Analytical Prediction of Ride in Car Cabin from Virtual Rough Road. Arvind K Jain, Amol Patil, Vaibhav Kaka, Indranil Bhattacharya

Transcription

1 Analytical Prediction of Ride in Car Cabin from Virtual Rough Road Arvind K Jain, Amol Patil, Vaibhav Kaka, Indranil Bhattacharya

2 Contents Organization Background Objective & Scope Model Building Load Case Ride Comfort Ride Results NVH Road Noise Benefits & Challenges Acknowledgements

3 Organization Background TATA Technologies Established in 1989 An integrated workforce of over 8500 professionals Achieved $424 Million in consolidated revenue by 2015 We are active in North America, Europe, and the Asia Pacific region, We provides services to automotive, aerospace & Heavy Machinery OEMs in: Vehicle Programs & Development Engineering & Design Manufacturing Automation and Control Solutions Customer Relationship Management Product Lifecycle Management (PLM) & Solution Integration Product Development IT Enterprise IT & Enterprise Resource Planning

4 Organization Background

5 Objective and Scope Objective: To show the process of Analytical Prediction of Ride and NVH Scope performance in a Car Cabin through driving the vehicle on Virtual Rough Road using Hyperworks Motionview and Motionsolve Full vehicle model developed with following subsystems Front MacPherson suspension Rear twist beam suspension Linear Powertrain MF Tire Open CRG road profile Computation of Ride Index as per ISO 2631 Cabin NVH

6 Model Building - Front Suspension Front McPherson Suspension LCA & other bushings were modelled as nonlinear Non-linear damper characteristics were used to model damper Spring was modelled as linear LCA, knuckle and sub-frame were modelled as flex bodies Steering - Rack and pinion Constant gear ratio was modelled as coupler Rack housing was mounted to Subframe using bushes Important KnC parameters Ride, roll and compliance tests were carried out to study important suspension parameters.

7 Model Building Rear Suspension Rear Suspension - Twist beam suspension Twist beam was mounted to body using non-linear bushes Linear spring was considered for this analysis Damper was modelled as non-linear Damper top and bottom mounts were modelled as non-linear bushes Important KnC parameters Ride, roll and compliance tests were carried out to study important suspension.

8 Load Case Ride Comfort Ride Simulation Constant speed - 30 kmph Gear Position constant Brake input zero Open CRG rough road scanned profile Outputs accelerations Wheel center Driver, co-driver, rear left passenger Outputs forces Wheel center

9 Ride Results Accelerations

10 Ride Results Cntd FFTs ~2Hz ~2Hz FFTs are plotted to understand frequency distribution of acceleration signals. Front and rear natural frequencies found to be close to 2Hz.

11 Ride Results Cntd Transmissibility System transmissibility is plotted Driver and rear passenger. Input Knuckle Acceleration Output Driver Acceleration Front and rear natural frequencies are found to be close to 2Hz.

12 Ride Index (m/s^2) Copyright 2017 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved. Ride Results Cntd Ride Index Signals Required: Seat X,Y,Z Procedure: Acceleration Signals (X,Y,Z) ISO 2631 Frequency Weighing RMS of ISO weighted signals are calculated Ride Index is calculated using below formula Ride Index 0.55 Ride Index = (w x x iso ) 2 + (w y y iso ) 2 + (w z z iso ) Co-Driver Driver Rear Ride Index

13 NVH Road Noise Approach Pre-processing & post processing is done in Altair s Hyper Works Mode and Noise calculation is done using Nastran / OPTISTRUCT Tyre and suspensions modes are calculated by constraining at tyre contact patch Road excitation are applied at tyre / wheel centre Noise prediction is done at DoE (Driver outer Ear) location and diagonally opposite rear PoE (Passenger outer Ear) location Noise peak investigation is done to identify the excitation source location Time Vs. Force Frequency Vs. Force

14 SPL (db/n) Copyright 2017 Altair Engineering, Inc. Proprietary and Confidential. All rights reserved. NVH Road Noise Key Achievement Performed modal and response analysis Performed noise transfer path analysis to identify peak dominating excitation source location DoE Driver Outer Ear Location PoE Rear Passenger Outer Ear Location Road Noise Road Excitation at All Wheel

15 Conclusion Attempted modelling of full vehicle with flexbodies in MotionView Ride analysis carried out using open road CRG FFT, FRF plotted to visualize frequency spectrum of signals in Hypergraph Front and rear Natural frequency were found close to 2 Hz Ride Index for rear seat is found to be maximum in this analysis

16 Benefits & Challenges Benefits to Organization Ride load-cases are developed in MotionView Process to analyze results is automated Hypergraph report template files are created to define report format 0.5 hour/iteration of user time is saved This process can further be used to carry out ride analysis using 3-D scanned road profiles Challenges Road profile RM marker tuned to converge the solution Flex-bodies -.h3d files created to bring more accuracy Frequency spectrum Hypergraph inbuilt FFT and FRF functions used Ride Index Process flow created in n-code to use ISO 2631 filters

17 Acknowledgements Tata Technologies Work Opportunity Suspension Designers Guidance Altair Technical Support For organizing the event Providing opportunity to showcase the work