Virtual Prototype Simulation and Reliability Analysis for Drive System of Armored Chassis

LIU Jin-hua(刘金华), ZHANG Yan(张 彦), CAO Li-jun(曹立军), SHAO Xin-jie(邵新杰), ZHOU Jing-tao(周景涛)

1 Department of Vehicle and Electrical Engineering, Mechanical Engineering College, Shijiazhuang 050003, China2 Department of Information Engineering, Shijiazhuang Vocational Technology Institute, Shijiazhuang 050081, China

Virtual Prototype Simulation and Reliability Analysis for Drive System of Armored Chassis

LIU Jin-hua(刘金华)1*, ZHANG Yan(张 彦)2, CAO Li-jun(曹立军)1, SHAO Xin-jie(邵新杰)1, ZHOU Jing-tao(周景涛)1

1DepartmentofVehicleandElectricalEngineering,MechanicalEngineeringCollege,Shijiazhuang050003,China2DepartmentofInformationEngineering,ShijiazhuangVocationalTechnologyInstitute,Shijiazhuang050081,China

Drive system is the key device of armored chassis. Its working state and reliability influence the maneuver performance of armored chassis directly. In order to simulate the failure process and evaluate the service reliability of drive system in training or battle missions, a new kind of dynamic simulation model and driving simulation platform of the complete drive system were established based on virtual prototype and finite element technology in this paper. Using the platform, the kinematics and dynamic characteristics of drive system were studied and analyzed in detail, the dynamic load spectrum of key components was obtained, the service life was predicted, and the service reliability evaluation results were provided. A simulation example of transmission gear was shown to illustrate the simulation and evaluation process. The result proves that the simulation method not only can be used to compute and evaluate the service reliability of complex mechanical mechanism, but also has high precision and reasonable computational cost. Therefore, simulation and reliability analysis based on virtual prototype of the armored chassis drive system will provide scientific reference for the formulation of armored chassis reasonable repair cycle.

virtualprototype;armoredchassis;drivesystem;reliability;loadspectrum

Introduction

Virtual prototyping technology is the integration of modern information technology, advanced simulation technology, and advanced manufacture technology. It is applied to the life cycle and the whole system integrated management of complex mechanical system. Testing and evaluation of product innovation design by using the virtual prototype instead of physical prototype can shorten the product development cycle, reduce the cost of product development, and improve product design quality[1-3]. Virtual prototype technology has been widely applied in developed countries, such as Germany, Japan, and USA.

With the development of vehicle technology, the system dynamics of the modern armored chassis design becomes more and more complicated, and the precision requirement of dynamics becomes more and more strict. Structuring a human-machine-environment system integration model, implementing the analysis and simulation of dynamic in combating situations shooting and running process, quantitatively revealing the inherent law of overall vehicle and components among system parameters, design parameters, the structure characteristics and the overall vehicle dynamic characteristic, have become the research important topic of armored vehicle system dynamics[4-7]. As an example, the dynamic properties simulation analysis of the armored chassis drive system based on virtual prototype technology is described, and the dynamic reliability of the drive system is studied and forecasted in this paper. This method can provide strongly technical guidelines for the equipment support and equipment design.

1 Building Virtual Prototype Model of Drive System

The armored chassis drive system is a complicated operating system integrating machine, electricity, and hydromantic, including the front transmission box, clutch, gearbox, transfer case, and many other institutions, so it is very difficult for dynamic simulation and analysis from the overall system. Based on function analysis, the transmission function of the drive system is decomposed and three reasonably simplified models are built including the front transmission box model, clutch model, and gearbox model. This method reduces the size of each model , reduces the overall system model errors, and improves the precision of drive system model through checking each subsystem model. According to the working principle of the system, reasonable constraints are applied in the MSC.ADAMS platform to ensure the consistent working process of virtual prototype and real drive system prototype.

1.1 The virtual prototype of drive system

For constructing the virtual prototype of drive system, firstly virtual prototype of the subsystems is established, secondly each subsystem is verified through dynamic simulation, at last the virtual prototype of overall drive system is built through integrated the subsystem virtual prototype. As an example, the process of building virtual prototype of gearbox is described. In the virtual dynamics model of 1 to 4 shifts are set up. In addition, based on the operating condition of gearbox, the constraint of gear pair and different fixed side constraints are applied. The gearbox dynamics model is shown in Fig.1.

Fig.1 The gearbox dynamics model

Given the gearbox simulation model on the platform of ADAMS self check is successful, it is necessary to verify the model kinematics. The model kinematics verification makes sure of the motion characteristics of uniform between the established simulation model and the actual prototype[8-10]. This is the five-gear position of the virtual prototype model, and the transmission ratio of virtual prototype and the designed transmission ratio of gearbox gears is shown in Table 1.

Table 1 The designed transmission ratio of gearbox gears and the transmission ratio of virtual prototype

ClimbinggearThe1stgearThe2ndgearThe3rdgearThe4thgearThedesignedtransmissionratio5.57142.60001.85711.32650.8442Thetransmissionratioofvirtualprototype5.56902.59671.85331.32380.8424Deviation/%0.0360.1190.2000.1660.296

From Table 1, the comparison between the transmission ratio of virtual prototype and the designed transmission ratio of gearbox gears validates that the error is very small. Therefore the virtual prototype of gearbox may be applied in the simulation of drive system.

1.2 Virtual prototype verification of drive system

Through the MSC.ADAMS platform the virtual prototype of each subsystem will be assembled. In the process of reorganization, virtual prototype of gearbox will be the basic model merged into the main model as it has relatively complicated structure and more important function. After adjusting, virtual prototype of the overall drive system will be verified. If the virtual prototype model verification is successful, the virtual prototype model will be established successfully.

As an example, virtual prototype of drive system on the 3rd gear is quantitatively verified. The initial velocity of the front transmission gear isV0=9 000 (°)/s. When loading cases for the active wheel, there are changes in the driving load and the driving wheel speed of engine change. According to the virtual prototype model, the dynamic simulation is done. Virtual prototype dynamics simulation is shown in Fig.2. Based on the dynamic simulation results and the initial conditions, the motion parameter of drive system is listed in Table 2.

(a) The load torque of driving wheel end

(b) The engine output torque of the 3rd gear

(c) The 3rd gear angular speed and angular acceleration comparison of front transmission gear

Table 2 Parameters comparison in different gear position of drive system

From the motion state comparison of the drive system shown in Fig.2 and Table 2, the virtual prototype of drive system may represent the real physical prototype for dynamic simulation and reliability analysis of the critical components.

2 Statistical Processing of Load Spectrum

Based onvirtual prototype, the load spectrum of key components can be obtained. Rain-flow counting method is adopted to finish the statistical processing of load spectrum. Take three-parameter weibull distribution verification for amplitude values of load spectrum, and take logarithmic distribution for equalizing values. Three-parameter weibull distribution belongs to skew distribution. Related coefficient optimization method is adopted to confirm three parameters of weibull distribution. Then, the weibull overbalance accumulative frequency function is

whereαis shape parameter,εis the position parameter,βis the scale parameter, andtis the simulation time.

Take statistical processing to the load spectra of different gears on different roads using three-parameter weibull method. The weibull distribution parameters of amplitude values are shown in Table 3. The corresponding distribution figure is shown in Figs. 3-4.

Table 3 The weibull distribution parameters of amplitude values and check values

PavementlevelGearpositionεαβγThe3rd-classpavementThe1stgear155.58981.3098258.9960-0.9863The2ndgear295.08071.6144385.7888-0.9915The3rdgear1.31821.7926608.8513-0.9968The4thgear39.03763.03711210.8750-0.9962The4th-classpavementThe1stgear142.02991.3751307.9542-0.9858The2ndgear252.85171.5870440.4393-0.9881The3rdgear31.92521.7247584.7281-0.9991The4thgear108.83712.41881228.6290-0.9938

Fig.3 Amplitude weibull distribution frequency of the 3rd-class pavement

Fig.4 Amplitude weibull distribution frequency of the 4th-class pavement

As for the key components under complex working conditions, the extremeness value of amplitude values should be the maximum value of extended amplitude values under complex working conditions.

The maximum values of amplitude values under different pavements and different gears are shown in Table 4.

Table 4 The maximum amplitude values under different pavements and different gears Unit:N·m

Pavementlevel The1stgearThe2ndgearThe3rdgearThe4thgearThe3rd-classpavement2078.32257.32635.82913.7The4th-classpavement2220.62556.82712.03747.1

The classes of amplitude values of load spectrum can be classified into eight levels. The amplitude value is

xaj=βj·xamax, j=1, 2, …, 8,

whereβjis the scale coefficient; the corresponding values are 1, 0.95, 0.85, 0.725, 0.575, 0.425, 0.275, and 0.125; andxajis the amplitude value level.

Take the fluctuation center as static component of load cycles, take the amplitude value as dynamic component, superpose the amplitude value on fluctuation center, and ignore the distribution of equalizing value.

The total equalizing value is also the fluctuation center,

whereMiis the equalizing value of different groups andviis the frequency number of group equalizing value.

Then, extend the load spectra of specified working conditions to the whole life cycle. Table 5 is the full-life load spectrum data of the 2nd gear on the 3rd-class pavement.

TorquegradeAmplituderatioTorqueamplitude/(N·m)AccumulatedcyclefrequencyLoadcyclefrequency11.0002257.31120.9502144.43.5242.52430.8501918.738.06134.53740.7251636.5565.96527.89950.5751297.99327.48761.4460.425959.349033681008.670.275620.7546733037699480.125282.161000000532670

3 Life Prediction and Reliability Evaluation

Based on the full-life load spectrum data of key components, finite element method can predict the service life and reliability according to the material’sS-Ncurve. Transmission gear is taken as the research object to illustrate the prediction and evaluation process. In MSC.Marc software, the finite element model of transmission gear is established and shown in Fig.5. It includes 14 597 nodes and 11 920 Hex8 solid units, where Hex8 denotes hexahedron in finite element analysis. The elastic modular ratio is 20 700 kg/mm2, Poisson ratio is 0.3, and mass density is 7.801E-6 kg/mm3.

Fig.5 Finite element model of transmission gear

Define the boundary conditions and load condition. Apply unit force on transmission gear. Set maximum iterative number to be 25 and tolerance value to be 0.1. Adopt modified Newton-Raphson method as the iterative method and employ relative displacement control. Dynamic response of transmission gear can be obtained. Then, the danger node distribution of transmission gear is shown in Fig.6. Corresponding simulation results show that the maximum contact stress is on the node of 2 889, and the value is 780.6 MPa; the maximum bending stress is on the node of 3 811, and the value is 152.4 MPa.

Fig.6 Danger node distribution of transmission gear

The material of transmission gear is 20Cr2Ni4A. ItsS-Ncurves are shown in Fig.7.

Fig.7 S-N curves of 20Cr2Ni4A

Modified linear accumulative damage rule is adopted to predict the fatigue life of transmission gear. The corresponding bending and contact fatigue lives of transmission gear under reliability level of 50% and 99% can be calculated in Table 6.

Table 6 Bending fatigue life of transmission gear (×104 km)

4 Conclusions

The virtual prototype technology may complete virtual experiment analysis at real condition by using“virtual prototype” instead of “real prototype”, and may set up equipment virtual prototype system of all state parameters in the virtual environment. On the basis of the integration of each subsystem, the motion simulation and reliability analysis of drive system are done. In the process of virtual prototype simulation, given the model is simplified and the system is subdivided, the time and difficulty of calculation and analysis of virtual prototype reduce, meanwhile the precision of simulation analysis remains unchanged approximately.

By simulating the life-cycle real working condition of armored chassis drive system in complex environment, the problems of performance assessment, residual life evaluation and prediction can be solved. Meanwhile the result of simulation and reliability analysis may provide scientific basis for setting technical rules and reasonable repair cycle of equipment support.

[1] Shabana A A. Flexible Multibody Dynamics: Review of Past and Recent Developments [J].MultibodySystemDynamics, 1997, 1(2): 189-222.

[2] Zhang X Z. Introduction to Multi-dimensional Virtual Proto-Type Technology of Mechanical Systems [J].Machinery&Electronics, 2006(12): 72-74. (in Chinese)

[3] Wang K, Yang X M. The Overview of Virtual Prototyping Technology [J].NewTechnology&NewProcess, 2008(3): 29-33. (in Chinese)

[4] Lai Y N, Zhang G Y, Chen Z G. Spacecraft Docking Rotating Simulator Based on Virtual Prototype [J].JournalofSystemSimulation, 2005, 17(3): 639-641. (in Chinese)

[5] Papadrakakis M, Lagaros N D. Reliability Based Structural Optimization Using Neural Networks and Monte Carlo Simulation [J].ComputerMethodsinAppliedMechanicsAndEngineering, 2002, 191(32): 3491-3507.

[6] MSC. Applying Mechanical System Simulation to Vehicle Design and Testing [R]. Mechanical Dynamics, Inc, 1999.

[7] Yin H B, Fang H C, Wei L S. Virtual Prototype Technology with Adams ATV [J].ModelandSimulationofaSelf-propelledGunChassis, 2004, 16(10): 2289-2293. (in Chinese)

[8] Wu D L, Ma J S, Li Y D,etal. Model and Simulation of a Self-propelled Gun Chassis [J].JournalofSystemSimulation, 2004, 16(11): 2552-2554, 2574. (in Chinese)

[9] Shang Q G, Wang H Y, Yang T,etal. Research on Simulation of Predicting Fatigue Life of Tracked Armored Vehicles Hull [J].ComputerSimulation, 2011, 28(6): 13-16. (in Chinese)

[10] Zhang S, Guo X, Gao W,etal. Geometry Traficability Modeling and Simulation of Wheeled Armored Vehicles [J].JournalofArmoredForceEngineeringInstitute, 2011, 25(5) : 75-78. (in Chinese)

TP391.9 Document code: A

1672-5220(2015)01-0166-05

Received date: 2014-08-08

*Correspondence should be addressed to LIU Jin-hua, E-mail: liuhequngao@sina.com