Switching Response Optimization for Cylinder Deactivation with Type II Passenger Car Applications

Paper #:
  • 2014-01-1704

  • 2014-04-01
Radulescu, A., Krishnasamy, V., and Chandras, P., "Switching Response Optimization for Cylinder Deactivation with Type II Passenger Car Applications," SAE Technical Paper 2014-01-1704, 2014, https://doi.org/10.4271/2014-01-1704.
An advanced Variable Valve Actuation (VVA) system is optimized for response time in order to provide robust switching at high engine speeds. The VVA system considered is Cylinder Deactivation (CDA) for the purpose of improving fuel economy. Specifically, a Switching Roller Finger Follower (SRFF) on a Dual Overhead Camshaft (DOHC) engine is optimized for cylinder deactivation. The objective of this work is to (1) improve the latch response time when the system response is the slowest, and (2) balance the “ON” and “OFF” response time. A proper tradeoff was established to provide the minimum switching time such that deactivation and reactivation occurs seamlessly and in the right sequence. The response time optimization is accomplished while maintaining the existing packaging space of the overhead. A camshaft with a single lobe per SRFF device on a type II valvetrain was used as the baseline configuration for this study. A hydraulic and spring force model is developed using AMESim simulation software. A Design of Experiments (DOE) is conducted to characterize the system design of the latching mechanism subject to dimensional variations and oil properties including temperature and pressure. The baseline configuration requires approximately 12 milliseconds to deactivate the intake and exhaust valves and 18 milliseconds to re-enable the valves at a temperature of 10°C using 5W30 oil. The design goal is to equate both “ON” and “OFF” responses, while minimizing the response time in order to provide enough time to switch at 3500 engine rpm. The optimized design resulted in a balanced “ON” and “OFF” time of approximately 13.5 milliseconds for each, at 10°C oil temperature and 3.0 bar oil pressure. Model results combined with experimental verification are presented. The model correlated within 4.5% Root Mean Square error of the experimental results.
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