Any and all applications for which a foreign or domestic priority claim is identified in the Application Data Sheet as filed with the present application are hereby incorporated by reference under 37 CFR 1.57.
The application relates to devices and methods for detecting residual braking torque, e.g., in a vehicle.
Residual braking torque is the braking torque, often having relatively small values, in a vehicle due to the unintended interaction between the brake pad and the disc while the vehicle is not actually braking.
This condition can be caused by abnormal operation of the brake caliper to maintain a residual contact between the disc and the pad after braking.
The persistence of this contact condition, although typically small, can maintain a nearly constant residual braking torque that has a considerable effect on fuel consumption and brake pad wear over the long term.
EU6 715/2007/EC standards on CO2 emissions establish significantly more stringent limits on emissions, forcing vehicle manufacturers to seek innovative solutions to reduce them.
Embodiments described herein are configured to limit, measure, estimate, and/or prevent residual braking torque, e.g., to reduce fuel consumption, and thus, the resulting emissions of the vehicle.
The present application describes devices and methods that can estimate residual braking torque in a vehicle due to undesirable interactions between the brake pad and the disc (or drum), e.g., for each brake pad.
Disclosed devices and methods can enable real-time estimates of residual braking torque.
Disclosed devices and methods enable estimates of residual braking torque that can detect the minimum clearance between the brake pads and the disc, to help reduce brake delays.
Disclosed devices and methods can estimate residual braking torque in a manner compatible with on-board installations and applications.
According to additional disclosed embodiments, devices and methods can estimate residual braking torque in a manner compatible with on-board installations and applications, e.g., connecting a means of connection and a means of recording to a remotely controlled system.
According to additional embodiments, disclosed devices and methods use a method to estimate the residual torque between the braking (e.g., brake pad including friction material and/or support plate) and braked elements (e.g., brake disc or drum) of a vehicle.
According to certain aspects, the method can be implemented in whole or in part by one or more computing devices (e.g., an electronic control unit of a vehicle comprising one or more computer hardware processors). The method can include. acquiring the temperature value of said braking element. The method can further include determining whether this brake is activated when the temperature value is acquired. The method can further include accepting the acquired temperature value if said brake is not activated at said acquisition time. If the acquired temperature value is accepted, the method can include automatically calculating a reference temperature using input from an N-dimensional calculation model with an N-dimensional vector of input variables. The N-dimensional vector of variables can include at least the acquired temperature of said braking element. The N-dimensional calculation model can be an analytical or experimental characterization of the thermal behavior of the brake. The method can include estimating residual torque by comparing the accepted acquired temperature to the calculated reference temperature.
Depending on the embodiment, the N-dimensional vector of variables can include at a speed of the vehicle, at least an ambient temperature, at least a time delay between the instant of temperature acquisition and the last instant in which the brake was activated, or any combination
The braking element can include a braking disc or drum and said braking element can includes a wearable block of friction material and a back support plate for the friction material block. The temperature of the braking element can be acquired by at least one temperature sensor configured and positioned to detect the temperature of the back support plate.
The method can include using a temporal acquisition logic to acquire the temperature of the braking element based on a sampling frequency for at least one preset time interval. According to further embodiments, the method can include using a temporal acquisition logic to acquire the temperature of the braking element based on continuous sampling for at least one preset time interval starting from an acquisition instant determined by an event.
Depending on the embodiment, at least one variable chosen from vehicle speed, temperature of the braking element, temporal variation of the temperature of the braking element, or brake pedal status can used to determine whether said brake is activated at the instant of temperature value acquisition.
According to certain embodiments, the residual torque can be estimated with the N-dimensional calculation model and, in addition, with an acquired change in brake temperature over time. According to addition aspects, a device or system for estimating the residual braking torque of a vehicle can include a braked element that includes a braking disc or drum. The device can further
Include a braking element that includes a block of friction material and a back support plate for said friction material block. The device can further include at least one temperature sensor configured and positioned to detect the temperature of said back support plate. The device can further include an electronic control unit (e.g., a computing device comprising one or more computer hardware processors) connected to said temperature sensor, with said electronic control unit implementing an N-dimensional calculation model that represents an analytical or experimental characterization of the brake's thermal behavior. The electronic control unit (ECU) being programmed (e.g., with software or firmware stored in a memory of the electronic control unit) to acquire the temperature value of said back support plate from said temperature sensor. The ECU can be programmed to determine whether this brake is activated when the temperature value is acquired. The ECU can be programmed to accept the temperature value if said brake is not activated at said acquisition time. The ECU can be programmed, if the temperature value is accepted, to automatically calculate a temperature reference value by providing an N-dimensional vector of variables. The N-dimensional vector of variables can include at least the acquired temperature of said back support plate, as input to said N-dimensional calculation model. The ECU can be programmed to estimate residual torque by comparing the accepted acquired temperature to the calculated reference temperature.
The temperature sensor can be a contact temperature sensor integrated into said back support plate. In some embodiments, the temperature sensor can be a non-contact temperature sensor.
The temperature sensor can be configured and positioned to detect the surface or internal temperature of the support plate.
Various embodiments are represented in the drawings included in attachment hereto for illustrative purposes, and the scope of this illustration is not in any way to be interpreted as limiting.
Various characteristics of the different embodiments being disclosed may be combined to create additional embodiments, all of which are considered part of this illustration.
The following detailed description makes reference to the attached drawings, which form part of this description. In the drawings, similar reference numbers typically identify similar components, unless otherwise dictated by the context. The sequence and forms of execution described in the detailed description and drawings are not intended to be limiting. While in some drawings the components for only one corner of the vehicle are illustrated, the characteristics of which should be understood as being applicable to all corners. Other embodiments may be used, and other changes may be made without deviating from the spirit or scope of the subject-matter presented herein. The aspects of this illustration, as described generally herein and illustrated in the figures, may be arranged, replaced, combined, separated and designed in a wide variety of different configurations, all of which are explicitly contemplated and presented in this illustration.
According to certain embodiments, as schematically illustrated in
Temperature sensor 100 can comprise a contact temperature sensor integrated into back support plate 40, or a non-contact temperature sensor. Additionally, temperature sensor 100 may be configured and positioned to detect the surface temperature of back support plate 40 or the average temperature of back support plate 40. For example, temperature sensor 100 may be positioned on the back support plate 40 surface facing friction material block 20. Temperature sensor 100 may be positioned on back support plate 40 and positioned flush with the back support plate 40 surface facing friction material block 20. If the surface temperature of back support plate 40 is to be detected, however, then this surface may be a back support plate 40 surface facing towards or away from the block of friction material 20.
Temperature sensor 100 may comprise a separate component or may be silk-screened, and, e.g., printed directly onto the metal back support plate; different arrangements can be made by combining different types of sensors; multiple temperature sensors may be used for distributed temperature monitoring.
The braking element may comprise a brake pad that coordinates with a braking element represented by disc 10, as illustrated by way of example in
The device for estimating residual torque can include electronic control unit (ECU) 200, which is connected to temperature sensor 100.
The method for estimating the residual torque of a vehicle braking element according to this embodiment provides for temperature sensors 100 to acquire the temperature detected on back support plate 40, generate the temperature signals, and transmit the temperature signals to electronic control unit (ECU) 200.
The electronic control unit (ECU) 200 can also be connected to and receives input signals from a number of auxiliary sensors on board the vehicle. In the illustrated embodiment, the auxiliary sensors include one or more sensors chosen from vehicle speed sensor 50, ambient temperature sensor 51, and brake pedal activation sensor 52.
Vehicle speed detection and the recording of ambient temperature, the temperature for the corner of the vehicle where the braking device is operating, can refine the algorithm's performance and resolution.
In addition, other sensors may be incorporated into the brake pad and connected to electronic control unit (ECU) 200.
The sensors embedded in the brake pad may include one or more sensors chosen between shear strain sensor 53 and pressure force sensor 54.
According to the illustrated embodiment, the ECU 200 executes a calculation algorithm 300. For example, the calculation algorithm 300 can execute to cause the ECU 200 to perform operations to implement or oversee the data collection, control and output of electronic control unit (ECU) 200, e.g., in calculating or estimating residual torque. For example, the ECU 200 can comprise a computing system having one or more computer hardware processors (e.g., central processing units [CPUs]) and memory storing instructions (e.g., software or firmware) which, when executed by the ECU 200 implement the calculation algorithm 300.
According to certain embodiments, one or more of the signals for the variables detected by the auxiliary sensors are used to accept the temperature value acquired by temperature sensor 100 and are also configured, together with the acquired and accepted temperature value, into an N-dimensional array input to an N-dimensional model of the calculation algorithm 300.
The N-dimensional model can generate a reference temperature. The ECU 200 or other appropriate component can estimate residual torque by comparing the acquired and accepted temperature to the calculated reference temperature.
The N-dimensional calculation model can comprise an analytical or experimental characterization of the thermal behavior of the brake.
For example, the N-dimensional calculation model can be represented by the brake's thermal energy storage equation, where the thermal output energy, which equals the thermal energy lost by radiation, conduction, and convection, is equal to the incoming thermal energy generated by the friction of contact between the braking and braked elements of the brake.
The reference temperature, therefore, can be calculated by feeding the equation with the N-dimensional input array, which can also include a residual pressure or residual brake-through-torque value between the braking and braked elements, which can be assumed to have generated the reference temperature.
To estimate the residual torque with multiple identification levels, the calculation may be repeated with different residual pressure values or residual brake-through-torque values, which will correspond to different reference temperature values.
Through a calibration curve, for example, each Trd1, Trd2, Trd3, and Trdn is associated with a corresponding residual torque value rd1, rd2, rd3, and rdn.
The comparison between the acquired temperature T and the calculated reference temperature values Trd1, Trd2, Trd3, and Trdn can be used to estimate the residual torque value. For example, in the example shown in
According to certain embodiments, each corner of the vehicle may be equipped with one or two brake pads, with or without the sensors described above.
According to certain embodiments, the residual torque calculation may be estimated by a single electronic control unit (ECU) for supervision and control, or by individual electronic control units (ECU) dedicated to each corner of the vehicle.
According to certain embodiments, the residual torque calculation may be estimated in real time.
According to certain embodiments, the acquisition and control algorithms may be independent of vehicle type and/or braking pad and/or driving style, thanks to a self-assessment of the calibration of the signal threshold: therefore, according to certain embodiment, no tuning operations are necessary for the different applications.
Depending on the embodiment, the data capture may be based on two different strategies: a time-based strategy, or an event-based strategy.
According to certain embodiments, the residual torque estimate, e.g., the technique used to estimate the residual torque, is independent of the data acquisition strategy.
The acquisition can take place independently of brake pedal activation; activation of the pedal can be recorded.
Activating the brake pedal can trigger the acquisition of data within a subsequent time window, e.g., typically from 10 to 60 minutes, preferably 30 minutes.
The data capture within the time window can happen with preset and constant acquisition periods, e.g., typically from 20 to 60 seconds, preferably 30 seconds.
Any activation of the brake pedal within an already open time window can trigger a subsequent time window starting from the brake pedal activation event.
A first configuration of an embodiment of the residual torque estimation system and method according to certain embodiments is illustrated in
The system includes at least one temperature sensor 100, ambient temperature sensor 51, speed sensor 50, brake pedal activation sensor 52, and electronic control unit (ECU) 200, which can provide an estimate of residual torque 500 by processing the signals with algorithm 300. For example, the system of
The ambient temperature detection in the corner of the vehicle detected by ambient temperature sensor 51 can be used for seasonal calibration of the temperature detected by temperature sensor 100 of back support plate 40 of the brake pad. For example, ECU 200 can adjust or otherwise calibrate the temperature detected by the temperature sensor 100 using the ambient temperature detected by the ambient sensor 51 to calibrate for the ambient temperature.
According to the illustrated embodiment, an initial estimate of residual torque 500 is obtained through calculation section 310, which evaluates the first derivative of the detected temperature over time, and section 320, which processes it based on the braking status, thereby obtains substantially immediate or real-time information, especially for high levels of residual torque.
Calculation section 330 performs temperature selection under non-braking conditions based on the data received from temperature sensor 100, as corrected by ambient temperature sensor 51, from the data processed by calculation section 320, as shown above, from brake pedal activation sensor signal 52, and from the speed detected by vehicle speed sensor 50.
Calculation section 330 filters the temperature that is acquired and accepted in calculation section 340 by using low-pass filters to eliminate high-frequency peaks and components.
Calculation section 330 also generates a variable flag that enables reference temperature evaluation through calculation section 350, using N-dimensional model 351 powered by an N-dimensional vector of organized brake pad temperature data detected by sensor 100, ambient temperature detected by sensor 51, vehicle speed detected by sensor 50 and the time detected relative to the braking event detected by sensor 52.
N-dimensional model 351 may alternatively comprise an analytical model derived from an analytical description of the energy exchanged between the disc and the pad during braking, or an experimental model derived from a set of experimental data collected during a series of dynamic energy exchanges between disc and pad.
Calculation section 350 can calculate the reference temperature by feeding, for example, the equation representing the thermal equilibrium of the brake with the N-dimensional input array, which also includes a residual pressure or residual brake-through-torque value between the braking and braked elements, which are assumed to have generated the reference temperature.
Calculation section 360 receives and compares the selected temperature evaluation signals filtered by calculation section 340 and the reference temperature signal from calculation section 350 and produces and processes a signal for residual torque estimate 500.
This signal is then compared with the signal obtained from calculation section 320.
This second logical flow differs from the first, as described above and illustrated in
The architecture includes at least one temperature sensor 100, ambient temperature sensor 51, brake pedal activation sensor 52, and electronic control unit (ECU) 200, which provides an estimate of residual torque 500 by processing signals through algorithm 300.
The architecture of the second configuration differs from the first configuration shown in
The ambient temperature detection in the corner of the vehicle detected by ambient temperature sensor 51 can be used for seasonal calibration of the temperature detected by temperature sensor 100 of back support plate 40 of the brake pad. For example, ECU 200 can adjust or otherwise calibrate the temperature detected by the temperature sensor 100 using the ambient temperature detected by the ambient sensor 51 to calibrate for the ambient temperature.
According to the illustrated embodiment, an initial estimate of residual torque 500 is obtained through calculation section 310, which evaluates the first derivative of the detected temperature over time, and section 320, which processes it based on the braking status: this obtains immediate information, especially for high levels of residual torque.
Calculation section 330 performs temperature selection under non-braking conditions based on the data received from temperature sensor 100, as corrected by ambient temperature sensor 51, from the data processed by calculation section 320, as shown above, from brake pedal activation sensor signal 52.
Calculation section 330 filters the temperature that is acquired and accepted in calculation section 340 by using low-pass filters to eliminate high-frequency peaks and components.
Calculation section 330 also generates a variable flag that enables reference temperature evaluation through calculation section 350, using N-dimensional model 351 powered by an N-dimensional vector of organized brake pad temperature data detected by sensor 100, ambient temperature detected by sensor 51, and the time detected relative to the braking event detected by sensor 52.
Calculation section 360 receives and compares the selected temperature evaluation signals filtered by calculation section 340 and the reference temperature signal from calculation section 350 and produces and processes a signal for residual torque estimate 500.
This signal is then compared with the signal obtained from calculation section 320.
This second logical flow differs from the first, as described above and illustrated in
The third configuration differs from the first configuration shown in
The ambient temperature detection in the corner of the vehicle detected by ambient temperature sensor 51 can be used for seasonal calibration of the temperature detected by temperature sensor 100 of back support plate 40 of the brake pad. For example, ECU 200 can adjust or otherwise calibrate the temperature detected by the temperature sensor 100 using the ambient temperature detected by the ambient sensor 51 to calibrate for the ambient temperature.
According to the illustrated embodiment, an initial estimate of residual torque 500 is obtained through calculation section 310, which evaluates the first derivative of the detected temperature over time, and section 320, which processes it based on the braking status: this obtains immediate information, especially for high levels of residual torque.
One variant of the embodiment does not include calculation section 310.
Calculation section 330 performs temperature selection under non-braking conditions based on the data received from temperature sensor 100, as corrected by ambient temperature sensor 51, from the data processed by calculation section 320, as shown above, from the signal from vehicle speed sensor 50.
Calculation section 330 filters the temperature that is acquired and accepted in calculation section 340 by using low-pass filters to eliminate high-frequency peaks and components.
Calculation section 330 also generates a variable flag that enables reference temperature evaluation through calculation section 350, using N-dimensional model 351 powered by an N-dimensional vector of organized brake pad temperature data detected by sensor 100, ambient temperature detected by sensor 51, and vehicle speed detected by sensor 50.
Calculation section 360 receives and compares the selected temperature evaluation signals filtered by calculation section 340 and the reference temperature signal from calculation section 350 and produces and processes a signal for residual torque estimate 500.
This signal is then compared with the signal obtained from calculation section 320.
The architecture of the fourth configuration differs from the first configuration shown in
The ambient temperature detection in the corner of the vehicle detected by ambient temperature sensor 51 can be used for seasonal calibration of the temperature detected by temperature sensor 100 of back support plate 40 of the brake pad. For example, ECU 200 can adjust or otherwise calibrate the temperature detected by the temperature sensor 100 using the ambient temperature detected by the ambient sensor 51 to calibrate for the ambient temperature.
According to the illustrated embodiment, an initial estimate of residual torque 500 is obtained through calculation section 310, which evaluates the first derivative of the detected temperature over time, and section 320, which processes it based on the braking status: this obtains immediate information, especially for high levels of residual torque.
One variant of the embodiment does not include calculation section 310.
Calculation section 330 performs temperature selection under non-braking conditions based on the data received from temperature sensor 100, as corrected by ambient temperature sensor 51, from the data processed by calculation section 320, as shown above.
Calculation section 330 filters the temperature that is acquired and accepted in calculation section 340 by using low-pass filters to eliminate high-frequency peaks and components.
Calculation section 330 also generates a variable flag that enables reference temperature evaluation through calculation section 350, using N-dimensional model 351 powered by an N-dimensional vector of organized brake pad temperature data detected by sensor 100, and ambient temperature detected by sensor 51.
Calculation section 360 receives and compares the selected temperature evaluation signals filtered by calculation section 340 and the reference temperature signal from calculation section 350 and produces and processes a signal for residual torque estimate 500.
This signal is then compared with the signal obtained from calculation section 320.
Other changes and variations to the method and the device for estimating the residual torque of a vehicle brake element are possible.
The disclosed methods and systems for estimating the residual torque of a vehicle brake element can be subject to changes and variants while still falling within the scope of the inventions described herein, including equivalents.
For example, any type of appropriate materials and systems may be used.
Although certain devices, systems, and processes have been disclosed in the context of certain example embodiments, it will be understood by those skilled in the art that the scope of this disclosure extends beyond the specifically disclosed embodiments to other alternative embodiments and/or uses of the embodiments and certain modifications and equivalents thereof. Use with any structure is expressly within the scope of this present disclosure. Various features and aspects of the disclosed embodiments can be combined with or substituted for one another in order to form varying modes of the assembly. The scope of this disclosure should not be limited by the particular disclosed embodiments described herein.
Certain features that are described in this disclosure in the context of separate implementations can also be implemented in combination in a single implementation. Conversely, various features that are described in the context of a single implementation can also be implemented in multiple implementations separately or in any suitable subcombination. Moreover, although features may be described above as acting in certain combinations, one or more features from a claimed combination can, in some cases, be excised from the combination, and the combination may be claimed as any subcombination or variation of any subcombination.
Terms of orientation used herein, such as “top,” “bottom,” “proximal,” “distal,” “longitudinal,” “lateral,” and “end” are used in the context of the illustrated embodiment. However, the present disclosure should not be limited to the illustrated orientation. Indeed, other orientations are possible and are within the scope of this disclosure. Terms relating to circular shapes as used herein, such as diameter or radius, should be understood not to require perfect circular structures, but rather should be applied to any suitable structure with a cross-sectional region that can be measured from side-to-side. Terms relating to shapes generally, such as “circular” or “cylindrical” or “semi-circular” or “semi-cylindrical” or any related or similar terms, are not required to conform strictly to the mathematical definitions of circles or cylinders or other structures, but can encompass structures that are reasonably close approximations.
Conditional language, such as “can,” “could,” “might,” or “may,” unless specifically stated otherwise, or otherwise understood within the context as used, is generally intended to convey that certain embodiments include or do not include, certain features, elements, and/or steps. Thus, such conditional language is not generally intended to imply that features, elements, and/or steps are in any way required for one or more embodiments.
Conjunctive language, such as the phrase “at least one of X, Y, and Z,” unless specifically stated otherwise, is otherwise understood with the context as used in general to convey that an item, term, etc. may be either X, Y, or Z. Thus, such conjunctive language is not generally intended to imply that certain embodiments require the presence of at least one of X, at least one of Y, and at least one of Z.
The terms “approximately,” “about,” and “substantially” as used herein represent an amount close to the stated amount that still performs a desired function or achieves a desired result. For example, in some embodiments, as the context may dictate, the terms “approximately”, “about”, and “substantially” may refer to an amount that is within less than or equal to 10% of the stated amount. The term “generally” as used herein represents a value, amount, or characteristic that predominantly includes or tends toward a particular value, amount, or characteristic. As an example, in certain embodiments, as the context may dictate, the term “generally parallel” can refer to something that departs from exactly parallel by less than or equal to 20 degrees.
Some embodiments have been described in connection with the accompanying drawings. The figures are to scale, but such scale should not be limiting, since dimensions and proportions other than what are shown are contemplated and are within the scope of the disclosed present disclosure. Distances, angles, etc. are merely illustrative and do not necessarily bear an exact relationship to actual dimensions and layout of the devices illustrated. Components can be added, removed, and/or rearranged. Further, the disclosure herein of any particular feature, aspect, method, property, characteristic, quality, attribute, element, or the like in connection with various embodiments can be used in all other embodiments set forth herein. Additionally, it will be recognized that any methods described herein may be practiced using any device suitable for performing the recited steps.
Various illustrative embodiments of devices, systems, and methods have been disclosed. Although the devices, systems, and methods have been disclosed in the context of those embodiments, this disclosure extends beyond the specifically disclosed embodiments to other alternative embodiments and/or other uses of the embodiments, as well as to certain modifications and equivalents thereof. This disclosure expressly contemplates that various features and aspects of the disclosed embodiments can be combined with, or substituted for, one another. Accordingly, the scope of this disclosure should not be limited by the particular disclosed embodiments described above, but should be determined only by a fair reading of the claims that follow as well as their full scope of equivalents.
Number | Date | Country | Kind |
---|---|---|---|
102021000013529 | May 2021 | IT | national |
Number | Name | Date | Kind |
---|---|---|---|
2117027 | Langbein | May 1938 | A |
2289954 | Arndt | Jul 1942 | A |
3689880 | McKee et al. | Sep 1972 | A |
3724916 | Hirzel | Apr 1973 | A |
3902157 | Kita et al. | Aug 1975 | A |
4023864 | Lang et al. | May 1977 | A |
4117451 | Sato et al. | Sep 1978 | A |
4298857 | Robins et al. | Nov 1981 | A |
4456098 | Lindre | Jun 1984 | A |
4484280 | Brugger et al. | Nov 1984 | A |
4495434 | Diepers et al. | Jan 1985 | A |
4602702 | Ohta et al. | Jul 1986 | A |
4623044 | Ohta et al. | Nov 1986 | A |
4649370 | Thomason | Mar 1987 | A |
4782319 | Dell'Acqua et al. | Nov 1988 | A |
4854424 | Yamatoh et al. | Aug 1989 | A |
4869350 | Fargier et al. | Sep 1989 | A |
4901055 | Rosenberg et al. | Feb 1990 | A |
4928030 | Culp | May 1990 | A |
5090518 | Schenk et al. | Feb 1992 | A |
5099962 | Furusu et al. | Mar 1992 | A |
5115162 | Leonard et al. | May 1992 | A |
5133431 | Braun | Jul 1992 | A |
5176034 | Hazony et al. | Jan 1993 | A |
5235135 | Knecht et al. | Aug 1993 | A |
5302940 | Chen | Apr 1994 | A |
5325011 | Kahn | Jun 1994 | A |
5404067 | Stein | Apr 1995 | A |
5406682 | Zimnicki et al. | Apr 1995 | A |
5416415 | Dorri et al. | May 1995 | A |
5419415 | Lamb et al. | May 1995 | A |
5660215 | Nishikawa et al. | Aug 1997 | A |
5719577 | Pitot et al. | Feb 1998 | A |
5839545 | Preston et al. | Nov 1998 | A |
6064970 | McMillan et al. | May 2000 | A |
6122585 | Ono et al. | Sep 2000 | A |
6179091 | Takanashi | Jan 2001 | B1 |
6204786 | Bieth et al. | Mar 2001 | B1 |
6247560 | Bunker | Jun 2001 | B1 |
6310545 | Sapir | Oct 2001 | B1 |
6339956 | Huinink et al. | Jan 2002 | B1 |
6345225 | Bohm et al. | Feb 2002 | B1 |
6414818 | Tanimoto | Jul 2002 | B1 |
6477893 | Djordjevic | Nov 2002 | B1 |
6529803 | Meyers et al. | Mar 2003 | B2 |
6549126 | Hageman et al. | Apr 2003 | B2 |
6612736 | Lee et al. | Sep 2003 | B2 |
6668983 | Drennen et al. | Dec 2003 | B2 |
6681631 | Apel | Jan 2004 | B2 |
6813581 | Snyder | Nov 2004 | B1 |
6823242 | Ralph | Nov 2004 | B1 |
6934618 | Eckert et al. | Aug 2005 | B2 |
7124639 | Kurtz et al. | Oct 2006 | B1 |
7127948 | Tavares et al. | Oct 2006 | B2 |
7331427 | Mohr | Feb 2008 | B2 |
7451653 | Sippola | Nov 2008 | B1 |
7694555 | Howell et al. | Apr 2010 | B2 |
8026802 | Shimura | Sep 2011 | B2 |
8066339 | Crombez | Nov 2011 | B2 |
8151944 | Waltz | Apr 2012 | B2 |
8287055 | Lee | Oct 2012 | B2 |
8310356 | Evans et al. | Nov 2012 | B2 |
8437934 | Degenstein | May 2013 | B2 |
8573045 | Gotschlich | Nov 2013 | B2 |
8676721 | Piovesan et al. | Mar 2014 | B2 |
8717158 | Roach | May 2014 | B2 |
8729938 | Watanabe | May 2014 | B2 |
8789896 | Albright et al. | Jul 2014 | B2 |
8958966 | Nohira et al. | Feb 2015 | B2 |
9187099 | Powers et al. | Nov 2015 | B2 |
9269202 | Phelan et al. | Feb 2016 | B2 |
9286736 | Punjabi et al. | Mar 2016 | B2 |
9316278 | Moore et al. | Apr 2016 | B2 |
9353815 | Eden | May 2016 | B1 |
9415757 | Martinotto et al. | Aug 2016 | B2 |
9635467 | Miyoshi et al. | Apr 2017 | B2 |
9827961 | Spieker et al. | Nov 2017 | B2 |
9939035 | Donzelli et al. | Apr 2018 | B2 |
9964167 | Martinotto et al. | May 2018 | B2 |
9988024 | Schwartz et al. | Jun 2018 | B2 |
10052957 | Azzi | Aug 2018 | B2 |
10119586 | Merlo | Nov 2018 | B2 |
10138968 | Serra et al. | Nov 2018 | B2 |
10208822 | Donzelli et al. | Feb 2019 | B2 |
10224128 | Lee | Mar 2019 | B2 |
10227064 | Serra et al. | Mar 2019 | B2 |
10295006 | Serra et al. | May 2019 | B2 |
10408292 | Donzelli et al. | Sep 2019 | B2 |
10451130 | Solari et al. | Oct 2019 | B2 |
10495168 | Serra et al. | Dec 2019 | B2 |
10598239 | Martinotto et al. | Mar 2020 | B2 |
10677304 | Donzelli et al. | Jun 2020 | B2 |
10955017 | Serra et al. | Mar 2021 | B2 |
11047440 | Serra et al. | Jun 2021 | B2 |
20010042661 | Treyde | Nov 2001 | A1 |
20010049577 | Kesselgruber | Dec 2001 | A1 |
20020047496 | Wierach | Apr 2002 | A1 |
20020095253 | Losey et al. | Jul 2002 | A1 |
20020104717 | Borugian | Aug 2002 | A1 |
20030111305 | Drennen et al. | Jun 2003 | A1 |
20040015283 | Eckert et al. | Jan 2004 | A1 |
20040041464 | Eckert et al. | Mar 2004 | A1 |
20040187591 | Baumann et al. | Sep 2004 | A1 |
20040238299 | Ralea et al. | Dec 2004 | A1 |
20040242803 | Ohme et al. | Dec 2004 | A1 |
20050029056 | Baumgartner et al. | Feb 2005 | A1 |
20050103580 | Kramer | May 2005 | A1 |
20050236104 | Tanaka | Oct 2005 | A1 |
20050251306 | Gowan et al. | Nov 2005 | A1 |
20060016055 | Wilkie et al. | Jan 2006 | A1 |
20060076196 | Palladino | Apr 2006 | A1 |
20060254868 | Thiesing et al. | Nov 2006 | A1 |
20070024113 | Thrush | Feb 2007 | A1 |
20070228824 | Yasukawa et al. | Oct 2007 | A1 |
20070235268 | Caron | Oct 2007 | A1 |
20070284713 | Ninomiya et al. | Dec 2007 | A1 |
20080246335 | Spieker et al. | Oct 2008 | A1 |
20090033146 | Rieth et al. | Feb 2009 | A1 |
20090133971 | Baier-Welt | May 2009 | A1 |
20090157358 | Kim | Jun 2009 | A1 |
20090187324 | Lu et al. | Jul 2009 | A1 |
20090218179 | Yokoyama et al. | Sep 2009 | A1 |
20090223282 | Yamazaki | Sep 2009 | A1 |
20090289529 | Ito | Nov 2009 | A1 |
20090296945 | Attia | Dec 2009 | A1 |
20100032898 | Gearty | Feb 2010 | A1 |
20100186938 | Murata et al. | Jul 2010 | A1 |
20100210745 | McDaniel | Aug 2010 | A1 |
20100211249 | McClellan | Aug 2010 | A1 |
20100250081 | Kinser et al. | Sep 2010 | A1 |
20100318258 | Katayama et al. | Dec 2010 | A1 |
20110050406 | Hennig et al. | Mar 2011 | A1 |
20110125381 | Szell et al. | May 2011 | A1 |
20120055257 | Shaw-Klein | Mar 2012 | A1 |
20130013348 | Ling et al. | Jan 2013 | A1 |
20130018266 | Nishikubo | Jan 2013 | A1 |
20130048443 | Muramatsu et al. | Feb 2013 | A1 |
20130192933 | King et al. | Aug 2013 | A1 |
20140097951 | Grgic | Apr 2014 | A1 |
20140200784 | Nohira et al. | Jul 2014 | A1 |
20140257605 | Beck et al. | Sep 2014 | A1 |
20140311833 | Martinotto et al. | Oct 2014 | A1 |
20140337086 | Asenjo et al. | Nov 2014 | A1 |
20150112515 | Conway | Apr 2015 | A1 |
20160014526 | Miyoshi et al. | Jan 2016 | A1 |
20160084331 | Merlo et al. | Mar 2016 | A1 |
20160146279 | Philpott | May 2016 | A1 |
20160272176 | Furuyama | Sep 2016 | A1 |
20160341622 | Mensa | Nov 2016 | A1 |
20170052028 | Choudhury et al. | Feb 2017 | A1 |
20170082165 | Donzelli et al. | Mar 2017 | A1 |
20170082167 | Serra et al. | Mar 2017 | A1 |
20170267220 | Serra et al. | Sep 2017 | A1 |
20170331030 | Inoue et al. | Nov 2017 | A1 |
20180106319 | Solari et al. | Apr 2018 | A1 |
20180160248 | Murakami et al. | Jun 2018 | A1 |
20180244159 | Satterthwaite et al. | Aug 2018 | A1 |
20190003541 | Serra et al. | Jan 2019 | A1 |
20190005743 | Serra et al. | Jan 2019 | A1 |
20190078630 | Serra et al. | Mar 2019 | A1 |
20190241166 | Serra et al. | Aug 2019 | A1 |
20190249736 | Donzelli et al. | Aug 2019 | A1 |
20190351889 | Serra et al. | Nov 2019 | A1 |
20200088256 | Solari et al. | Mar 2020 | A1 |
20200124124 | Serra et al. | Apr 2020 | A1 |
20210071728 | Serra et al. | Mar 2021 | A1 |
20210148427 | Martinotto et al. | May 2021 | A1 |
20210348666 | Serra et al. | Nov 2021 | A1 |
20210388878 | Serra et al. | Dec 2021 | A1 |
20220176826 | Cho | Jun 2022 | A1 |
Number | Date | Country |
---|---|---|
1678893 | Oct 2005 | CN |
102317130 | Jan 2012 | CN |
102658812 | Sep 2012 | CN |
102785648 | Nov 2012 | CN |
104813060 | Feb 2018 | CN |
104821372 | Jun 2018 | CN |
10006012 | Sep 2000 | DE |
10230008 | Jan 2004 | DE |
10243127 | Mar 2004 | DE |
10259629 | Jul 2004 | DE |
102005052630 | Mar 2007 | DE |
102006018952 | Oct 2007 | DE |
102006053489 | May 2008 | DE |
102010010482 | Aug 2011 | DE |
102011006002 | Sep 2012 | DE |
10-2012-007118 | Oct 2013 | DE |
0189076 | Jul 1986 | EP |
0601681 | Jun 1995 | EP |
0744558 | Nov 1996 | EP |
0781936 | Jul 1997 | EP |
1431606 | Jun 2004 | EP |
1530037 | May 2005 | EP |
1531110 | May 2005 | EP |
1923592 | May 2008 | EP |
2647866 | Oct 2013 | EP |
2741063 | Jun 2014 | EP |
2778462 | Sep 2014 | EP |
2570691 | Oct 2014 | EP |
1173687 | Jan 2022 | EP |
2815040 | Apr 2002 | FR |
2309057 | Jul 1997 | GB |
2372825 | Sep 2002 | GB |
2478423 | Sep 2011 | GB |
S57-011143 | Jan 1982 | JP |
S58-206458 | Dec 1983 | JP |
S61275049 | Dec 1986 | JP |
04-054326 | Feb 1992 | JP |
H07-002107 | Jan 1995 | JP |
H09-002240 | Jan 1997 | JP |
H11-94707 | Apr 1999 | JP |
H11-125285 | May 1999 | JP |
2002-130348 | May 2002 | JP |
2002-538039 | Nov 2002 | JP |
2003-104139 | Apr 2003 | JP |
2003-205833 | Jul 2003 | JP |
2005-035344 | Feb 2005 | JP |
2006-193091 | Jul 2006 | JP |
2007-224988 | Sep 2007 | JP |
2011-116237 | Jun 2011 | JP |
2012-202983 | Oct 2012 | JP |
2016-516631 | Jun 2016 | JP |
2016-521336 | Jul 2016 | JP |
10-2002-0051429 | Jun 2002 | KR |
10-2007-0027041 | Mar 2007 | KR |
10-0791632 | Dec 2007 | KR |
2009-0057640 | Jun 2009 | KR |
10-2004-48957 | Jun 2010 | KR |
2011-0043849 | Apr 2011 | KR |
10-2013-0039804 | Apr 2013 | KR |
10-2015-0045047 | Apr 2015 | KR |
10-2016-0174510 | Dec 2016 | KR |
10-2015-0143696 | Dec 2019 | KR |
WO 199908018 | Feb 1999 | WO |
WO 2004027433 | Apr 2004 | WO |
WO 2014170726 | Oct 2014 | WO |
WO 2014170849 | Oct 2014 | WO |
WO 2015013217 | Jan 2015 | WO |
WO 2016038533 | Mar 2016 | WO |
WO 2016189150 | Dec 2016 | WO |
WO 2018019438 | Feb 2018 | WO |
WO 2019171289 | Sep 2019 | WO |
Entry |
---|
European Search Report; European Application No. EP 14158449; dated Aug. 6, 2014. |
International Search Report; International Application No. PCT/IB2013/060881; dated Jul. 3, 2014. |
International Search Report; International Application No. PCT/IB2014/060778; dated Aug. 6, 2014. |
International Search Report; International Application No. PCT/IB2015/056861; dated Jan. 18, 2016. |
International Search Report in PCT Application No. PCT/EP2016/071865 dated Dec. 13, 2016 in 3 pages. |
International Search Report and Written Opinion; International Application No. PCT/EP2017/059238; dated Aug. 10, 2017. |
Chinese Office Action in Chinese Application No. 201680054121.1 dated Mar. 26, 2019, in 9 pages. |
Chinese Office Action in Chinese Application No. 201680054121.1 dated Feb. 3, 2020, in 8 pages. |
Chinese Office Action in Chinese Application No. 201680054121.1 dated Nov. 4, 2020, in 8 pages. |
Chinese Office Action in Chinese Application No. 201680054121.1 dated Jan. 19, 2021, in 28 pages. |
Chinese Office Action in Chinese Application No. 201780011871.5, dated Jun. 17, 2020, in 15 pages. |
Chinese Search Report in Chinese Application No. 201780011871.5, dated Jun. 10, 2020, in 2 pages. |
Chinese Office Action in Chinese Application No. 201980033093.9, dated Sep. 28, 2021, in 14 pages. |
Chinese Office Action in Chinese Application No. 201980033093.9, dated Feb. 16, 2022, in 13 pages. |
European Office Action in European Application No. 16770243.0 dated Oct. 15, 2019, in 5 pages. |
European Office Action in European Application No. 16770243.0 dated Jan. 12, 2020, in 3 pages. |
European Office Action in European Application No. 16770243.0 dated Jun. 23, 2020, in 5 pages. |
Indian Office Action Indian Application No. 201837009364 dated Nov. 20, 2020, in 15 pages. |
Official European Communication in European Application No. 16770243.0 dated Oct. 19, 2020, in 11 pages. |
Written Opinion in PCT Application No. PCT/EP2016/071865 dated Dec. 13, 2020, in 6 pages. |
Written Opinion in Japanese Application No. 2018513655 dated Oct. 12, 2020, in 4 pages. |
Written Opinion in Japanese Application No. 2018-545192, dated Feb. 24, 2021, in 6 pages. |
Written Amendment in Japanese Application No. 2018513655 dated Oct. 12, 2020, in 5 pages. |
Office Action with English translation issued in Korean Application No. 10-2019-7004821, dated Feb. 10, 2021, in 18 pages. |
Second Office Action with English translation in Chinese Application No. 201780045954.6, in 14 pages. |
Search Report with English translation in Japanese Application No. JP 2019-503519, dated Dec. 10, 2020, in 22 pages. |
Office Action with English translation in Japanese Application No. 2019-503519, dated Dec. 23, 2020, in 20 pages. |
First Office Action with English translation in Chinese Application No. 201780045954.6, in 15 pages. |
Japanese Written Amendment in Japanese Application No. 2018545192, dated Feb. 24, 2021, in 8 pages. |
International Search Report and Written Opinion for Application No. PCT/EP2019/062680, dated Jun. 27, 2019, in 9 pages. |
Italian Search Report for Italian Application No. IT 201800005484, dated Feb. 19, 2019, in 7 pages. |
Italian Search Report and Written Opinion for Italian Patent Application No. IT UB20151059; dated May 28, 2015; 7 pages. |
Italian Search Report and Written Opinion for ITTO 20130307; dated Mar. 7, 2014; 7 pages. |
Italian Search Report Coversheet for Italian Patent Application No. 102015000018714/ITUB20151184; dated Jan. 26, 2016; 1 page. |
Italian Search Report Coversheet for Italian Patent Application No. 102015000018748/ITUB20151291; dated Feb. 3, 2016; 1 page. |
Italian Search Report Coversheet Italian Patent Application No. 102015000018701 ITUB20151029; dated Feb. 3, 2016; 1 page. |
Italian Search Report for Italian Patent Application No. 102015000018771 (UB20151059); dated Jan. 27, 2016; 1 page. |
Italian Search Report for Italian Patent Application No. IO 56568 It UB20151059; dated Jan. 20, 2016; 7 pages. |
Italian Search Report for Italian Patent Application No. IO 56584/ITUB20151184; dated Jan. 14, 2016; 7 pages. |
Italian Search Report for Italian Patent Application No. IO 56597/ITUB20151291; dated Jan. 25, 2016; 7 pages. |
Italian Search Report Italian Patent Application No. IO 56565/ITUB20151029; dated Jan. 22, 2016; 8 pages. |
Italian Search Report and Written Opinion for Italian Patent Application No. IT 201600077944 (IO 69013); dated May 26, 2017; 8 pages. |
Japanese Office Action in Japanese Application No. 2018513655 dated Jul. 14, 2020, in 16 pages. |
Japanese Office Action in Japanese Application No. 2018-545192, dated Jan. 5, 2021, in 17 pages. |
Japanese Search Report in Japanese Application No. 2018513655 (0022000625) dated May 25, 2020, in 12 pages. |
Von Wagner, et al., “Active Control of Brake Squeal Via ‘Smart Pads’”; Oct. 10, 2004. |
“The Next Generation of Hub Units”; SKF Group; 2012, www.vsm.skf.com; 32 pages. |
Solyom, Stefan, et al.; “Synthesis of a Model-Based Tire Slip Controller”; 2004; Vehicle System Dynamics, pp. 475-499; http://dx.doi.org/10.1080/004231105123313868. |
Gustafsson, Fredrik; “Slip-based Tire-Road Friction Estimation”; Automatica, 1997; vol. 33, No. 6; pp. 1087-1099. |
Pasillas-Lepine, William; “Hybrid Modeling and Limit Cycle Analysis for a Class of Five-Phase Anti-Lock Brake Algorithms”; Feb. 1, 2006; vol. 44, No. 2; pp. 173-188. |
Capra, D. et al.; An ABS Control Logic Based on Wheel Force Measurement. In: Vehicle System Dynamics; vol. 50, No. 12, pp. 1779-1796; http://porto.polito.it/2497487/. |
Ait-Hammouda, Islam; “Jumps and Synchronization in Anti-Lock Brake Algorithms”; Oct. 2008, Japan, 7 pages; https://hal.archives-ouvertes.fr/hal-00525788. |
Yi, Jingang; “Emergency Braking Control with an Observer-based Dynamic Tire/Rotation Friction Model and Wheel Angular Velocity Measurement”; Vehicle System Dynamics; 2003, vol. 39, No. 2; peg. 81-97. |
Ray, Laura; “Nonlinear Tire Force Estimation and Road Friction Identification: Simulation and Experiments”; Automatica, vol. 33, No. 10, pp. 1819-1833; 1997. |
Italian Search Report, IO 58761 (IT UB20153706), dated May 25, 2016, 8 pages. |
Italian Search Report, IO 58837 (IT UB20153709), dated May 31, 2016, 7 pages. |
International Search Report and Written Opinion; International Application No. PCT/EP2017/054455, filed on Feb. 27, 2017; dated May 3, 2017, 9 pages. |
Italian Search Report and Written Opinion for Application No. IT201900015839, dated Apr. 21, 2020, in 6 pages. |
Written Opinion of PCT Application No. PCT/EP2022/059702, in 5 pages. |
Number | Date | Country | |
---|---|---|---|
20220381631 A1 | Dec 2022 | US |