Controlled Load and Speed Transitions in a Multicylinder Recompression HCCI Engine

Abstract

A model-based control strategy to track combustion phasing during load and speed transitions in the homogeneous charge compression ignition (HCCI) operating region of a multimode combustion engine is presented in this paper. HCCI transitions can traverse regions of high cyclic variability (CV), even if the steady state transition end points are stable with low CV. A control-oriented HCCI model for both the stable, low CV region and the oscillatory, high CV, late phasing region is used to design a controller that uses valve and fuel injection timings to track combustion phasing. Novel aspects of the controller include nonlinear model-inversion-based feedforward and gain scheduled feedback based on unburned fuel that reduces transient CV. Transitions tested on a multicylinder HCCI engine include load transitions at fixed engine speeds, simultaneous load, and speed transitions, and select FTP75 drive-cycle transitions with high load slew rates. Good combustion phasing tracking performance is demonstrated, and misfires are prevented.

Reduced Order Modeling for Multi-scale Control of Low Temperature Combustion Engines

“…The introduced proportional constant β 4 is eventually tuned to fit the model to measurement data. For the main compression on the other hand, a varying combustion efficiency η hr is introduced, which is initially presented in [6]. These incomplete combustions lead to a dynamic coupling between consecutive cycles.…”

“…Analogous to [6], the heat release during the intermediate compression is modeled in the beginning of the stage. The only change in the species' masses caused by fuel injection trivially is dm fuel = m inj,f .…”

Model-based control of gasoline-controlled auto-ignition

“…Linear quadratic regulator (LQR) control designed with a linearized semiphysical model is used in Hellstro¨m et al 13 In a study by Bidarvatan et al, 14 sliding mode control is used, and in Chiang et al, 15 adaptive control is used. Whereas in Jade et al, 16,17 a reference governor approach for respecting actuator constraints is used, and in Widd et al, 18 switching/hybrid controllers are used. An also commonly used method is model-based predictive control (MPC) as it is very well suited for the characteristics of the GCAI process and has therefore some key advantages compared to the other (nonlinear) control methods.…”

Real-time, adaptive machine learning for non-stationary, near chaotic gasoline engine combustion time series

“…Time series predictions were not shown, only a cloud of possible combustion timings ranging from stable to oscillatory. This fact was highlighted in an extension of the work [18] that again used random residual noise because "the actual time series of disturbances to the experiments are unknown." That said, these models are useful for showing that a period doubling cascade to chaos driven by residual gas fraction can explain the observed high CV behavior.…”