Fuel Saving Strategy in Spark Ignition Engine Using Fuzzy Logic Engine Torque Control

Abstract

In the case of injection gasoline engine, or better known as spark ignition engines, an effort to improve engine performance as well as to reduce fuel consumption is a fairly complex problem. Generally, engine performance improvement efforts will lead to increase in fuel consumption. However, this problem can be solved by implementing engine torque control based on intelligent regulation such as the fuzzy logic inference system. In this study, fuzzy logic engine torque regulation is used to control the throttle position entered by the driver to achieve optimal engine torque. An engine torque vs. throttle position and engine speed mapping for vehicles with economical function is used to build this control process regulation. From the simulation result, it can be concluded that this control strategy is very effective to reduce fuel consumption and simultaneously to optimize the engine performance. Abstrak Strategi Penghematan Bahan Bakar pada Mesin dengan Pemicu Busi Melalui Kontrol Torsi Mesin denganLogika Fuzzy. Pada kasus kontrol mesin bensin, atau lebih dikenal sebagai mesin pengapian busi, upaya untuk meningkatkan kinerja mesin sekaligus mengurangi konsumsi bahan bakar adalah masalah yang cukup kompleks. Umumnya, upaya peningkatan performa mesin akan menyebabkan peningkatan konsumsi bahan bakar. Namun, hal ini dapat diselesaikan dengan melakukan kontrol torsi mesin berdasarkan peraturan cerdas seperti sistem inferensi logika fuzzy. Dalam studi ini, regulasi torsi mesin dengan logika fuzzy digunakan untuk mengontrol posisi throttle yang dimasukkan oleh pengemudi untuk mencapai torsi mesin yang optimal. Pemetaan torsi mesin vs posisi throttle dan kecepatan putar mesin untuk kendaraan dengan tujuan ekonomis digunakan untuk mendesain aturan proses kontrol. Dari hasil simulasi dapat disimpulkan bahwa strategi kontrol dengan logika fuzzy sangat efektif untuk mengurangi konsumsi bahan bakar dan sekaligus mengoptimalkan kinerja mesin.

Multi-criteria Genetic Algorithm Optimization Approach for Balancing Bicopter Control

“…Genetic Algorithm (GA) which uses the principle of natural selection process can be an example. It can search global optimal solution for optimization problem that makes GA is a promising way to produce more accurate and appropriate gains for a controller [19], [20].…”