A Ramesh

In this work an Engine Management System (EMS) using a low cost 8-bit microcontroller specifically for the cost sensitive small two-wheeler application was designed and developed. Only the Throttle Position Sensor (TPS) and the cam position sensor (also used for speed measurement) were used. A small capacity 125CC four stroke two-wheeler was converted into a Port Fuel Injected (PFI) engine and was coupled to a fully instrumented Eddy Current Dynamometer. Air-fuel ratio was controlled using the open loop, lookup-table [speed (N) and throttle (α)] based technique. Spark Time was controlled using a proportional / fuzzy logic based close loop control algorithm for the idle speed control to reduce fuel consumption and emissions. Test results show a significant improvement in engine performance over the original carbureted engine, in terms of fuel consumption, emissions and idle speed fluctuations. The Proportional controller resulted in significantly lower speed fluctuations and HC / CO emissions than the fuzzy logic controller. Though the fuzzy logic controller resulted in low cycle by cycle variations than the original carbureted engine, it leads to significantly higher HC levels. The performance fuzzy logic can be improved by modifying the membership function shapes with more engine test data. Copyright © 2007 by ASME.

A two-degree freedom air fuel ratio controller (Model based feed forward transient plus closed loop Proportional Integral-Derivative (PID) steady state controllers) developed for controlling the air fuel ratio of the charge in a small displacement (125 CC) SI engine is presented. The feed forward controller's airflow and injector models were developed after conducting extensive experiments on the engine modified for the Port Fuel Injection (PFI) operation. A dynamic air fuel ratio model obtained (air fuel ratio changes measured using an UEGO sensor) by injecting the Pseudo Random Binary Signal (PRBS) signal in addition to base line fuel injection pulse, was used for designing the PID controller. Optimal PID gain values were identified using Nelfer-Mead optimization technique. The control algorithms were implemented and optimized using SIMULINK blocks that are run under dSPACE on the MicroAuto box hardware. The optimized control algorithms were ported on the specially designed, in-house built, low cost engine management system (EMS) developed around an 8-bit microcontroller. The spark timing was also controlled simultaneously for knock free operation. The two-degree freedom air fuel ratio controller could maintain the air fuel ratio under steady and transient conditions closely. High thermal efficiency and low HC & NOx emissions were achieved using the developed EMS. At higher speed elevated NOx emission was observed, due to the use of leaner mixture. The improvements are expected to be higher if a suitable smaller injector is used. Copyright © 2012 by ASME.

In this work an Engine Management System (EMS) using a low cost 8-bit microcontroller specifically for the cost sensitive small two-wheeler application was designed and developed. Only the Throttle Position Sensor (TPS) and the cam position sensor (also used for speed measurement) were used. A small capacity 125CC four stroke two-wheeler was converted into a Port Fuel Injected (PFI) engine and was coupled to a fully instrumented Eddy Current Dynamometer. Air-fuel ratio was controlled using the open loop, lookup-table [speed (N) and throttle (α)] based technique. Spark Time was controlled using a proportional / fuzzy logic based close loop control algorithm for the idle speed control to reduce fuel consumption and emissions. Test results show a significant improvement in engine performance over the original carbureted engine, in terms of fuel consumption, emissions and idle speed fluctuations. The Proportional controller resulted in significantly lower speed fluctuations and HC / CO emissions than the fuzzy logic controller. Though the fuzzy logic controller resulted in low cycle by cycle variations than the original carbureted engine, it leads to significantly higher HC levels. The performance fuzzy logic can be improved by modifying the membership function shapes with more engine test data.