Modeling and Control of Combustion Phasing in Dual-Fuel Compression Ignition Engines

Abstract

Dual fuel engines can achieve high efficiencies and low emissions but also can encounter high cylinder-to-cylinder variations on multi-cylinder engines. In order to avoid these variations, they require a more complex method for combustion phasing control such as model-based control. Since the combustion process in these engines is complex, typical models of the system are complex as well and there is a need for simpler, computationally efficient, control-oriented models of the dual fuel combustion process. In this paper, a mean-value combustion phasing model is designed and calibrated and two control strategies are proposed. Combustion phasing is predicted using a knock integral model, burn duration model and a Wiebe function and this model is used in both an adaptive closed loop controller and an open loop controller. These two control methodologies are tested and compared in simulations. Both control strategies are able to reach steady state in 5 cycles after a transient and have steady state errors in CA50 that are less than ±0.1 crank angle degree (CAD) with the adaptive control strategy and less than ±1.5 CAD with the model-based feedforward control method.

Modeling combustion timing in an RCCI engine by means of a control oriented model

“…Similar modeling has been done by Shahbakhti in 2016 [18] and Khodadadi Sadabadi, K. et al in 2010 [20]. Recently in 2019, Sui W and Pulpeiro et al used two different close loop and open loop controller to estimate combustion characteristic of an RCCI six cylinder engine [21]. Genetic Algorithm (GA) also was used to predict start of combustion in a HCCI engine, M.Taghavi et al, in their study Artificial Neural Network (ANN) was used as a low computational time consuming method to predict SOC.…”

“…In Wiebe function, equation ( 19),𝑥 𝑏 is fraction of fuel burnt in each CAD and 𝜃 𝑑 is burning duration in CAD, equation 20 [21].This relation of burn duration shows dependency of combustion duration to different input variables such as global equivalence ratio of each fuels and dilution factor, dilution factor represents both EGR and residual gasses and depends on valve timing, engine speed, fuel amount, intake manifold pressure and exhaust manifold pressure was calculated from equation 21 [20]. Using equation 20 to model CA50 provides more mathematically control on direct calibration of CA50 which was used also by A. Raut, et al, in 2018 [38] 𝜃 𝑑 = 𝐶(1 + 𝑥 𝑑 ) 𝐷 (φ DI 𝑏 1 + φ PFI 𝑏 2 )…”

“…As discussed, Wiebe function is used to model CA50 using equations (19)(20)(21). According to these equations 𝐶, 𝑑, 𝑚, 𝑎, a 1 and a 2 should be calibrated.…”

“…[20] and Akshat Raut et al in 2018 [38]. Sui W et al used a delay time which is a function of global equivalence ratio of each fuel, temperature, pressure and EGR [21]. In current study a delay time function is a function of equivalence ratio of each fuel, inlet oxygen percentage, temperature, pressure and Cetane number of fuel mixture with focusing on calibration CA50 and IMEP.…”

“…However, COM was used for modeling of the RCCI engine combustion which works with two fuels such as gasoline as LRF and diesel as HRF which are also considered in MKIM equations. In fact, this type of combustion is related to fuel mixture reactivity and the oxygen concentration [17,21]. Calibration and validation of modeling is performed using five experimental data type those are various in variation of input parameters, about 5000 cycles data points.…”