Predicting and Optimizing CNG Vehicle Performance on Chassis Dynamometer through 1D Simulation by using Vehicle Performance Algorithm 2015-26-0059
The paper deals with the simulation of a Light Commercial Vehicle (LCV) using vehicle performance algorithms. This method speeds up the product development process. Also by using these kind of methodology in vehicle simulation there is much noticeable reduction in cost of testing. The simulation model is used for parametric studies of the vehicle and also to attain objectives such as to optimize transmission ratio, full load acceleration, maximum tractive force, gradient performance, fuel consumption and the exhaust emission.
In this case study, simulation model of a CNG, LCV is used to analyze the performances similar to that done in a chassis dynamometer. The simulation leads to the prediction and evaluation of various parameters such as fuel consumption, exhaust emissions, full load acceleration, gradient performance & maximum tractive effort for Indian Driving Cycle. The methodology of optimization of transmission ratio includes the design and mathematical calculation of transmission ratios. The values of transmission ratios are obtained by theoretical mathematical calculations and the second category of ratios are based on the bench marked values from different products. Set of transmission ratios are given as input to the simulation in different cases and required results are achieved. These results are compared and the transmission ratio is optimized. The shift velocities at different gears and maximum vehicle speed are also evaluated using this methodology. NOx, HC, CO & CO2 emissions are evaluated and compared with tested results. The comparison should be with in within 5%. The methodology can be extended to study the influence of transmission ratio on specific fuel consumption and emissions.
Citation: R Kartha, R., Jamadar, M., Kavathekar, K., Rairikar, S. et al., "Predicting and Optimizing CNG Vehicle Performance on Chassis Dynamometer through 1D Simulation by using Vehicle Performance Algorithm," SAE Technical Paper 2015-26-0059, 2015, https://doi.org/10.4271/2015-26-0059. Download Citation
Rahul R Kartha, Mohammad Jamadar, Kishor Kumar Kavathekar, S D Rairikar, S. S Ramdasi, S.S Thipse, N. V Marathe
VIT University / A R A I Academy
Symposium on International Automotive Technology 2015