scaled using the predetermined Bobs matrix to generate the term Bobs·u, as shown at block 605. The adder component 650 receives, as a third input the estimated states {circumflex over (x)} 612 after being scaled using the predetermined Aobs matrix. The adder component 650, thus, adds the three terms that are on the right-hand-side of Equation 1. The output of the adder 650 provides the vector {circumflex over ({dot over (x)})}obs 655 that represents a rate of change of the system state, which is integrated by an integrator 660 to output a vector of the estimated states {circumflex over (x)} 612. Multiplying the vector of the estimated states {circumflex over (x)} 612 with a selector matrix P provides the estimated Tdis 515 as the output of the Tdis modeler, as shown at block 670.
Referring back to
The estimated disturbance torque rate Tdis 415 matches measured torsion bar torque (Ttbar) well as long as the error Tuncertainty is close to zero. However, when the error Tuncertainty is significant (for example, >=0.05), an offset error is introduced between Ttbar and Tdis. Hence, using Tdis directly as a main control signal to provide the assist command 225 may lead to incorrect estimation of the driver torque signal. Accordingly, the technical solutions described herein use a rate of change of Tdis 415, to predict the driver intention.
For example, the disturbance compute module 410 computes a delta-Tdis value 550 to use the rate of change of filtered-Tdis 415. The disturbance torque compute module 410 computes the delta-Tdis value 550 by computing a difference between the filtered-Tdis 415 and a delayed Tdis value 552. The delayed Tdis value 552 is computed by passing the Tdis value 415 through a delay component 530, which may be a unit delay component. The delta-Tdis value 550 represents an instantaneous change in the driver steering input.
The driver intent detection module 210 uses the delta-Tdis value 550 to compute the scalar output Tdis-SF 215 by passing the delta-Tdis value 550 to the scaling module 420, which combines the disturbance torque rate with the previous assist command 242 to provide the torque disturbance scaling factor Tdis-SF 215.
Thus, the scaling module 420, and the driver intent detection module 210 provides the Tdis-SF 215 scalar value, which scales down the assist command when the estimated disturbance input is in opposite direction to the assist command 225. As described earlier, the delta-Tdis 550 value is used to predict the driver intent. Accordingly, when the sign of the delta-Tdis 550 value is opposite that of the previous assist command 225, it is indicative that an assist command opposite to the driver intent is being provided. Accordingly, the assist command is scaled down to a low value, as shown at block 712. In one or more examples, the assist command is negated or cancelled, for example if the scalar used in block 712 is 0 (zero). Alternatively, if the delta-Tdis 550 value and the previous assist command 242 are in the same direction, that is have the same sign, the assist command is not altered, for example by using a scalar value close to 1, as shown at block 715.
The technical solutions described herein provide a power steering system that predicts a disturbance torque rate (Tdis) that is inclusive of driver torque and un-modeled rack torque. Further, the technical solutions monitor changes in the computed Tdis signal to determine changes in driver intent. The power steering system implementing the technical solutions described herein facilitates predicting driver intent when the driver moves a steering wheel of the vehicle even in case of failure or absence of a driver torque signal. The driver torque signal is generally received from a torque sensor in the power steering system. Accordingly, by implementing the technical solutions described herein, the power steering system is able to continue to provide torque assistance in case the torque sensor fails.
In one or more examples, the power steering system uses the predicted disturbance torque rate to provide the torque assistance in case the vehicle is travelling at a speed below a predetermined threshold speed, such as less than 20 KPH. The predetermined threshold speed is representative of a speed value below which the change in the disturbance torque reflects a change in the driver intentions.
The technical solutions described herein, thus, facilitate techniques for using EPS signals such as motor angle, motor velocity, (other than the driver torque Ttbar signal) to predict a disturbance torque Tdis that is representative of the Ttbar signal (and un-modeled system dynamics, which may be caused by non-linearity, error, and signal noise). The technical solutions further use existing motor command and a derivative of the Tdis to predict a driver intent signal, in case of absence or failure of the driver torque sensor. Further yet, the technical solutions facilitate scaling down an assist command that provides torque assistance to the steering wheel using a scaling factor based on the driver intent signal. Accordingly, the technical solutions described herein facilitate scaling down the assist command if direction of assist is opposite to Ttbar direction. The technical solutions described herein, thus, facilitate an improved tuning for assist in a power steering system used in a vehicle.
The present technical solutions may be a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present technical solutions.
Aspects of the present technical solutions are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the technical solutions. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions.
The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present technical solutions. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the Figures. For example, two blocks shown in succession, in fact, may be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions.
It will also be appreciated that any module, unit, component, server, computer, terminal or device exemplified herein that executes instructions may include or otherwise have access to computer readable media such as storage media, computer storage media, or data storage devices (removable and/or non-removable) such as, for example, magnetic disks, optical disks, or tape. Computer storage media may include volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information, such as computer readable instructions, data structures, program modules, or other data. Such computer storage media may be part of the device or accessible or connectable thereto. Any application or module herein described may be implemented using computer readable/executable instructions that may be stored or otherwise held by such computer readable media.
While the technical solutions are described in detail in connection with only a limited number of embodiments, it should be readily understood that the technical solutions are not limited to such disclosed embodiments. Rather, the technical solutions can be modified to incorporate any number of variations, alterations, substitutions or equivalent arrangements not heretofore described, but which are commensurate with the spirit and scope of the technical solutions. Additionally, while various embodiments of the technical solutions have been described, it is to be understood that aspects of the technical solutions may include only some of the described embodiments. Accordingly, the technical solutions are not to be seen as limited by the foregoing description.
Number | Name | Date | Kind |
---|---|---|---|
4660671 | Behr et al. | Apr 1987 | A |
4800974 | Wand et al. | Jan 1989 | A |
4874053 | Kimura et al. | Oct 1989 | A |
5029466 | Nishihara et al. | Jul 1991 | A |
5473539 | Shimizu et al. | Dec 1995 | A |
5482129 | Shimizu | Jan 1996 | A |
5709281 | Sherwin et al. | Jan 1998 | A |
5919241 | Bolourchi et al. | Jul 1999 | A |
5927421 | Fukada | Jul 1999 | A |
5948030 | Miller et al. | Sep 1999 | A |
5992557 | Nakamura et al. | Nov 1999 | A |
6032091 | Noro et al. | Feb 2000 | A |
6152254 | Phillips | Nov 2000 | A |
6223852 | Mukai et al. | May 2001 | B1 |
6250419 | Chabaan et al. | Jun 2001 | B1 |
6298941 | Spadafora | Oct 2001 | B1 |
6370459 | Phillips | Apr 2002 | B1 |
6425454 | Chabaan et al. | Jul 2002 | B1 |
6588541 | Norman et al. | Jul 2003 | B2 |
6687590 | Kifuku et al. | Feb 2004 | B2 |
6690137 | Iwaji et al. | Feb 2004 | B2 |
6742620 | Eidam et al. | Jun 2004 | B2 |
6799656 | Kimura et al. | Oct 2004 | B2 |
6959970 | Tseng | Nov 2005 | B2 |
7040450 | Nagase et al. | May 2006 | B2 |
7558661 | Sundaram et al. | Jul 2009 | B2 |
7596441 | Yokota et al. | Sep 2009 | B2 |
7613258 | Yu et al. | Nov 2009 | B2 |
7885750 | Lu | Feb 2011 | B2 |
7954593 | Dornhege et al. | Jun 2011 | B2 |
7974754 | Nakatsu | Jul 2011 | B2 |
7975801 | Tashiro | Jul 2011 | B2 |
8010252 | Getman et al. | Aug 2011 | B2 |
8108105 | Saruwatari et al. | Jan 2012 | B2 |
8165770 | Getman et al. | Apr 2012 | B2 |
8170751 | Lee | May 2012 | B2 |
8175771 | Ukai et al. | May 2012 | B2 |
8219283 | Recker et al. | Jul 2012 | B2 |
8548667 | Kaufmann et al. | Oct 2013 | B2 |
8571759 | Oblizajek et al. | Oct 2013 | B2 |
8666605 | DeLarche et al. | Mar 2014 | B2 |
8666607 | Kojo | Mar 2014 | B2 |
8798864 | Champagne et al. | Aug 2014 | B2 |
8825301 | Sugawara et al. | Sep 2014 | B2 |
8843276 | Kojo et al. | Sep 2014 | B2 |
8903606 | Kleinau et al. | Dec 2014 | B2 |
8977433 | Kojima | Mar 2015 | B2 |
8977436 | Endo et al. | Mar 2015 | B2 |
8977437 | Tamaizumi et al. | Mar 2015 | B2 |
9067601 | Itabashi et al. | Jun 2015 | B2 |
9327761 | Tsubaki | May 2016 | B2 |
9387875 | Shimizu et al. | Jul 2016 | B2 |
9409595 | Varunjikar et al. | Aug 2016 | B2 |
9452775 | Tamura et al. | Sep 2016 | B2 |
9540040 | Varunjikar et al. | Jan 2017 | B2 |
9540044 | Kaufmann et al. | Jan 2017 | B2 |
9545945 | Akatsuka et al. | Jan 2017 | B2 |
9676409 | Champagne et al. | Jun 2017 | B2 |
20020005316 | Tokumoto | Jan 2002 | A1 |
20020026267 | Kifuku | Feb 2002 | A1 |
20020092696 | Bohner et al. | Jul 2002 | A1 |
20020177932 | Kifuku et al. | Nov 2002 | A1 |
20020179362 | Norman et al. | Dec 2002 | A1 |
20030030404 | Iwaji et al. | Feb 2003 | A1 |
20030074120 | Kleinau | Apr 2003 | A1 |
20030150366 | Kaufmann et al. | Aug 2003 | A1 |
20040024505 | Salib et al. | Feb 2004 | A1 |
20040055810 | Chabaan | Mar 2004 | A1 |
20040099469 | Koibuchi et al. | May 2004 | A1 |
20040117088 | Dilger | Jun 2004 | A1 |
20040262063 | Kaufmann | Dec 2004 | A1 |
20050189163 | Barton et al. | Sep 2005 | A1 |
20050206224 | Lu | Sep 2005 | A1 |
20050206229 | Lu et al. | Sep 2005 | A1 |
20050246085 | Salib et al. | Nov 2005 | A1 |
20050256620 | Kato | Nov 2005 | A1 |
20060060412 | Bolourchi | Mar 2006 | A1 |
20060069481 | Kubota et al. | Mar 2006 | A1 |
20070299580 | Lin | Dec 2007 | A1 |
20080147276 | Pattok et al. | Jun 2008 | A1 |
20090024281 | Hwang | Jan 2009 | A1 |
20090105907 | Yamaguchi et al. | Apr 2009 | A1 |
20090125186 | Recker et al. | May 2009 | A1 |
20090143938 | Nishimura | Jun 2009 | A1 |
20090216407 | Cottard et al. | Aug 2009 | A1 |
20090240389 | Nomura et al. | Sep 2009 | A1 |
20090271075 | Hales | Oct 2009 | A1 |
20090292421 | Williams et al. | Nov 2009 | A1 |
20090294206 | Oblizajek et al. | Dec 2009 | A1 |
20100100283 | Hales et al. | Apr 2010 | A1 |
20100286869 | Katch et al. | Nov 2010 | A1 |
20110010054 | Wilson-Jones | Jan 2011 | A1 |
20110022272 | Hung et al. | Jan 2011 | A1 |
20110213527 | Itabashi | Sep 2011 | A1 |
20110218706 | Mori et al. | Sep 2011 | A1 |
20110282552 | Gebregergis et al. | Nov 2011 | A1 |
20120041644 | Turner | Feb 2012 | A1 |
20120199414 | Shimizu et al. | Aug 2012 | A1 |
20120232754 | Champagne et al. | Sep 2012 | A1 |
20120261209 | Shiino | Oct 2012 | A1 |
20120312627 | Morishita et al. | Dec 2012 | A1 |
20130024072 | Michelis et al. | Jan 2013 | A1 |
20130030654 | Oblizajek et al. | Jan 2013 | A1 |
20130073146 | Konomi et al. | Mar 2013 | A1 |
20130124048 | Gruener | May 2013 | A1 |
20130131926 | Champagne et al. | May 2013 | A1 |
20130151066 | Koukes et al. | Jun 2013 | A1 |
20130201047 | Tsai et al. | Aug 2013 | A1 |
20130261894 | Kojima | Oct 2013 | A1 |
20140005894 | Aoki | Jan 2014 | A1 |
20140149000 | Tamura et al. | May 2014 | A1 |
20140257641 | Champagne et al. | Sep 2014 | A1 |
20140303848 | Bean | Oct 2014 | A1 |
20140324294 | Champagne | Oct 2014 | A1 |
20150012182 | Flehmig et al. | Jan 2015 | A1 |
20150151783 | Kitazume | Jun 2015 | A1 |
20150171667 | Kai et al. | Jun 2015 | A1 |
20150191200 | Tsubaki et al. | Jul 2015 | A1 |
20160001810 | Tsubaki | Jan 2016 | A1 |
20160031481 | Birsching | Feb 2016 | A1 |
20160075371 | Varunjikar et al. | Mar 2016 | A1 |
20160107679 | Kimura et al. | Apr 2016 | A1 |
20160229446 | Tamaizumi | Aug 2016 | A1 |
20160288825 | Varunjikat et al. | Oct 2016 | A1 |
20170066472 | Wang et al. | Mar 2017 | A1 |
20170066473 | Yu et al. | Mar 2017 | A1 |
20170158228 | She | Jun 2017 | A1 |
20170232998 | Ramanujam et al. | Aug 2017 | A1 |
20170355396 | Varunjikar et al. | Dec 2017 | A1 |
Number | Date | Country |
---|---|---|
1442336 | Sep 2003 | CN |
1651293 | Aug 2005 | CN |
1935576 | Mar 2007 | CN |
100999223 | Jul 2007 | CN |
101142548 | Mar 2008 | CN |
101218146 | Jul 2008 | CN |
101434258 | May 2009 | CN |
101522504 | Sep 2009 | CN |
101683867 | Mar 2010 | CN |
101734277 | Jun 2010 | CN |
102019957 | Apr 2011 | CN |
102556065 | Jul 2012 | CN |
102806942 | Dec 2012 | CN |
102917939 | Feb 2013 | CN |
103079934 | May 2013 | CN |
102556152 | Jul 2013 | CN |
104044586 | Sep 2014 | CN |
104334439 | Feb 2015 | CN |
104755358 | Jul 2015 | CN |
19634728 | Apr 1998 | DE |
19824914 | Dec 1999 | DE |
19912169 | Jul 2000 | DE |
10344279 | Apr 2004 | DE |
102005004726 | Aug 2006 | DE |
102008051552 | Apr 2009 | DE |
102008036001 | Feb 2010 | DE |
102013112901 | May 2015 | DE |
0353995 | Feb 1990 | EP |
1127775 | Aug 2001 | EP |
1508495 | Feb 2005 | EP |
1623907 | Feb 2006 | EP |
1995150 | Nov 2008 | EP |
2028080 | Feb 2009 | EP |
1808359 | Apr 2009 | EP |
2184218 | May 2010 | EP |
2275323 | Jan 2011 | EP |
2223838 | Nov 2011 | EP |
2492168 | Aug 2012 | EP |
2497698 | Sep 2012 | EP |
2454788 | May 2009 | GB |
2001106099 | Apr 2001 | JP |
2003002222 | Jan 2003 | JP |
3712876 | Nov 2005 | JP |
2006143151 | Jun 2006 | JP |
3819261 | Sep 2006 | JP |
2006248250 | Sep 2006 | JP |
2007514602 | Jun 2007 | JP |
2009006985 | Jan 2009 | JP |
2009051292 | Mar 2009 | JP |
2011051409 | Mar 2011 | JP |
2006083578 | Jul 2006 | KR |
2005097577 | Oct 2005 | WO |
2011148240 | Dec 2011 | WO |
2012014399 | Feb 2012 | WO |
2012066704 | May 2012 | WO |
2012176553 | Dec 2012 | WO |
Entry |
---|
AFCP Decision w/Art dated Dec. 29, 2016. |
CN Application No. 2014106438448 Second Office Action, dated Apr. 24, 2017, 9 pages. |
CN Application No. 201510617600 Office Action dated Apr. 12, 2017, 8 pages. |
CN Application No. 201510742251 First Office Action dated Apr. 26, 2017, 8 pages. |
CN Patent Application No. 201210586416.7 4th Office Action dated Sep. 21, 2016, 8 pages. |
English Translation of Chinese Office Action for related CN Application No. 201410643844.8; dated Aug. 22, 2016; 26 pages. |
EP Search Report dated Apr. 14, 2016 in related EP Application No. 15184544.3-1755 dated Mar. 14, 2016, 7 pages. |
European Office Action for Application No. 15173865.5-1755, dated Sep. 28, 2017 (8 pp.). |
Final Office Action dated Mar. 18, 2016. |
Final Office Action dated May 29, 2015. |
Final Office Action dated Jul. 27, 2017. |
Final Office Action, dated Aug. 25, 2016. |
Final Rejection dated Mar. 3, 2016. |
Gillespie, T.D.; “Fundamentals of Vehicle Dynamics”; Warrendale, PA; Society of Automotive Engineers; 1992; ISBN 1560911999, 9781560911999; pp. 205-206. |
Hsu, Yung-Hsiang Judy, “Estimation and Control of Lateral Tire Forces using Steering Torque”; Dissertaion of Stanford University, Mar. 2009; 191 pages. |
NFOA, dated Feb. 11, 2016. |
Non Final OA dated Mar. 17, 2017. |
Non-Final Office Action dated Jan. 5, 2017. |
Non-Final Office Action dated Oct. 21, 2015. |
Non-Final Office Action dated Aug. 26, 2016. |
Non-Final Office Action for U.S. Appl. No. 14/933,461, dated Oct. 3, 2017 (33 pp). |
Non-Final Office Action, dated Oct. 3, 2017. |
OA dated Sep. 28, 2017. |
Office Action dated Aug. 22, 2016. |
U.S. Appl. No. 13/299,407, filed Nov. 18, 2011, titled Road Wheel Disturbance Rejection. |
U.S. Appl. No. 13/792,897, filed Mar. 11, 2013, titled “Road Wheel Disturbance Rejection Based on Hand Wheel Acceleration”. |
Van der Jagt, Pim; “Prediction of Steering Efforts During Stationary or Slow Rolling Parking Maneuvers”; Ford Forschungszentrum Aachen GmbH.; Oct. 27, 1999; 20 pages. |
Ansgar Rehm, Vehicle Velocity Estimation by Dynamic Inversion of Wheel Force Generation; Control Conference (ECC), 2009 European Year: 2009; pp. 4798-4803. |
China Patent Application No. 201210586416.7 3rd Office Action dated Feb. 15, 2016, 14 pages. |
D.I. Katzourakis, et al.; “Steering Force Feedback for Human-Machine-Interface Automotive Experiments”; IEEE Transactions on Instrumentation and Measurement, vol. 60, No. 1, pp. 32-43, Jan. 2011. |
English Translation of Chinese Office Action for related CN Application No. 20121058416.7; dated Dec. 3, 2014; 15 pages. |
English Translation of Chinese Office Action for related CN Application No. 201210586416.7; dated Aug. 12, 2015; 14 pages. |
English Translation of CN Office Action & Search Report for related CN Application No. 201410086920.X; dated Nov. 5, 2015; 10 pages. |
English Translation of CN Office Action & Search Report for related CN Application No. 2014110331120.X; dated Nov. 30, 2015; 9 pages. |
EP Search Report for related EP Application No. 14166178.5; dated Aug. 22, 2014; 7 pages. |
European Patent Application No. 14192466.2; office action dated Feb. 5, 2016; 7 pages. |
Extended EP Search Report for related EP Application No. 12192967.3, dated Apr. 2, 2013; 8 pages. |
Extended EP Search Report for related EP Application No. EP14192466.2; dated Apr. 9, 2015; 8 pages. |
Extended EP Search report from related Application No. 151845443-1755: dated Mar. 14, 2016; 7 pages. |
Extended European Search Report for related EP Application No. 14156987.1; dated Jan. 21, 2015; 8 pages. |
Extended European Search Report for related EP Application No. 15173865.5; dated Nov. 23, 2015; 10 pages. |
J.C.F. de Winter, et al.; “A Two-Dimensional Weighting Function for a Driver Assistance System”; IEEE Transactions on Systems, Man and Cybernetics B, Cybern., vol. 38, No. 1, pp. 189-198, Feb. 2008. |
Katzourakis, D.I., et al.; “Road-Departure Prevention in an Emergency Obstacle Avoidance Situation”; IEEE Transactions on Systems, Man, and Cybernetics: Systems; vol. 44, Issue 5; vol. 44, No. 5, pp. 621-629. |
Peroutka, et al., Design Considerations for Control of Traction Drive with Permanent Magnet Synchronous Machine; Power Electronics and MOtion Control Conference, 2008, EPE-PEMC 2008, 13th Year: 2008; pp. 1529-1534, DOI: 10.1109/EPEPEMC.2008.4635484. |
Pornsarayouth, S., et al., Sensor Fusion of Delay and Non-delay Signal using Kalman Filter with Moving Covariance, Robotics and Biomimetics, 2008, ROBIO 2008, IEEE International Conference on: Year 2009; pp. 2045-2049, DOI: 10.1109/ROBIO.2009.4913316. |
Wilhelm, et al., Friction Compensation Control for Power Steering, Control Systems Technology, IEEE Transactions on; Year: 2015, vol. PP, Issue: 99; pp. 1-14, DOI:10.1109/TCST.2015.2483561. |
English Abstract of Li Yong et al., Control Technique of Vehicle Stability, Jan. 31, 2013, Mechanical Industry Press, 1 page. |
Gillespie, Thomas D., Fundamentals of Vehicle Dynamics, 2000, pp. 201-208, Society of Automotive Engineers—Authorized Simplified Chinese translation edition by Scientific & Technical Publishing Co., 2006, pp. 138-142 (correspond to original pp. 201-208). |
Gillespie, Thomas D., Fundamentals of Vehicle Dynamics, 2000, pp. 201-208, Society of Automotive Engineers. |
Li Yong et al., Control Technique of Vehicle Stability, Jan. 31, 2013, pp. 137-138, Mechanical Industry Press. |
English Translation of Chinese Office Action & Search Report for Chinese Application No. 201611113750.5 dated Apr. 25, 2018, 10 pages. |
English Translation of Chinese Office Action & Search Report for Chinese Application No. 201611113886.6 dated Apr. 27, 2018, 7 pages. |
DE Application No. 102016116291.4 Translation of Office Action dated Mar. 5, 2018, 5 pages. |
DE Application No. 102016116292.2 Translation of Office Action dated Mar. 5, 2018, 5 pages. |
Athira Vijayan et al., Precise Tuning for Power Steering, International Conference on Wireless Communications, Signal Processing and Networking (IEEE WiSPNET), 2017, pp. 2309-2313. |
Dongpil Lee et al., Disturbance Adaptive Steering Wheel Torque Control for Enhanced Path Tracking of Autonomous Vehicles, American Control Conference (ACC), May 24-26, 2017, pp. 2321-2326, Seattle, WA USA. |
Frederic Wilhelm et al., Friction Compensation Control for Power Steering, IEEE Transactions on Control Systems Technology, Jul. 2016, pp. 1354-1367, vol. 24, No. 4, IEEE Journals & Magazines. |
Luis Daniel Sosa Ruiz et al., Design and Construction of a Passive Mechanism for Emulation of Load Forces in an Electric Power Steering System, Sep. 20-22, 2017, pp. 1-6, 2017 14th IEEE International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), Mexico City, Mexico. |
Number | Date | Country | |
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20170355396 A1 | Dec 2017 | US |