The present disclosure relates generally to electromechanical actuators, and more particularly to electric multi-speed hub drive wheels (eMDWs).
Various multi-speed hub drive wheels have been developed in the art. These include, for example, the multi-speed hub drive wheels described in U.S. 2014/0246893 (Tesar), U.S. 2015/0102655 (Tesar) and U.S. 2015/0292601 (Tesar).
In one aspect, a rotary actuator is provided which comprises (a) a prime mover including a rotor and a stator; (b) a front-end star compound gear equipped with a first pinion, a first plurality of star gears arrayed concentrically around said first pinion, a first clutch, a first clutch shift motor, an output shaft, and first, second and third gears, wherein said third gear is attached to said output shaft; (c) a back-end star compound gear; and (d) a wheel interface including a principal bearing and a brake disk; wherein said first pinion drives said first clutch; wherein said first clutch shift motor shifts said first clutch between a first position in which said first clutch engages said first gear, and a second position in which said first clutch engages said second gear; and wherein, when said first clutch engages said first gear, said first gear drives said first plurality of star gears.
It is a goal of the present disclosure to provide an in-wheel drive which maximizes operational choices for the best response to route duty cycles. Such duty cycles are often complex and may include stop-and-go traffic, hilly terrain, poor weather, concern for emissions, a need to maximize efficiency, or a need to minimize route times. All of these priorities may be embedded as real-time operator choices, parametrically defined by criteria measures, and archived to off-line use of predictive analytics to refine these choices, to further improve route planning, to predict timely repair and refreshment, or to recommend improvements to basic component software and hardware.
In many vehicular applications, providing four or more distinct speeds in the drive wheel may maximize the foregoing choices. For example, using four (or more) in-wheel drives on an urban bus, a school bus, or a fleet vehicle may enable a further expansion of these choices. Thus, to start from stop to climb a hill may require the low gear in all 4 wheels. To regenerate energy while going downhill may require all 4 wheels operating initially in high gear and sequentially shifting to low gear while minimizing the use of friction generating brakes. On level terrain, only two (and, in some cases only one) of the wheels may be used for propulsion. In sharp curves, torque levels may be managed to maximize torque in the outer front wheel and to minimize torque at the inner rear wheel. In poor weather conditions, some wheels may experience low traction coefficients (of friction), and hence, less torque may need to be applied to those wheels.
The range of the foregoing choices may be further expanded into a large listing of choices. For 4 speeds in 4 eMDWs, over 2000 distinct choices may be available to the driver. These choices go down dramatically (perhaps to about 250) when using only two eMDWs on the same vehicle.
The rotor is suspended by a disk on the left which drives the pinion shaft (3) of the front-end clutched star compound gear reducer. The pinion shaft (3) drives the dog leg clutch (4), which is shifted by motor (5) either to engage floating gear (6) or gear (10). If gear (6) is engaged, it drives star gears (8 and 9) on the same rigid shaft (7). Three or more star gears are concentrically arrayed around pinion (3) to produce no radial forces on the pinion (3). The shaft (7) of each star gear is supported by two bearings (at each end of the shaft in rigid stationary support disks). This array of star gears (9) drive gear (10) splined to the output shaft (11) for the front-end star compound. Alternatively, the clutch can now engage gear (10) directly to then drive shaft (11). Generally, it is expected that this shift ratio is 2-to-1.
Shaft (11) now drives the second dog leg clutch (12) driven by motor (13) (with a spline on the shaft) to engage either floating gear (14) or (15). Note that shaft (16) rigidly connects star gears (17) and (18). Engaging (14) drives star gear (17) which, then, drives star gear (19) on shaft (16) to drive the output internal gear (20) which is the output of the backend star compound. The reduction ratio may be 3-to-1. Engaging floating gear (15) drives the second star gear (18) with a reduction ratio (say) of 1.15. In this case, the shift ratio would be 2.61 for the backend star compound. Star gear (18) on shaft (16) now drives star gear (19), which drives the final output internal gear (20).
The output internal gear (20) is supported by principal bearing (21) to form the shortest force path to the actuator frame. The brake (22) and wheel rim (23) are rigidly attached to internal gear (20). All of these principal items are also shown in the 3-D layout of this 4-speed eMDW.
All of the 23 parts are listed in TABLE 1 except for the bearings that support all the gear shafts. The important principal bearing (20) is singled out in TABLE 1. There are a total of 23 principal parts in 4 basic modules:
All shafts are preferably supported by simple ball bearings that are lightly loaded. All gears may be helical to reduce noise. Both clutches may be driven by simple on/off motors with switching times of 10 m-sec. Note that the front-end star compound is small enough to fit inside the rotor of the prime mover. Its small scale means that it runs at high speed, low forces/torques and modest inertia content. The back-end star compound is roughly twice as large in scale as the front-end star compound. The back-end star compound runs at low speeds to store lower kinetic energy, but carries heavier torques and forces. Finally, the last plane of gears is unusually rugged to carry very heavy forces/torques. It is preferably able to resist all shocks, which validates the use of the large diameter grooved roller bearing.
The cross-section in
Preferably, all of the gears are equipped with standard helical gear teeth. The clutches are preferably on/off motor driven dog legs that can be switched in 5 to 10 m-sec. Preferably, all of the bearings are small diameter, lightly loaded ball bearings in fixed backbone structures; the exception is the principal bearing, which is preferably a grooved roller bearing. This bearing provides exceptional ruggedness between the suspension and the wheel.
Note that the disk brake is open (as usual) to the air for cooling. It is not expected that anything needs to be done to reconfigure the wheel. The 100 h.p. continuous power version disclosed herein is expected to weigh 200 lb., not counting the wheel and tire. This is an exceptionally light wheel drive, and would be useful for transit buses and fleet vehicles. Construction and farming machinery (such as, for example, loaders, scrapers, and farm row crop chemical sprayers) may also benefit from this layout. The eMDWs disclosed herein impart various benefits to the vehicles and systems which utilize them. These benefits include, but are not limited to, the benefits set forth in TABLE 2 below. Each of these benefits is discussed in greater detail below.
Economic Impact
U.S. land transport is currently a $1 trillion/year business, and includes cars, trucks, buses, trains and fleet vehicles. In all cases, a modern driveline technology would reduce life cycle cost and reduce fuel consumption. Further, emissions would be reduced, especially in inner cities.
Customer Choice
The computer/social media revolution has shown that customers want expanded choices at lower cost. For vehicles, this means standardization of highly-certified components that can be rapidly repaired or upgraded (plug-and-play) and mass produced in minimum sets to minimize cost while enhancing performance (see
Reduced Drive Line Complexity
Almost all vehicles use a singular internal combustion engine, a complex transmission (clutches and flywheel), a driveline of several universal joints in a central shaft, differential, split drives for front and rear axles, perpendicular wheel axles, and wheels with brakes. This complexity dominates vehicle architecture, represents major design constraints, ensures the existence of a few large manufacturers, and results in a continuously increasing life cycle cost with minimal choices (perhaps cosmetic) left to the customer (see
Rapid Vehicle Redesign
During the 1930's, many cars were designed with separate bodies and chassis. Today, the chassis dramatically constrains body design. For example, a modular chassis with eMDWs would permit free battery mass distribution, lower the mass center of gravity for more stability, remove the driveline hump, eliminate expensive transmissions and differentials, and permit low weight but stiff body structures. Doing so would permit rapid/revolutionary vehicle design to accelerate integration of emerging technologies, while also reducing cost by mass production in minimum sets.
Computer Reference Model
Early computers were massive centralized systems of high repetitive complexity where electronic switching tubes required constant surveillance to prevent failure. During the 1970's, the tech base was energized by computer chips and became easier to maintain (higher durability), but the systems remained centralized with poor customer accessibility and specialized maintenance. Essentially, current land transport systems are locked in this old paradigm. In the 1980's, however, DELL, Inc. combined with Microsoft and Intel to create open architecture personal computers, enabling component choices by the customer. This dramatically improved performance/cost ratios, created a competitive supply chain to accelerate technical integration, and provided mass production of highly-certified components in minimum sets. This now must be done for vehicles with a cost reduction of 2× and a fuel reduction of 2× for automobiles and similar goals for other land transport systems.
Traction Management
Vehicle control depends on managed friction forces at the tire/surface contact. Considering all potential forces (wheel spin, sideways sliding, bounce, etc.), and effects of road surface condition (ice, moisture, snow, temperature, tire wear, etc.), all tires should be represented by a finite number of embedded performance maps to calculate actual force levels based on real time (less than 1 m-sec.) sensor data generation. To obtain rapid response to this map-based command means that the prime mover must be rigidly connected to the wheel. By contrast, a cross-country truck with its heavy/deformable driveline has a decision latency of 1 sec., or 100 ft. at 70 mph. Getting this latency down to 10 m-sec. (i.e., 1 ft.) requires direct drive, as represented by the eMDW.
Performance Map Based eMDW Operation
All intelligent systems (tires, gear trains, controllers, power supplies, and the like) are highly non-linear. For example, each eMDW component will preferably have a non-planar map of its efficiency relative to wheel torque/speed parameters. Some prime mover maps have sweet spots of high efficiency of 90% for about 30% of the space, but drop down to 50% in 20-30% of the space. Hence, it is essential to combine these component maps into efficiency envelopes to always maximize efficiency. This may be done by choosing the most suitable gear ratio for the existing torque and speed, or choosing 3 wheels to drive, or 2 or even just 1. The one-wheel choice in slow traffic may reduce fuel consumption by 4× in this class of duty cycle. Similar envelopes for acceleration, hill climbing, downhill energy recovery, and the like now become possible because of the versatility of the eMDW-based vehicle disclosed herein.
eMDW Configurations
For automobiles, the range of choices typically goes from 16 to 40 h.p. in the 2-speed configuration to give the customer a very useful minimum set of power choices (16, 20, 24, 30, & 40) at very low cost (see
For trains, the same eMDW can drive an axle on each railroad car to move robotically in a switchyard. This requires little or no human support, and thus avoids the risk of injury normally associated with such maneuvers. Moreover, this approach may provide nearly perfect train makeups in precise timelines.
The adoption of the 4-speed eMDWs disclosed herein provides significant design flexibility in that it allows the number of in-wheel drives to be optimized for a given end use. Thus, for example, it enables the use of 2 eMDWs on fleet vehicles, 4 eMDWs on buses, 4 eMDWs on earth moving trucks, 2 eMDWs on the rear wheels of earth scrapers, 4 eMDWs on all wheels of material loaders, and 4 eMDWs on all wheels of farm row crop sprayers. It will thus be appreciated that eMDWs provide the basis for a revolution in land transport systems.
Reconfigurable Power Controller (RPC)
Given major choices for parameters such as speed, torque, gear ratios, acceleration and efficiency, the power controller may also embed similar choices (for example, efficiency, voltage, current and temperature management). This means that multiple subsystem components and circuits may need to be available in milliseconds to best match the demands on the eMDW. These controllers may be made up of high-end/low-cost components in sub modules that may be configured on demand. The combination of the RPC and the eMDW may be utilized to maximize choices at each wheel (perhaps 12 choices and 80 configurations). These choices not only help respond to performance commands, but also provide a means for configuring around faults so as to reduce single point failures.
Remaining Useful Life
More choices in a vehicle system implies more basic components that might degrade or fail as compared to the previous direct mechanical drivelines (sensors, controllers, prime movers, bearings, gearing, and the like). Given original performance maps for each component, updated maps resulting from use may be differenced to:
Most HEVs will generate power to go directly to the eMDWs or to battery packs for later use. The necessary I.C. engine (typically a light diesel) will be tuned to run at maximum efficiency and drive a 50 to 100 h.p. generator that may also be tuned for maximum efficiency. The combination means that if high peak acceleration is necessary, it may be achieved by the eMDWs that are preferably adapted to generate high peak power for at least short periods of time. All of these components (such as, for example, engine, battery, generator, controllers and eMDWs) preferably utilize standard interfaces to enable rapid quick-change out (plug-and-play) to minimize downtime and to maximize availability. This works to enable minimum sets of components to be mass produced in large quantities at increasingly lower costs and with increasing better performance (i.e., the mechanical equivalent of Moore's law for electronics, computers, and social media).
Eliminate Single Point Failures
The eMDW-based vehicle open architectures disclosed herein may tolerate numerous failures while maintaining a reasonable level of performance. Given 4 speeds and 5 choices, 4 power controller choices, and 4 voltage choices, each eMDW represents 80 choices. Given 4 wheels, this becomes 320 choices, all of which may be used to continue operation under somewhat reduced performance. This continued operation improves availability, reduces repair costs, and reduces the need for distributed large caches of spares for organizational vehicle fleets.
Maneuverability
One benefit of individual wheel control is dramatically improved maneuverability, especially in tight turns and poor weather. Classic concern for passive under/over steer may be eliminated in favor of real time (5 m-sec.) torque response at each wheel in the systems disclosed herein. For example, in a turn, the front outer wheel has more contact force, while the rear inner wheel has less contact force. Managing the torques on all four wheels depending, for example, on their real (measured) contact force, will always ensure proper commanded steering (unless sudden contact friction changes occur in bad weather). Fundamentally, this is called torque vectoring. The many choices in the eMDW may make this remarkably effective. Similarly, pitch control when accelerating or braking may rapidly account for contact force changes (front and rear tires). Finally, for off-road cases in rough terrain, it may become necessary to combine active suspensions with the active eMDWs. Because the low weight of eMDWs (from 40 to 70 lb.) for cars, this is typically not necessary in automotive applications.
Responsiveness
In heavy traffic, poor weather, rough terrain, or when acceleration is desired, it is preferred that the eMDW respond rapidly to command. This typically requires high prime mover peak torque and low rotational inertia in the eMDW gear reducer. Also, it is very desirable to shift eMDW reduction ratios smoothly and sequentially in the 5 to 10 millisecond regime to best distribute speed change torque crossovers (shocks). The eMDW is superior in this regard to the normal cumbersome mechanical driveline still used in most vehicles (which has a shift latency of 0.3 to 1 sec.).
Managed Duty Cycles
One significant benefit of eMDW-based vehicles is their potential to manage best performance to match a given route duty cycle (see
The above description of the present invention is illustrative, and is not intended to be limiting. It will thus be appreciated that various additions, substitutions and modifications may be made to the above described embodiments without departing from the scope of the present invention. Accordingly, the scope of the present invention should be construed in reference to the appended claims. It will also be appreciated that the various features set forth in the claims may be presented in various combinations and sub-combinations in future claims without departing from the scope of the invention. In particular, the present disclosure expressly contemplates any such combination or sub-combination that is not known to the prior art, as if such combinations or sub-combinations were expressly written out.
This application claims the benefit of priority of U.S. provisional application No. 62/354,417, filed Jun. 24, 2016, having the same inventor and the same title, and which is incorporated herein by reference in its entirety.
Number | Name | Date | Kind |
---|---|---|---|
276776 | Clemons | May 1883 | A |
341389 | Prescott | May 1886 | A |
386168 | Spencer et al. | Jul 1888 | A |
1601750 | Wildhaber | Oct 1926 | A |
2084844 | Harris | Jun 1937 | A |
2750850 | Wildhaber | Jun 1956 | A |
3310990 | Lettel | Mar 1967 | A |
3371552 | Soper | Mar 1968 | A |
3705522 | Ogawa | Dec 1972 | A |
3709055 | Grove | Jan 1973 | A |
3729276 | Boyadjieff et al. | Apr 1973 | A |
3907470 | Harle et al. | Sep 1975 | A |
4095150 | Senckel | Jun 1978 | A |
4270401 | Davidson | Jun 1981 | A |
4367424 | Presley | Jan 1983 | A |
4407170 | Fukui | Oct 1983 | A |
4505166 | Tesar | Mar 1985 | A |
4768400 | McKay | Sep 1988 | A |
4846018 | Matsumoto et al. | Jul 1989 | A |
4922781 | Peiji | May 1990 | A |
4988581 | Wycliffe | Jan 1991 | A |
5102377 | Spanski | Apr 1992 | A |
5116291 | Toyosumi et al. | May 1992 | A |
5293107 | Akeel | Mar 1994 | A |
5355743 | Tesar | Oct 1994 | A |
5692989 | Kamlukin | Dec 1997 | A |
5704864 | Yanagisawa | Jan 1998 | A |
6119542 | Arbrink | Sep 2000 | A |
6367571 | Schwarz | Apr 2002 | B1 |
6672966 | Muju et al. | Jan 2004 | B2 |
6791215 | Tesar | Sep 2004 | B2 |
6948402 | Amendolea | Sep 2005 | B1 |
6991580 | Elser et al. | Jan 2006 | B2 |
7081062 | Tesar | Jul 2006 | B2 |
7122926 | Tesar | Oct 2006 | B2 |
7201700 | Buxton | Apr 2007 | B2 |
7431676 | Tesar | Oct 2008 | B2 |
7534184 | Tsurumi | May 2009 | B2 |
7552664 | Bulatowicz | Jun 2009 | B2 |
7553249 | Nohara | Jun 2009 | B2 |
7604599 | Fujimoto et al. | Oct 2009 | B2 |
7641579 | Junkers | Jan 2010 | B2 |
7722494 | Tesar | May 2010 | B2 |
7766634 | Liavas et al. | Aug 2010 | B2 |
7811193 | Nakamura | Oct 2010 | B2 |
7935017 | Kurita et al. | May 2011 | B2 |
7942779 | Kobayashi | May 2011 | B2 |
7976420 | Nakamura | Jul 2011 | B2 |
8022564 | Nohara et al. | Sep 2011 | B2 |
8029400 | Nakamura | Oct 2011 | B2 |
8033942 | Tesar | Oct 2011 | B2 |
8047943 | Nakamura | Nov 2011 | B2 |
8117945 | Nakamura | Feb 2012 | B2 |
8133143 | Schoon | Mar 2012 | B2 |
8162789 | Takeuchi | Apr 2012 | B2 |
8235856 | Nakamura | Aug 2012 | B2 |
8308599 | Akami | Nov 2012 | B2 |
8323140 | Nakamura | Dec 2012 | B2 |
8353798 | Miyoshi et al. | Jan 2013 | B2 |
8382629 | Hirata | Feb 2013 | B2 |
8424625 | Ishii | Apr 2013 | B2 |
8435149 | Koyama et al. | May 2013 | B2 |
8523732 | Le Moal | Sep 2013 | B2 |
8545357 | Hibino | Oct 2013 | B2 |
9067582 | Smetana | Jun 2015 | B2 |
9365105 | Tesar | Jun 2016 | B2 |
9566857 | Pritchard | Feb 2017 | B1 |
9579974 | Bittlingmaier | Feb 2017 | B2 |
9657813 | Tesar | May 2017 | B2 |
9879760 | Teasr | Jan 2018 | B2 |
9915319 | Tesar | Mar 2018 | B2 |
20030027681 | Kakemo | Feb 2003 | A1 |
20040007923 | Tesar | Jan 2004 | A1 |
20040102274 | Tesar | May 2004 | A1 |
20040103742 | Tesar | Jun 2004 | A1 |
20050168084 | Tesar | Aug 2005 | A1 |
20050221945 | Plath | Oct 2005 | A1 |
20060264292 | Plath | Nov 2006 | A1 |
20070168081 | Shin et al. | Jul 2007 | A1 |
20070249457 | Tesar | Oct 2007 | A1 |
20080060473 | Li | Mar 2008 | A1 |
20080139357 | Fujimoto | Jun 2008 | A1 |
20080257088 | Tesar | Oct 2008 | A1 |
20080269922 | Tesar | Oct 2008 | A1 |
20080295623 | Kurita et al. | Dec 2008 | A1 |
20090075771 | Tesar | Mar 2009 | A1 |
20090118050 | Takeuchi | May 2009 | A1 |
20100113206 | Wang et al. | May 2010 | A1 |
20120088622 | Tesar | Apr 2012 | A1 |
20120204671 | Tesar | Aug 2012 | A1 |
20120215450 | Ashok et al. | Aug 2012 | A1 |
20130217530 | Tesar | Aug 2013 | A1 |
20140224064 | Tesar | Aug 2014 | A1 |
20140228162 | Tesar | Aug 2014 | A1 |
20140246893 | Tesar | Sep 2014 | A1 |
20150102655 | Tesar | Apr 2015 | A1 |
20150292601 | Tesar | Oct 2015 | A1 |
Number | Date | Country |
---|---|---|
0058025 | Aug 1982 | EP |
0527483 | Feb 1993 | EP |
2149724 | Feb 2010 | EP |
2169263 | Mar 2010 | EP |
008203 | Apr 1903 | GB |
224449 | Nov 1924 | GB |
419171 | Nov 1934 | GB |
426136 | Mar 1935 | GB |
450246 | Jul 1936 | GB |
676894 | Aug 1952 | GB |
759185 | Oct 1956 | GB |
775629 | May 1957 | GB |
856486 | Dec 1960 | GB |
926760 | May 1963 | GB |
1083689 | Sep 1967 | GB |
1104250 | Feb 1968 | GB |
1176936 | Jan 1970 | GB |
1179105 | Jan 1970 | GB |
1409651 | Oct 1975 | GB |
1453135 | Oct 1976 | GB |
1453135 | Oct 1976 | GB |
1494895 | Dec 1977 | GB |
2014260 | Aug 1979 | GB |
2377740 | Jan 2003 | GB |
2387882 | Oct 2003 | GB |
2489503 | Oct 2012 | GB |
9604493 | Feb 1996 | WO |
Entry |
---|
Ghionea, Adrian et al.; “Utilization of Some Computer Assisted Techniques in Generating and Study of the Hypocycloidal Flanks of the Spur Gear Teeth Stress”; 5th Intemational Meeting of the Carpathian Region Specialists In The Field of Gears; May 2004; 8 pages. |
Jones, Chris M. Sr.; “'Real-Time' Travel: A Strategy for Distributed Synchronized Actuator Control Using Open Standards”; Naval Engineers White Paper; 9 pages. |
Rabindran, Dinesh et al.; “A Differential-Based Dual Actuator for a Safe Robot Joint: Theory and Experiments”; Norld Automated Congress (WAC); Aug. 2014; 6 pages. |
Tesar, Delbert et al.; “Test-Bed to Measure the Performance Criteria of Actuators”; Robotics Research Group, University of Texas at Austin, 2002 Deliverable for Thread 3: High Performance Envelope Based on Intelligent; Dec. 1, 2001; 14 pages. |
Townsend, Dennis P.; “A Comparison of the Double-Circular-Arc-Gear Drives With Standard Involute Gear Drives”; Abstract; www.pumpjack.com/downloads; 8 pages. |
Litvin, Faydor L et al.; “Helical Gears With Circular Arc Teeth: Generation, Geometry, Precision and Adjustment to Errors, Computer Aided Simulation of Conditions of Meshing, and Bearing Contact”; NASA Contractor Report 4089; AVSCOM Technical Report 87-C-18; Oct. 1987; 95 pages. |
Krisfinamoorthy, Ganesh et al.; “Multi-Sensor Architecture for Intelligent Electromechanical Actuators”; 12th IFToMM World Congress, Besancon, France; Jun. 18-21, 2007; 6 pages. |
Lim, Gee Kwang et al.; “Modeling and Simulation of a Stewart Platform Type Parallel Structure Robot”; Final Report, Grant No. NAG 9-188; the University of Texas at Austin, Mechanical Engineering Department; Apr. 1989; 216 pages. |
Lee, Hoon et al.; “An Analytical Stiffness Analysis Between Actuator Structure and Principal Bearings Used for Robot Actuators”; Proceedings of ASME 2011 International Design Engineering Technical Conference and Computers and Information in Engineering Conference; IDEC/CIE 2011; Aug. 29-31, 2011; Washington, D.C.; 10 pages. |
Koran, Lucas et al.; “Duty Cycle Analysis to Drive Intelligent Actuator Development”; IEEE Systems Journal; May 2008; 14 pages. |
Ashok, Pradeepkumar et al.; “Guidelines for Managing Sensors in Cyber Physical Systems with Multiple Sensors”; Research Article; Hindawi Publishing Corporation, Journal of Sensors; vol. 2011, Article ID 321709; Nov. 22, 2011;16 pages. |
Hvass, Paul Brian et al.; “Condition Based Maintenance for Intelligent Electromechanical Actuators”; Research Paper; Jun. 2004; 262 pages. |
Kang, Seong-Flo et al.; “Indoor GPS Metrology System with 3D Probe for Precision Applications”; ASPE.pointinspace.com/publications/annual_2004 Papers; 2004; 4 pages. |
Knight, W.; “The Robots Running This Way”; MIT Technology Review; 2014; 8 pages. |
Ting, Yung et al.; “A Control Structure for Fault-Tolerant Operation of Robotic Manipulators”; Research Paper; University of Texas at Austin, Department of Mechanical Engineering; Apr. 1993; 10 pages. |
Number | Date | Country | |
---|---|---|---|
20170368931 A1 | Dec 2017 | US |
Number | Date | Country | |
---|---|---|---|
62354417 | Jun 2016 | US |