Method and system for testing combined hybrid dynamic system

Abstract

To provide a test system and test method for testing a combined hybrid dynamic system that performs simulated motion along a route, the test system and test method comprising a physical test device configured to test physical constituents.SOLUTION: A processor is configured such that at least one virtual model portion and physical constituents are a combined hybrid dynamic system. The processor is configured to control a test device so that the at least one virtual model portion and a constituent to be tested travel along a route. Provided is a method for generating initial input to start an iterative process in order to obtain input suitable for the at least one virtual portion.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] [Cross - Reference to Related Applications] This application claims the benefit of priority from U.S. Provisional Patent Application No. 63 / 598,943, filed on November 14, 2023, entitled "Methods and Systems for Testing Coupled Hybrid Dynamic Systems", the content of which is incorporated herein by reference in its entirety.

Background Art

[0002] The following discussion is provided only for general background information and is not intended to be used as an aid in determining the scope of the claimed subject matter.

[0003] The present invention is related to U.S. Patent No. 8,135,556 and U.S. Patent Application Publication No. 2013 / 030444, which are incorporated herein by reference in their entireties. Generally, the aforementioned applications provide facilities for controlling the simulation of coupled hybrid dynamic systems. This facility includes a physical test device, which is configured to drive the physical structural components of the system and generate a test device response as a result of applying a drive signal input to the test device. The processor is configured with a virtual model of the complementary system for the physical components (also referred to herein as the "virtual model"), i.e., the virtual model of the complementary system and the physical components constitute a complete hybrid dynamic system. The processor receives, as an input, a first portion of the test device response, and uses the first portion of the test device response received as an input and the virtual drive to generate a model response of the complementary system. The processor is further configured to compare a different second portion of the test device response with the corresponding response from the virtual model of the complementary system to form a difference, and this difference is used to form a system dynamic response model for generating a test device drive signal.

[0004] In one embodiment, the processor is further configured to generate a test drive signal, receive a test device response, generate a response from a virtual model of the complementary system, compare the test device response with the response from the virtual model of the complementary system, and generate a hybrid simulation process error. This error is then reduced in an iterative manner using the inverse function of the system dynamic response model until the difference between the response from the virtual model of the complementary system and the test device response falls below a specified threshold.

SUMMARY OF THE INVENTION

[0005] This summary and abstract in this specification are provided to introduce, in a simplified form, selected concepts that are further described below in the detailed description. This summary and abstract are not intended to identify key features or essential features of the claimed subject matter, nor are they intended to be used as an aid in determining the scope of the claimed subject matter. The claimed subject matter is not limited to implementations that solve any or all of the disadvantages described in the background art.

[0006] A test system is disclosed for testing a coupled hybrid dynamic system corresponding to a vehicle that simulates movement along a virtual path. The test system includes at least one actuator and a physical test device configured to use the at least one actuator to test physical structural components of the vehicle. A memory stores a virtual model portion of the coupled hybrid dynamic system. The virtual model portion and the physical structural components constitute the coupled hybrid dynamic system. Data corresponds to a plurality of attachment points that define connections in the coupled hybrid dynamic system. A processor is coupled to the memory and the physical test device and is configured to derive a drive that, when executed by the processor, operates at least one actuator of the physical test device. The derived drive corresponds to the virtual model portion and the physical structural components moving virtually together along the path. The virtual model portion receives a first input including modeled test data, a second input that is guidance control for maintaining the virtual model portion of the coupled hybrid dynamic system along the path, a third input that is a response from the physical test device having the physical structural components to be tested, and a fourth input that is driver guidance control for a second virtual model portion corresponding to a driver of the vehicle, wherein the processor is configured to calculate an initial prediction of the driver guidance control based on the speed of the first virtual model portion along the path.

[0007] In a second embodiment, the test system includes a physical test device including at least one actuator and configured to test a physical structural component of a vehicle using the at least one actuator. A memory stores a first virtual model portion of a coupled hybrid dynamic system and a second virtual model portion of the coupled hybrid dynamic system. The first virtual model portion, the second virtual model portion, and the physical structural component constitute a coupled hybrid dynamic system. The first virtual model portion includes a separated vehicle portion with constraints acting on the separated vehicle portion, and data corresponding to a plurality of attachment points defining connections in the coupled hybrid dynamic system. A processor is coupled to the memory and the physical test device and is configured to derive a drive that, when executed by the processor, operates at least one actuator of the physical test device. The derived drive corresponds to the first virtual model portion, the second virtual model portion, and the physical structural component virtually moving together along a path. The second virtual model portion receives a first input including modeled test data, a second input that is the motion of the first virtual model portion of the coupled hybrid dynamic system, a third input that is a response from the physical test device having the physical structural component being tested, and a fourth input that is a driver guidance control for the second virtual model portion corresponding to a driver of the vehicle, where the processor is configured to calculate an initial prediction of the driver guidance control based on the speed of the first virtual model portion along the path. The first virtual model portion receives a fifth input including guidance control from virtual guidance control and a sixth input that is a response from the physical structural component being tested, where the derived drive is obtained by repeatedly applying a test drive of the physical test device until the virtual guidance control for the first virtual model portion becomes at least very slightly reduced when an input to the first virtual model portion corresponding to the attachment point from the response of the physical test device to the derived drive properly positions the first virtual model portion to move along the path with the second virtual model portion.

[0008] In further embodiments of each of the above test systems, the processor is configured to iteratively correct the driver induced control. The processor may be configured to calculate an initial prediction of the driver induced control based on an array of X and Y points describing a path, calculate an initial prediction of the driver induced control based on a desired vehicle speed along the path, calculate an initial prediction of the driver induced control based on a total mass of the vehicle, and / or calculate an initial prediction of the driver induced control based on front axle cornering power and rear axle cornering power of the vehicle.

[0009] In one embodiment, the driver guided controls include steering wheel angle, total vehicle body XY velocity, and / or yaw rate of the first virtual model portion.

[0010] The processor receives vehicle position information including a plurality of X and Y points in a coordinate system describing a route, integrates the position information to calculate a distance traveled as a function of the position information, receives vehicle speed information including a vehicle speed as a function of time, calculates the distance traveled as a function of time, and interpolates using the distance traveled as a function of the position information and the distance traveled as a function of time to obtain X and Y positions along the route as a function of time, and calculates a speed V of the vehicle along the route. x and V y Calculate the vehicle's V along the route. x and V y From this, Zr=atan(V y / V x ) to find the yaw angle Z at the tangent to the path. r Calculate the yaw rate V that follows the tangent to the path. Zr Calculate the vehicle's V along the route. x and V y to total vehicle speed V Total to receive a total vehicle mass for the vehicle during the simulated motion, and / or to calculate an initial prediction of driver induced control including total vehicle XY velocity, yaw rate, and steering angle as a function of time.

[0011] In one advantageous embodiment, the virtual model portion includes a plurality of tires and wheel assemblies.

[0012] Another aspect is a computer-implemented method for generating simulated vehicle trajectory information for use in a test system having a physical device with a plurality of actuators to simulate the movement of a vehicle along a path. The method includes receiving vehicle position information including a plurality of X points and Y points in a coordinate system describing the path, integrating the position information by a processor to calculate a travel distance as a function of the position information, receiving vehicle speed information including the vehicle speed as a function of time and calculating a travel distance as a function of time, interpolating by the processor using the travel distance as a function of the position information and the travel distance as a function of time to obtain X and Y positions along the path as a function of time points, and calculating the vehicle speeds V x and V y along the path, calculating, by the processor, the yaw angle Z x and V y from the V r and V y along the path using Z x =atan(V r / V Zr ) for the tangent to the path, calculating the yaw rate V x along the tangent to the path, calculating, by the processor, the total vehicle speed V y from the V Total and V

Brief Description of the Drawings

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DETAILED DESCRIPTION OF THE INVENTION

[0021] In one embodiment shown in FIGS. 11 and 12 of U.S. Patent Application Publication No. 2013 / 0304441, which is shown herein as FIGS. 1 and 2 with different forms of schematic diagrams but with the same reference numerals, a random test device drive 78' is reproduced within a test device 72' on which a vehicle 80' is installed. The test device 72' applies a load and / or displacement to each spindle of the vehicle 80'. The random test device drive 78' may be a general drive such as a random amplitude, broadband frequency drive provided to a device controller 74', and the device controller 74' further controls the actuators of the test device 72'. A plurality of responses 82', for example, six degrees of freedom (6DOF), are obtained from suitable sensors for each spindle, and in this embodiment, they are applied to a virtual model 70' of a complementary system comprising virtual tires and wheel assemblies (disembodied tires and wheels, also referred to herein as "DWT") for each spindle. For example, without limitation, the plurality of responses 82' can include vertical force, longitudinal displacement, lateral displacement, camber angle, and steering angle at each spindle. Other responses 84' from the test device 72' are compared with responses 88' from the virtual model 70' of the complementary system. Also in this case, for example, without limitation, the responses 88' can include vertical displacement, longitudinal force, lateral force, camber moment, and steering moment. It should be noted that the force signals and displacement signals are merely illustrative since other response signals may be provided from the test device 72'.

[0022] The responses 82' from the test device 72' are supplied as inputs for forming a random drive 86' to the virtual model 70' of the tire and wheel assembly. The virtual vehicle model 70' excludes the vehicle 80' excluding the components to be tested, in this case, the wheels and tires. The virtual model 70' responds to the random drive input signal 86' with a random response signal 88'.

[0023] In the third step of the process, the random response 88’ of the virtual model 70’ of the tire and wheel is compared with the associated test rig random response 84’. A comparison 90’ is performed to form a random response difference 92’ (including forces, moments, and displacements in this specification). Due to the relationship between the random response difference 92’ and the random rig drive 78’, a system dynamic response model 76’ is established. The determination of the combined system dynamic response model 76’ can be done in an offline process so that high power and high speed computing capabilities are not required. The offline measurement of the system dynamic response model 76’ measures the sensitivity of the difference between the response 88’ of the virtual model 70’ of the tire and wheel and the rig response 84’ to the rig input when the vehicle 80’ is in the physical system. Further, since there is no need to collect data, in the virtual model or in the physical environment, any component can be tested without prior knowledge of how that component responds. The offline measurement of the system dynamic response model 76’ measures the sensitivity of the difference between the response 88’ of the virtual model of the complementary system and the rig response 84’ to the rig input when the component 80’ is in the physical system. When the relationship between the rig drive 78’ and the system response difference 92’ is modeled, an offline iterative process is performed as seen in Figure 2. This can be considered a test drive development step.

[0024] In the iterative process of Figure 2, which is an offline iteration, the virtual model 70’ of the DWT is used. The virtual DWT is driven on the virtual test road 79’ to generate a response 88’. In addition to the virtual test road input 79’ and / or the powertrain and steering 83’ (driver input), additional inputs to the virtual model 70 of the complementary system are shown as reference numeral 86’. The additional model input 86’ to the model 70’ is based on the input of the DWT induction 85’ together with the test rig response 82’ from the test rig 72’. The additional model input 86’ is applied simultaneously to the vehicle model 70 during the test. For the first iteration (N = 0), the input 86’ to the virtual model of the complementary system is typically zero.

[0025] The response 88' of the virtual model 70' is compared with the test apparatus response 84' from the test apparatus 72'. This test apparatus response 84' is the same force and / or displacement as the response 88', so the comparison is made by the comparator 90' to obtain the response difference indicated at 92'.

[0026] The response difference 92' is compared with the desired difference 104' by the comparator 106'. Typically, the desired difference 104' is set to zero for the iterative control process, but other desired differences may be employed.

[0027] The comparison between the response difference 92' and the desired difference 104' results in a simulation error 107', which is used by the inverse function (FRF - 1) 77' of the system dynamic response model 76' previously determined in the steps shown in FIG. 1. A drive correction 109' is added to the previous test apparatus drive signal 110' at 112' to generate the next test apparatus drive signal 78'.

[0028] The next test apparatus drive signal 78' is applied to the test apparatus 72' to measure the first response 82' and the second response 84'. The response 82' is applied to the DWT model 70' to generate the response 88' via the processor and the virtual DWT model 70', and the response 88' is compared with the test apparatus response 84' to generate another simulation error 107'. The process of applying the corrected drive 78' and generating the simulation error 107' is repeated iteratively until the resulting simulation error 107' is reduced to the desired tolerance value.

[0029] Following determination of the final test rig drive signal 78', the final test rig drive signal 78' is used in testing the test component 80'. The test rig drive signal 78' is an input to a test rig controller 74' that drives the device 72'. In addition to the response 82' as shown above, the DWT model 70' also receives, as inputs, digital road data 79', the powertrain and steering inputs to the DWT indicated by 83', and / or DWT guidance 85'. Thus, performance tests, durability tests, and other types of tests can be performed on the physical component 80', herein the vehicle, without the need for the physical tire and wheel to have been previously measured and tested or even to actually exist.

[0030] The above-described embodiment includes an actual vehicle body 80' connected to the test rig 72' via the actual suspension components (struts, springs, shock absorbers, spindles, etc.) of the vehicle 80', and the virtual model 70' was provided for non-realistic wheels and tires (DWT). In other words, in the embodiments of FIGS. 1 and 2, the system included an actual vehicle body 80' that could freely respond to the force inputs and / or displacement inputs provided by the device 72'. In contrast, FIG. 3 shows another embodiment of the invention comprising a system 200 having a plurality of virtual models 202 (each virtual DWT, collectively representing a total of four virtual DWTs herein), 204 operably connected together by the physical components of the test object.

[0031] The concepts described herein can be applied to other forms of hybrid systems, but aspects of the present invention are particularly useful in vehicle component testing, in a vehicle such as an automobile, by way of example only herein. In an illustrative embodiment, generally, system 200 generally includes a virtual DWT model 202, a virtual vehicle body model 204, and an apparatus 206, and the apparatus 206 has an actuator that applies a load and / or displacement to two actual physical suspension components (struts, springs, shock absorbers, spindles, etc.) indicated at 208. The apparatus 206 further includes a fixed reaction structure 210 on which the actual physical suspension components 208 are mounted. A load cell and / or displacement sensor operably connected to the actual physical suspension components 208 provides a response 212 that serves as an input to the virtual vehicle body model 204, while a response 214 (similar to the response 82' in FIGS. 1 and 2) is provided as an input (control mode) to the virtual DWT model 202. Typically, the response 212 includes the connection force on the virtual vehicle body model 204 in the vehicle body restraint, and the virtual vehicle body model 204 further provides a virtual vehicle body reference motion or displacement 216 that is likewise provided as an input to the virtual DWT model 202. Inputs from the digital road file 218 and / or DWT power train and steering inputs 272 (FIG. 4) are also provided as inputs (in some cases multiple) to the virtual DWT model 202. The digital road file 218 can include a path defined in one to three dimensions and can include one or more different types of roads (e.g., cobblestone, asphalt, etc.) with other optional features such as road depressions, curbs, etc., alone or in combination, without limitation. The spindle convergence mode error block 220 represents the components identified within the dashed region 220 in FIG. 2. The system dynamic response model can be obtained in a manner similar to that described above with respect to FIG. 1, and the final drive 224 for the controller 228 of the apparatus 206 is the inverse function of that system dynamic response model (FRF -1) is obtained iteratively in a manner similar to that of FIG. 2 using. However, importantly, the final device drive 224 must also be appropriate such that the virtual vehicle body of the vehicle, described later, properly tracks the non-realistic tires and wheel assemblies. In other words, the virtual vehicle body represented by the model 204 must appear to track with the other virtual elements (each virtual DWT represented collectively by the model 202) by appropriately responding to the response 212 obtained from the physical components of the test object, which is a virtual inertia element.

[0032] Referring also to FIG. 4, it should be noted that the virtual model of the vehicle body 204 is a model of the center of gravity (CG) of the vehicle body that responds to the virtual vehicle body induced drive indicated at 230 with up to six degrees of freedom (DOF) together with the coupling force 212. On the road defined by the digital road file 218 using the system 200, if desired, a virtual vehicle 240 (FIG. 5) including the virtual vehicle body model 204 and the DWT model 202 can be tested against the actual physical components 208, such as moving along the path 242 through the turning angle 244.

[0033] For example, without limitation, the vehicle body 204 represented by the CG 250 can be displaced in the selected degrees of freedom, for example, in the degrees of freedom of only the horizontal plane (including horizontal movement, i.e., the X and Y positions with respect to the coordinate system 254 and the yaw, i.e., rotational movement, about the Z axis of the coordinate system 254). In a further embodiment, it can include additional DOFs including all the remaining DOFs other than horizontal movement, particularly, heave (linear movement parallel to the Z axis), pitch (rotational movement about the Y axis), and roll (rotational movement about the X axis).

[0034] It should be noted that the vehicle body within system 200 is actually simulated as a segmented vehicle body with constraints (e.g., acting forces) applied to it. As shown in FIG. 4, these constraints include the coupling force 212 (the force applied at the defined suspension attachment points) and the virtual vehicle induced input (e.g., force) at a maximum of 6 DOF represented by 230. Using an iterative process, a final drive 224 is obtained that generates the coupling force 212 to properly position the virtual vehicle on the modeled DWT202 as the simulated vehicle moves along the path 242 defined by the road data 218. With respect to FIG. 4, this means that for the last iteration, the force applied by the virtual vehicle induced control 230 generates a force of zero (or preferably at least a very small force in all dimensions) on the virtual vehicle. This can only be achieved if the vehicle body can follow the induced control with zero or a very small applied force at the induction point (i.e., no external force or only a very small external force is required to maintain the virtual vehicle relative to the DWT) by the coupling force 212 (the force applied at the defined suspension attachment points) acting on the virtual vehicle 204 that supports the required vehicle body motion.

[0035] For horizontal vehicle guidance (X, Y), the desired path 242 is known as it defines the simulation event, and adjusting it is not a solution. Rather, the driver input 272 is iteratively adjusted to minimize the guidance force 230 for horizontal vehicle guidance. The driver input 272 includes, for example, one or both of the steering angle and the drive torque in response to a simulation along a straight path, or a path with curves or turns. Since steering affects both the Y force and the yaw force, the adjustment of yaw guidance is also part of the iterative horizontal adjustment.

[0036] It should be noted that the "multiple attachment points" can also be referred to as the "hybrid interface reference" position. They are points fixed to the vehicle body and represent the positions of virtual / physical connections in a static riding state (i.e., adding some offsets to the four wheel positions relative to the vehicle body). These are the main drivers of the global XY motion of the "DWT simulation" tire simulation block in FIGS. 2 to 4. In FIGS. 3 and 4, these virtual motion signals are explicitly indicated as the "VB reference motion". FIG. 2 shows a floating vehicle body, so it does not have a 6DOF virtual model of the vehicle body, but still needs to represent the global X, Y, and yaw motions. This is shown by block 85 "DWT induction (horizontal)" in FIG. 2. Since only the hybrid interface reference motion as a function of the vehicle body planar motion is required, the positions of these points are calculated analytically instead of performing a complete vehicle body model simulation.

[0037] The driver input 272 is obtained iteratively, but it is advantageous to start with an initial value that can reduce the number of required iterations, thereby reducing the number of times the system is driven, and thus, more importantly for the system, reducing the wear on the actual test object under test. Using the method 251 shown in FIGS. 6A and 6B, initial values for the driver input 272 (or 83' in the previous embodiment), such as the total vehicle body X-Y speed as a function of time, the yaw rate of the virtual vehicle body 204 (or the vehicle body 80' in the previous embodiment), and the steering angle, can be obtained for the induction of the virtual models of the virtual vehicle body 204 and the DWT model 202 (or the DWT model 70' in the previous embodiment).

[0038] Method 251 is implemented by a processor as described hereinafter, and in step 253, includes receiving vehicle position information including a plurality of X points and Y points in a suitable coordinate system that describes path 242. Path 242 can be generated in many different ways, such as from stored map data indicating roads and the like, or can be generated from scan data of a road, such as following a center line or other road markings. Path 242 can have any desired shape, such as having a defined start and end, or can be essentially continuous or infinite, such as an ellipse, a slalom, or an 8-course, for example, but still has start and end points that coincide with each other. Also, as shown in step 253, the position information is integrated and the travel distance along path 242, which is a function of the position information, is calculated.

[0039] In step 255, a desired vehicle speed profile for traveling along path 242 is provided. In particular, a desired vehicle speed as a function of time is received and used to define the travel distance along path 242 as a function of time.

[0040] In step 257, using the travel distance as a function of the position information and the travel distance as a function of time, one-dimensional interpolation is used to obtain the X position and Y position along the path as a function of the time point, and the vehicle speeds Vx and Vy along path 242 are calculated.

[0041] In step 259, from Vx and Vy of the vehicle along path 242, the yaw angle Zr at the tangent to path 242 is calculated using Zr = atan(Vy / Vx), and the yaw rate V Zr is calculated.

[0042] In step 261, the total vehicle speed V Total is calculated from Vx and Vy of the vehicle along path 242, and for example, V Total = sqrt(V X2 + V Y2 ) is obtained.

[0043] In step 263, stability derivatives for the vehicle are calculated. These are not "derivatives" in the sense of calculus, but rather lumped coefficients that represent the total lateral force (Y) or yaw moment (N) when multiplying and summing the body side slip angle (β), yaw rate (r), and steering angle (δ), respectively. The derivatives include the following. Yβ is the lateral force per unit of body side slip angle, Yr is the lateral force per unit of yaw rate, and Yδ is the lateral force per unit of steering angle. The same pattern holds for N (yaw moment). Yβ - Lateral force per unit of body side slip angle, Yr - Lateral force per unit of yaw rate, Yδ - Lateral force per unit of steering angle, Nβ - Yaw moment per unit of body (lateral) slip angle, Nr - Yaw moment per unit of yaw rate, Nδ - Yaw moment per unit of steering angle.

[0044] For example, this can include calculating the stability derivatives of the vehicle using the distance (a) from the center of gravity to the front axle center line, the distance (b) from the center of gravity to the rear axle center line, the front axle cornering power (CP_Frnt), and the rear axle cornering power (CP_Rr), as follows. Yβ = -(CP_Frnt + CP_Rr) Yr = -1. / V Total * (a * CP_Frnt - b * CP_Rr) Yδ = CP_Frnt Nβ = -a * CP_Frnt + b * CP_Rr Nr = 1. / V Total * (-(a 2 ) * CP_Frnt - (b 2 ) *CP_Rr) Nd = a * CP_Frnt

[0045] In step 265, the above-mentioned can be used in the equations of the linear two-wheel model of the vehicle together with the total vehicle mass (Body_M) to calculate the main wheel steering angle (SWA) and the vehicle body sideslip angle (Body_SSA). SWA = ((Nb * (Body_M * V Total -Yr) + Nr * Yb) / (Yd * Nb - Nd * Yb)) * Vzr_tan Body_SSA = (SWA * ((-Nd * (Body_M * VTotal - Yr) - Nr. * Yd) / (Nb * (Body_M. * V_total - Yr) - Nr * Yb)))

[0046] In step 267, then, the vehicle body sideslip angle and the steering angle are added to the tangent path trajectory, and for the derivation of the virtual model of the virtual vehicle 204 and the DWT model 202 (or the DWT model 70' in the previous embodiment), the total vehicle body X-Y speed as a function of time, the yaw rate of the virtual vehicle 204 (or the vehicle body 80' in the previous embodiment), and the steering angle, etc., initial values for the driver input 272 (or 83' in the previous embodiment) are obtained.

[0047] In contrast, the necessary derivations for heave, roll, and pitch (non-horizontal derivation) are not known, and therefore, the control objective is to repeatedly adjust the vehicle body derivation 230 to minimize the heave, roll, and pitch derivation forces in synchronization (corresponding and matching) with the suspension force 212 derived from the fixed vehicle body test system.

[0048] Figure 4 shows the iterative determination of the drive 224. The components of the spindle convergence mode error are also identified here at 220. The inverse function (FRF -1 ) 77’ is elucidated in a manner similar to that described above. Figure 4 also shows the use of the inverse model (FRF -1 ) 268 of the system dynamic response induction model. A method 300 for obtaining the inverse model (FRF -1 ) 268 of the system dynamic response induction model is shown in FIGS. 7A and 7B. Generally, the inverse model (FRF -1 ) 268 of the system dynamic response induction model is obtained from first elucidating the system dynamic response induction model (FRF). For calculating the required induction FRF model, random excitation in each induction control is provided to obtain the associated induction force error.

[0049] Referring to method 300, at step 302, a drive including random white noise excitation is (by way of example herein) created for six induction control inputs, namely, four virtual body induction control inputs (heave, roll, pitch, yaw), and two induction control inputs corresponding to the vehicle driver (driver profile) (e.g., steering angle and drive torque). It should be noted that for simpler motions of the body (e.g., linear motion), fewer than six induction controls may be acceptable.

[0050] At step 304, random heave, roll, pitch, and yaw induction control drive inputs are applied to the model of the virtual body 204 to obtain a reference motion of the virtual body.

[0051] At step 306, a random driver profile (steering angle and drive torque) and yaw are applied to each of the DWT virtual tire simulation models collectively represented at 202, and a “random” horizontal constraint force is obtained at each tire. It should be noted that the “random” steering input is applied only to the appropriately affected DWT, e.g., typically the first two virtual tires in a front-wheel-steering vehicle.

[0052] In step 308, a “random” excitation drive signal for the test device 206 is generated using the virtual tire forces elucidated in step 306 and the virtual vehicle reference motion elucidated in step 304. To do this, the inverse spindle convergence (FRF -1 ) 77’ obtained using the method described above is used to create the test device drive. It should be noted that the virtual vehicle reference motion in pitch, roll, heave measured for the vertical DWT spindle drive response needs to form the expected corresponding suspension relative vertical displacement that is applied to the fixed reaction suspension device in the apparatus along with the corresponding DWT virtual tire forces.

[0053] In step 310, the “random” drive is reproduced on the test device and a set of suspension reaction restraint forces 212 are recorded.

[0054] In step 312, this time, while applying the “random” suspension reaction force 212 to the virtual vehicle model 204 as well, the virtual vehicle model 204 is driven using the random heave, roll, pitch, and yaw drives from step 304 again.

[0055] In step 314, the resulting set of 6DOF vehicle induced forces 266 are recorded and used as output data for the calculation of the system dynamic response induction model (FRF) based on the random six induction control inputs, namely, four virtual vehicle induction control inputs (heave, roll, pitch, yaw), and two driver induction control inputs (steering angle and drive torque).

[0056] In step 316, the inverse model (FRF -1 ) 268 of the system dynamic response induction model is calculated from the system dynamic response induction model (FRF).

[0057] Assuming that there is a virtual vehicle induced force error 266 during the iterative process, the error 266 is the inverse function of the system dynamic response induction model (FRF -1) It is provided to 268. From the virtual vehicle body induction force error 266, the inverse function (FRF-1) 268 of the system dynamic response induction model provides an induction correction 270. The horizontal induction correction corresponds to the DWT wheel torque and steering correction (steering angle and / or steering torque) correction 271. These corrections are added to the DWT wheel torque and steering input 272 of the current iteration to generate values for a new iteration, and these new iteration values are later provided to the DWT virtual model 202 along with other inputs from the digital road file 218, the virtual vehicle body motion 216, and the actual motion of the spindle 214 respectively. Along with the reduction of the virtual induction force error 266 to zero (or a very small virtual induction force error), in this embodiment, according to the reduction of the spindle force error to zero (or a very small spindle force error) as measured by the comparison of the actual force and virtual force of the spindle indicated by arrows 260 and 262, when the desired horizontal path 242 of the vehicle body defined by the digital road data 218 and the virtual vehicle body induction 230 is provided, the final drive 224 can be obtained using the now-known essential DWT wheel torque and steering angle input 272. Then, this final drive 224 can be used to conduct tests.

[0058] At this point, a single virtual vehicle body is shown to respond to the test device (e.g., the coupling force 212) when driven, but it should be noted that this should not be considered limiting in that other coupling hybrid dynamic systems may have two or more virtual vehicle bodies, other virtual vehicle bodies, and / or other inputs from the system that respond to the responses obtained from the physical components. The generation of the final drive is performed in a similar manner, but the motion of each virtual vehicle body has the induction error and induction correction repeatedly used, with the corresponding inverse induction (FRF -1) is described in a similar manner as described above for each virtual vehicle body. For example, another virtual vehicle body may respond to the same and / or other physical components such as other physical components of the vehicle. By way of example only, in another embodiment, it may be necessary to also test the actual engine mounts together with the struts. In that embodiment, in addition to the vehicle body, another part of the vehicle (i.e., the engine) can be modeled. And / or in another embodiment, the system can have a model of the virtual body of the driver that interacts with the virtual vehicle body. And / or in yet another embodiment, the virtual vehicle body can receive other modeled inputs (similar to the modeled road 218), such as how the wind can apply different loads when the vehicle is subject to a crosswind.

[0059] FIG. 8 and the related discussion provide a brief, general description of a suitable computing environment in which the present invention can be implemented. Although not essential, the computer that implements the processing and storage of the models herein, together with the device controller, will be described, at least in part, in the overall context of computer-executable instructions, such as program modules, executed by computer 30. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The program modules will be described below using block diagrams and flowcharts. One skilled in the art can implement block diagrams and flowcharts for computer-executable instructions. Further, one skilled in the art will understand that the present invention can be practiced using other computer system configurations, including multiprocessor systems, network personal computers, minicomputers, mainframe computers, etc. The present invention can also be practiced in a distributed computing environment where tasks are performed by remote processing devices linked through a communications network. In a distributed computer environment, program modules can be located in both local and remote memory storage devices.

[0060] The computer 30 shown in FIG. 8 includes a conventional personal or desktop computer having a central processing unit (CPU) 32, a memory 34, and a system bus 36 that couples various system components including the memory 34 to the CPU 32. The system bus 36 can be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. The memory 34 includes read only memory (ROM) and random access memory (RAM). Basic input / output (BIOS) containing basic routines that help transfer information between elements within the computer 30 during startup and the like is stored in the ROM. Non-transitory computer-readable storage devices 38 such as hard disks, optical disk drives, ROM, RAM, flash memory cards, digital video disks, etc. are coupled to the system bus 36 and used for storage of programs and data. Generally, programs are loaded from at least one of the storage devices 38 into the memory 34, with or without accompanying data.

[0061] Input devices 40 such as a keyboard, a pointing device (mouse), etc. allow a user to provide commands to the computer 30. A monitor 42 or other type of output device is further connected via a suitable interface to the system bus 36 to provide feedback to the user. A desired response 22 can be provided as input to the computer 30 through a communication link such as a modem or through a removable medium of the storage device 38. Drive signals are provided to the test system based on program modules executed by the computer 30 and through a suitable interface 44 that couples the computer 30 to the test system apparatus. The interface 44 also receives responses.

[0062] The foregoing system and method are particularly advantageous in the testing of vehicle components, but this is merely one embodiment, and aspects of the present invention can be applied to other systems, such as, but not limited to, aircraft landing systems, train suspension systems, or other systems having a first modeled portion that receives an input (e.g., a force at a defined attachment point) from a physical component being tested, where the physical component being tested responds to a second modeled portion of the system, which further receives a first input that includes modeled test data, a second input that is a response (e.g., the motion of the first modeled portion), and a third input that is a control mode from the physical component being tested.

Claims

1. 1. A test system for testing an articulated hybrid dynamic system corresponding to a vehicle performing simulated motion along a virtual path, comprising: a physical testing device comprising at least one actuator and configured to test a physical structural component of the vehicle using the at least one actuator; A memory, a virtual model portion of the linked hybrid dynamic system, the virtual model portion and the physical structural components constituting the linked hybrid dynamic system; and data corresponding to a plurality of attachment points defining connections in the coupled hybrid dynamic system; A memory for storing a processor coupled to the memory and to the physical test device and configured, when executed by the processor, to derive drives for operating the at least one actuator of the physical test device, the derived drives corresponding to the virtual model portion and the physical structure component moving virtually together along the path, the virtual model portion being: A first input including modeled test data; a second input being a guidance control for keeping the virtual model portion of the coupled hybrid dynamic system along the path; a third input being a response from the physical testing device having the physical structural component under test; and a fourth input, driver guided controls for the second virtual model portion corresponding to a driver of the vehicle, the processor configured to calculate an initial prediction of the driver guided controls based on a speed of the first virtual model portion along the path; and Receive a processor; A test system comprising:

2. 2. The testing system of claim 1, wherein the processor is configured to iteratively correct the driver induced control, and / or the processor is configured to calculate the initial prediction of the driver induced control based on an array of X and Y points describing the path, and / or the processor is configured to calculate the initial prediction of the driver induced control based on a desired vehicle speed along the path, and / or the processor is configured to calculate the initial prediction of the driver induced control based on a total mass of the vehicle, and / or the processor is configured to calculate the initial prediction of the driver induced control based on front axle cornering power and rear axle cornering power of the vehicle.

3. 3. The test system of claim 1 or 2, wherein the driver induced control comprises a steering wheel angle, and / or the driver induced control comprises a total vehicle body XY velocity, and / or the driver induced control comprises a yaw rate of the first virtual model portion.

4. A test system according to any preceding claim, wherein the processor is configured to receive vehicle position information comprising a plurality of X and Y points in a coordinate system describing the path.

5. The test system of claim 4 , wherein the processor is configured to integrate the position information to calculate distance traveled as a function of the position information.

6. The processor, receiving vehicle speed information including vehicle speed as a function of time; and calculating distance traveled as a function of time; In one embodiment, distance traveled as a function of position information and distance traveled as a function of time are used to interpolate to obtain X and Y positions along the path as a function of time, and a velocity V of the vehicle along the path. ｘ and V ｙ Calculate In a further embodiment, the test system of any one of claims 1 to 5 is configured to calculate a yaw angle Zr at a tangent to the path from Vx and Vy of the vehicle along the path using Zr = atan (Vy / Vx) and to calculate a yaw rate VZr following the tangent to the path.

7. The processor, The total vehicle speed V from Vx and Vy of the vehicle along the route Ｔｏｔａｌ and / or receiving a total vehicle mass of the vehicle during simulated motion; and / or 7. The testing system of claim 6, configured to calculate the initial predictions of driver induced controls including total vehicle XY speed, yaw rate, and steering angle as a function of time.

8. The method of any one of claims 1 to 7, wherein the virtual model portion comprises a plurality of tire and wheel assemblies.

9. 1. A test system for testing an articulated hybrid dynamic system corresponding to a vehicle performing simulated motion along a virtual path, comprising: a physical testing device comprising at least one actuator and configured to test a physical structural component of the vehicle using the at least one actuator; A memory, a first virtual model portion of the coupled hybrid dynamic system; a second virtual model portion of the coupled hybrid dynamic system; Remember, the first virtual model portion, the second virtual model portion, and the physical structural component constitute the coupled hybrid dynamic system; the first virtual model portion includes an isolated vehicle portion with a constraint acting on the isolated vehicle portion; a memory further storing data corresponding to a plurality of attachment points defining connections in the coupled hybrid dynamic system; a processor coupled to the memory and to the physical test device and configured, when executed by the processor, to derive a drive for operating the at least one actuator of the physical test device; the derived drive corresponds to the first virtual model portion, the second virtual model portion and the physical structure component moving virtually together along the path; The second virtual model portion comprises: A first input including modeled test data; a second input being a motion of the first virtual model portion of the coupled hybrid dynamic system; and a third input being a response from the physical testing device having the physical structural component under test; and a fourth input, a driver guidance control for the second virtual model portion corresponding to a driver of the vehicle, the processor configured to calculate an initial prediction of the driver guidance control based on a speed of the first virtual model portion along the path; and Received The first virtual model portion comprises: a fifth input including a guidance control from a virtual guidance control; a sixth input, a response from the physical structural component under test, the derived drive being obtained by iteratively applying test drives of the physical testing apparatus until an input to the first virtual model portion corresponding to the attachment point from a response of the physical testing apparatus to the derived drive properly positions the first virtual model portion to move with the second virtual model portion along the path such that the virtual guidance control on the first virtual model portion is at least negligible; Receive a processor; A test system comprising:

10. The test system of claim 9 , wherein the processor is configured to iteratively correct the driver induced control.

11. 11. The testing system of claim 9 or 10, wherein the processor is configured to calculate the initial prediction of the driver guided control based on an array of X and Y points describing the path, and / or based on a desired vehicle speed along the path, and / or based on a total mass of the vehicle, and / or based on front and rear axle cornering powers of the vehicle.

12. A testing system according to any one of claims 9 to 11, wherein the driver guided control comprises steering wheel angle, and / or total vehicle XY velocity, and / or yaw rate of the first virtual model part.

13. The processor, receiving vehicle position information including a plurality of X and Y points in a coordinate system describing the route; In one embodiment, integrating the position information to calculate distance traveled as a function of position information; In a further embodiment, receiving vehicle speed information including vehicle speed as a function of time; and calculating a distance traveled as a function of time; In a further embodiment, distance traveled as a function of position information and distance traveled as a function of time are used to interpolate to obtain X and Y positions along the path as a function of time, and a velocity V of the vehicle along the path. ｘ and V ｙ Calculate The test system according to any one of claims 9 to 12, configured as follows.

14. 1. A computer-implemented method for generating simulated vehicle trajectory information for use in a test system having a physical device with a number of actuators to simulate vehicle motion along a path, comprising: receiving vehicle position information including a plurality of X and Y points in a coordinate system describing the route; integrating, with a processor, the position information to calculate distance traveled as a function of position information; receiving vehicle speed information including vehicle speed as a function of time and calculating a distance traveled as a function of time; The processor interpolates using the distance traveled as a function of position information and the distance traveled as a function of time to obtain X and Y positions along the path as a function of time, and a velocity V of the vehicle along the path. ｘ and V ｙ Calculating The processor determines the V of the vehicle along the route. ｘ and V ｙ From Z ｒ =a tan (V ｙ / V ｘ ) to determine the yaw angle Z ｒ and calculating the yaw rate V that follows the tangent to the path. Ｚｒ Calculating The processor determines the V of the vehicle along the route. ｘ and V ｙ from total vehicle speed V Ｔｏｔａｌ Calculating receiving a total vehicle mass of the vehicle in simulated motion; Calculating, by said processor, an initial estimate of total vehicle XY velocity, yaw rate, and steering angle as a function of time; A computer-implemented method comprising:

15. 15. The computer-implemented method of claim 14, further comprising iteratively correcting the total vehicle XY velocity, the yaw rate, and the steering angle as a function of time.

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