Your Selections

Nene, Devendra
Show Only

Collections

File Formats

Content Types

Dates

Sectors

Topics

Authors

Publishers

Affiliations

Events

   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Engine Fuel Economy Optimization for Different Hybrid Architectures Using 1-D Simulation Technique

Tafe Motors and Tractors Limited-Ajay Nain, Devendra Nene
  • Technical Paper
  • 2019-28-2496
Published 2019-11-21 by SAE International in United States
Hybridization of off road vehicles is in its early phase but it is likely to increase in coming years. In order to improve fuel economy and overall emission of the 3.3 litre tractor model, various kinds of engine hybridization is studied. This paper presents a methodology to predict vehicle fuel consumption and emission using 1-D software by coupling Ricardo Wave and Ricardo Ignite. Initially, An acceptable agreement within 5% deviation between simulation and experimental is established for engine steady state points, both for engine performance and NOx emission parameters. Engine fuel consumption and emission maps are predicted using Ricardo WAVE model. These maps are used as an input to IGNITE model for predicting cumulative fuel consumption. Same calibrated model is used further for studying idle start stop and fully hybrid P0 type hybrid architecture. The hybrid P0 type involves idle start stop, e-boost and regeneration. Model predicts overall significant reduction in cumulative fuel consumption and NOx, HC and CO emission.
This content contains downloadable datasets
Annotation ability available
   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Engine Valve Train Dynamic Analysis using 1-D Simulation Approach

Tafe Motors and Tractors Limited-Ajay Nain, Devendra Nene
  • Technical Paper
  • 2019-28-2422
Published 2019-11-21 by SAE International in United States
In order to reduce engine development timing and cost, a numerical calculation used to evaluate valve train systems. This paper discusses the work done on kinematic and dynamic analysis of Valve Train (VT) system of a diesel engine by using 1-D Ricardo Valdyn software. The goal is to meet optimum intake, exhaust valve timing requirement, maximize, valve open area and 30% over-speed requirement. Valve train model is prepared and inputs like mass and stiffness are estimated from 3-D model and finite element analysis, respectively. Simulation model is used for predicting valve bounce speed, valve displacement, cam-follower contact stress and strain in the rocker arm. Initially, Kinematic analysis is carried out to study the change in valve motion characteristics such as cam contour radius, tappet contact eccentricity etc. Further to this, dynamic analysis is carried out to assess forces and stresses on valve train components. Effect of cam tappet contact stresses, buckling load on push rod, spring surge, ratio of spring force to inertia force, valve seating velocity at increased speed condition etc. are discussed in…
Annotation ability available
   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Engine Exhaust Noise Optimization Using Sobol DoE Sequence and NSGA-II Algorithms

Tafe Motors and Tractors Limited-Ishwinder Pal Singh Sethi, Devendra Nene, Anand Shivajirao Patil
Published 2019-06-05 by SAE International in United States
Exhaust muffler is one of the most important component for overall vehicle noise signature. Optimized design of exhaust system plays a vital role in engine performance as well as auditory comfort. Exhaust orifice noise reduction is often contradicted by increased back pressure and packaging space. The process of arriving at exhaust design, which meets packaging space, back pressure and orifice noise requirements, is often manual and time consuming. Therefore, an automated numerical technique is needed for this multi-objective optimization.In current case study, a tractor exhaust system has been subjected to Design of Experiments (DoE) using Sobol sequencing algorithm and optimized using NSGA-II algorithm. Target design space of the exhaust muffler is identified and modeled considering available packaging constrain. Various exhaust design parameters like; length of internal pipes, location of baffles and perforation etc. are defined as input variables. Performance objective of back pressure and sound pressure level has also been defined in simulations workflow.Exhaust orifice noise has been reduced with significant reduction in overall simulations time. The optimal design is achieved satisfying all constrains leading…
This content contains downloadable datasets
Annotation ability available