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A Machine Learning based Multi-objective Multidisciplinary Design Optimization (MMDO) for Lightweighting the Automotive Structures

Mahindra and Mahindra, Ltd.-Ranga Srinivas Gunti
  • Technical Paper
  • 2019-28-2424
To be published on 2019-11-21 by SAE International in United States
The present work involves Machine Learning (ML) based Multi-objective Multidisciplinary Design Optimization (MMDO) for lightweighting the automotive structures. The challenge in deployment of MMDO algorithms in solving real-world automotive structural design problems is the enormous time involved in solving full vehicle finite element models that involve large number of design variables and multiple performance constraints pertaining to vehicle dynamics, durability, crash and NVH domains. With the availability of powerful workstations and using the advanced Computer Aided Engineering (CAE) tools, it has become possible to generate huge sets of simulation data pertaining to multiple domains. In the present work, lightweigting of the vehicle structure is achieved, considered the vehicular hardpoint locations and the gages of the vehicle structures as the design variables and performance parameters pertaining to vehicle dynamics, structural durability, front-end intrusions during an IIHS offset impact test and the modal frequencies of few critical structural members as the constraint variables. Artificial Neural Networks (ANN) based algorithms were used for developing the predictive models of various performance parameters. The predictive models were then used to…
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Ride- Comfort Analysis for Commercial Truck using MATLAB Simulink.

ARAI Academy-Sarnab Debnath
Automotive Research Association of India-Mohammad Rafiq Agrewale
  • Technical Paper
  • 2019-28-2428
To be published on 2019-11-21 by SAE International in United States
Ride Comfort forms a core design aspect for suspension and is to be considered as primary requirement for vehicle performance in terms of drivability and uptime of passenger. Maintaining a balance between ride comfort and handling poses a major challenge to finalize the suspension specifications. The objective of this project it to perform ride- comfort analysis for a commercial truck using MATLAB Simulink. First, benchmarking was carried out on a 4x2 commercial truck and the physical parameters were obtained. Further, a mathematical model is developed using MATLAB Simulink R2015a and acceleration- time data is collected. An experimentation was carried out on the truck at speeds of 20 kmph, 30 kmph, 40 kmph and 50 kmph over a single hump to obtain actual acceleration time domain data. The model is then correlated with actual test over a single hump. This is followed by running the vehicle on Class A, B & C road profiles to account for random vibrations. Similarly, a simulation is done on MATLAB Simulink and a correlation is established between simulated and actual…
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Non-linear dynamic Modeling, Simulation and Control of Five-Phase 10/8 Switched Reluctance Motor for Electric Vehicle Application

College of Engineering Pune-Rahul Muley
Hella India Automotive Private Limited-Ravi Marravula
  • Technical Paper
  • 2019-28-2473
To be published on 2019-11-21 by SAE International in United States
The SRM is gaining much interest for EVs due to its rare-earth-free characteristic and excellent performance. SRM possess several advantages such as low cost, high efficiency, high power density, fault-tolerant and it can produce extended constant power region, and this makes SRM as viable alternative over conventional PM drives. Objective: The objective of this paper is to establish proof of theoretical concepts related to SRM. The key to achieve an effective SRM modeling is to use a methodology that allow the nonlinearity of its magnetic characteristics to be represented while maximizing the simulation speed. This paper represents how magnetization data obtained from FEA in the form of look up tables is most appropriate way to represent SRM model. In this paper, performance analysis of SRM is done with the help of Open loop and Closed loop MATLAB simulations. These dynamic simulations of SRM will assist in understanding behavior of SRM in various loading and speed conditions. Methodology: The machine geometry and design are first completed in ANSYS Maxwell 2-D software. Then Non-linear magnetization data is…
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Vision based solution for auto- maneuvering of vehicle for emerging market

General Motors Technical Center-Souvik Bose, Ashwani Kumar Singh, D V Ram Kumar Singampalli
General Motors Technical Center India-Chandraprakash lalwani
  • Technical Paper
  • 2019-28-2517
To be published on 2019-11-21 by SAE International in United States
Vision based solution for auto- maneuvering of vehicle for emerging market: Author/Co-Author: Singh Ashwani, SDV Ram Kumar, Bose Souvik, Lalwani Chandraprakash General Motors Technical Centre India Key words: Image Processing, Gap finding, virtual/Imaginary lines, Advance Driver Assist System (ADAS), Vehicle to vehicle(V2V)/Vehicle to Infrastructure(V2I/V2X) Research & Engineering Objective: For the various levels of autonomous, the current perception algorithms involve considerable number of sensor inputs like cameras, radars and Lidars and their fusion logics. The planning route for the vehicle navigation is done through map information which is highly volatile and keep changing many at times. Existing steering assist feature during a curve is available by combining additional driver monitoring camera & 360 degree camera. The complexity is very high in the implementation and computation of these algorithm. These solutions are not cost-effective for emerging markets. Non-availability of required infrastructure in developing countries is one of the additional constrain. Feature unavailability due to road infrastructure (ex: poor or no lane markings), bad weather will lead to higher customer dissatisfaction. The objective is to develop a logic/study…
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SELF EXPRESSIVE & SELF HEALING CLOSURES HARDWARES FOR AUTONOMOUS AND SHARED MOBILITY

General Motors Technical Center India-Vijayasarathy Subramanian, Biju Kumar, Masani Sivakrishna, Anandakumar Marappan
  • Technical Paper
  • 2019-28-2525
To be published on 2019-11-21 by SAE International in United States
Shared Mobility is changing the trends in Automotive Industry and its one of the Disruptions. The current vehicle customer usage and life of components are designed majorly for personal vehicle and with factors that comprehend usage of shared vehicles. The usage pattern for customer differ between personal vehicle, shared vehicle & Taxi. In the era of Autonomous and Shared mobility systems, the customer usage and expectation is high. The vehicle needs systems that will control customer interactions (Self-Expressive) & fix the issues on their own (Self-Healing). These two systems / methods will help in increasing customer satisfaction and life of the vehicle. We will be focusing on vehicle Closure hardware & mechanisms and look for opportunities to improve product life and customer experience in ride share and shared mobility vehicles by enabling integrated designs, which will Self-Express & Self-Heal. Vehicle closures having direct human interfaces with components like closures, handle & other hardware's will be tracked for their performance parameters and usage pattern. The performance parameters will be tracked for every customer and mapped to…
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Design and Development of Industrial Automotive Battery Management system

Dipali Dange, Radhika Ballal L
Assistant professor, COE, Pune-Meera Murali
  • Technical Paper
  • 2019-28-2498
To be published on 2019-11-21 by SAE International in United States
Battery operated vehicle need accurate management system because of its quick changes in State of charge (SOC) due to aggressive acceleration profiles and regenerative braking. Li-ion battery needs control over its operating area for its safe working. So, the main objective of the proposed system is to develop a BMS having algorithms to estimate accurate SOC, predict degradation parameters, balance individual cells, manage cell temperature, and provide safe area of operation defined by voltage and temperature. Proposed methodology uses Model-based Design approach wherein nonlinear behavior of battery is modeled as Equivalent Circuit Model to compute the SOC and degradation effect on battery to decide the end of life of battery, also performing inductive Active balancing on cells to equalize the charge. proposed algorithms communicate with the vehicle ECU through CAN to assist the driver for runtime estimation, time for battery swapping, Alerts. Li-ion cells undergo current tests like pulsed charge-discharge, and transient response is effectively captured with parameter estimation with various degraded cells. Estimated model used in system and build battery stack. Balancing algorithm designed…
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Model Based Design of Chassis-Frame with MATLAB

VE Commercial Vehicles Ltd.-Rishabh Singh parihar, Gaurav Sharma, Nitinkumar prabhakar patil, Yogendra Aniya
  • Technical Paper
  • 2019-28-2429
To be published on 2019-11-21 by SAE International in United States
In the current commercial vehicles market, ride-comfort and handling are crucial parameters for the customer and end user. There are various aspects which determine the vehicle behaviour. One of aspects is the structural rigidity of the vehicle, which has its own effect on vehicle dynamics. To meet the required stiffness of the main structural component of the vehicle i.e. chassis frame, FEA analysis has to be done in current methodology. The number of iterations have to be done to build an appropriate model with low weight, which can meet the design requirements. At first, conceptual design mock-up unit is to be developed then FEA (CAE) analysis to be done on it. If any design criteria are not met, then this cycle repeats again until it fulfils the required stiffness. Today, the direct stiffness procedure is the basic principle of almost every FEA software package. In this paper, computer code based on MATLAB software is provided and presented for the analysis of the chassis frame using the direct stiffness method. The code, models a structure of…
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Rapid Prototyping and Implementation of traction motor drive for E- Mobility

Altair Engineering India Pvt Ltd.-Srikanth R, Sreeram Mohan
  • Technical Paper
  • 2019-28-2472
To be published on 2019-11-21 by SAE International in United States
Objective / Question: Is it possible to extend the envelope of simulation driven design and its advantages to development of complex dynamic systems viz. traction motor drives? The objective that then follows is how to enable OEM/Tier-1s to reduce wastes in the process of traction motor controller design, development, optimization and implementation. Motor control design to validation process is time consuming and tricky! Additionally, the requirement of software knowledge to write code to implement drive engineer's control ideas. The challenges here are - to name a few - algorithm for real time, addressing memory constraints, debugging, comprehending mathematical overflows, portability & BOM cost. These introduces wastes in parameters like time, cost, performance, efficiency and reliability. Methodology: Developing a new traction motor controller for E Mobility takes 18 - 24 months typically. 2 distinct activities take place in a loop. One is the motor drive engineer who has good understanding of the motor, requirement demands on the motor & digital control of the motor and the second is the software engineer who has a good understanding…
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Feasibility of Multiple Piston Motion Control Approaches in a Free Piston Engine Generator

West Virginia University-Mehar Bade, Nigel Clark, Parviz Famouri, PriyaankaDevi Guggilapu
  • Technical Paper
  • 2019-01-2599
Published 2019-10-22 by SAE International in United States
The control and design optimization of a Free Piston Engine Generator (FPEG) has been found to be difficult as each independent variable changes the piston dynamics with respect to time. These dynamics, in turn, alter the generator and engine response to other governing variables. As a result, the FPEG system requires an energy balance control algorithm such that the cumulative energy delivered by the engine is equal to the cumulative energy taken by the generator for stable operation. The main objective of this control algorithm is to match the power generated by the engine to the power demanded by the generator. In a conventional crankshaft engine, this energy balance control is similar to the use of a governor and a flywheel to control the rotational speed. In general, if the generator consumes more energy in a cycle than the engine provides, the system moves towards a stall. If the generator consumes less energy, then the effective stroke, compression ratio and maximum translator velocity must rise steadily from cycle-to-cycle until the heat transfer losses stop the…
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Study of Advanced Control Based on the RBF Neural Network Theory in Diesel Engine Speed Control

China-Li-Ping Yang
Harbin Engineering University, China-Guo-Feng Zhao, Yun Long, En-Zhe Song, Xiu-Zhen Ma
  • Journal Article
  • 03-13-01-0005
Published 2019-10-14 by SAE International in United States
Based on radial basis function (RBF) neural network (NN) theory, RBF-Proportional Integral Derivative (PID) diesel engine speed control is proposed. The algorithm has strong self-learning ability and strong adaptive ability, and is able to optimize the control parameters of the speed loop controller in real time. A series of simulations are carried out with different initial weights. Simulation results reveal that initial weights have little effect on RBF-PID control performance. A STM32 MCU-based controller is developed according to the calculation requirement. Experiments are carried out on a D6114 diesel engine generator to verify the proposed speed control algorithm. The simulation results are in good agreement with the experimental results. The results show that the influence of initial weights on RBF-PID control algorithm is smaller than that on BP-PID control algorithm. When RBF-PID control algorithm is adopted, the steady speed fluctuation rate is 0.4%. When sudden load is carried out, the speed recovery time is 2.1 s and the instantaneous adjustment rate is 4.93%. When sudden unload simulation is carried out, the speed recovery time is…