**2.7 Transient engine simulation**

270 Computational Simulations and Applications

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et al., 2010).

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**0.2 0.4 0.6 0.8 1 Normalized engine speed [-]**

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**WOT**

**4.2% load**

(a) (b)

**4.2% load**

(c) (d)

**4.2% load**

(e) (f)

Fig. 5. Model results under steady-state working conditions, as functions of the engine speed. (a): Manifold Absolute Pressure; (b): air mass-flow rate; (c): Pressure at the turbine inlet (cylinder 1 side); (d): Temperature at the turbine inlet; (e): Peak Firing Pressure

(cylinder 1); (f): Engine brake torque. Each quantity is normalized to a specific value (Baratta

calibration was made with reference to the engine model without the turbocharger. Subsequently, turbocharger and intercooler (IC) were added and the pressure at the turbine outlet was tuned first, acting on the friction multipliers of the pipes located downstream from the turbine. Then, the turbine MFM and EM were adjusted so as to match both the

**simulated experimental**

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The simulation of the transient behaviour of an engine by means of a 1-D simulation code is more challenging than a steady-state modelling approach. In fact, in a steady-state simulation, only the 'converged' results are significant, and the code is run until the differences in the engine variables are negligible in two consecutive simulated cycles. In a transient simulation, in which the engine speed and/or load versus time change, the model should accurately reproduce not only the engine variable at the end of the transient, but also their evolution versus time.

Engine models that have to be used for transient simulation need a more careful calibration. In particular, it is not sufficient to set the model parameters with reference to the steady-state full-load conditions. This holds for all submodels, and was demonstrated in (Lefebvre & Guilain, 2006) for the combustion model. In fact, by simulating load transients using constant full-load combustion parameters, the model results presented unacceptable deviations from the experimental ones, and did not allow transient behaviour to be predicted correctly, or different engine configurations to be compared. The model inaccuracy decreased when the combustion process was modelled as a function of the engine load and speed, and the maps were included in GT-Power, and it was further reduced when the same procedure was followed for the in-cylinder heattransfer coefficient (c0 in Eq. (8)). A similar procedure was followed in (Baratta et al., 2010). The following aspects should also be taken into account:


Numerical Simulation Techniques for the

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2010).

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**alized M**

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to the observed difference in gas temperatures.

Prediction of Fluid-Dynamics, Combustion and Performance in IC Engines Fuelled by CNG 273


**simulated experimental**

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Fig. 6. Model results under transient working conditions (load step at constant engine speed, N = 0.55 Nmax). (a) manifold absolute pressure, (b) boost pressure, (c) pressure at the turbine inlet (cylinder 1 side), (d) temperature at the turbine inlet (cylinder 1 side), (e) air mass-flow rate, (f) engine brake torque. Each quantity is normalized to a specific value (Baratta et al.,

**alized brake torque [-]**

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(a) (b)

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(e) (f)

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**alized boost**

**pressure [-]**

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'numerical' one. This can be achieved by running the model for a few seconds before the start of the 'actual' transient phase.


Figure 6 (Baratta et al., 2010) shows the model calibration results for a tip-in event of the engine under study. The throttle was opened abruptly and the torque was varied from about 4.2% load to the steady-state values at WOT. Before applying the model to the transient simulations, the following changes were made:


The model resulted to be well calibrated. In fact, not only were the asymptotic values well reproduced but also the simulated slopes that occurred during the transient were comparable to the experimental ones. However, some discrepancies were observed in the time-histories of the temperature at the turbine inlet (Fig. 6d) and the brake torque (Fig. 6f). The main differences between simulated and experimental Tin,trb time-histories are that:




Figure 6 (Baratta et al., 2010) shows the model calibration results for a tip-in event of the engine under study. The throttle was opened abruptly and the torque was varied from about 4.2% load to the steady-state values at WOT. Before applying the model to the



The model resulted to be well calibrated. In fact, not only were the asymptotic values well reproduced but also the simulated slopes that occurred during the transient were comparable to the experimental ones. However, some discrepancies were observed in the time-histories of the temperature at the turbine inlet (Fig. 6d) and the brake torque (Fig. 6f). The main differences between simulated and experimental Tin,trb time-histories



was accurately simulated, taking the gas-wall heat transfer into account;

the start of the 'actual' transient phase.

scheme that accounts for thermal inertia.

different load-transient simulations.

flow and was included in the model.

are that:

Ångström, 2003).

transient simulations, the following changes were made:

2010; Westin & Ångström, 2003; Westin, 2005).

'numerical' one. This can be achieved by running the model for a few seconds before


Fig. 6. Model results under transient working conditions (load step at constant engine speed, N = 0.55 Nmax). (a) manifold absolute pressure, (b) boost pressure, (c) pressure at the turbine inlet (cylinder 1 side), (d) temperature at the turbine inlet (cylinder 1 side), (e) air mass-flow rate, (f) engine brake torque. Each quantity is normalized to a specific value (Baratta et al., 2010).

Numerical Simulation Techniques for the

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is normalized to a specific value.

**3.1 Introduction and overview** 

different approaches (Baratta et al ., 2006).

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**pressure [-]** **0.5**

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**1**

Prediction of Fluid-Dynamics, Combustion and Performance in IC Engines Fuelled by CNG 275

**experimental simulated**

**0 0.25 0.5 0.75 Normalized time [-]**

Fig. 7. Load step for an engine coupled to a stalled torque converter (Baratta & Spessa, 2009): experimental (solid black line) and simulated (red dotted line) time histories. Each quantity

The goal of a predictive combustion model is to predict the rate at which the unburned mixture is converted into burned gases. This allows the computation of the in-cylinder pressure through Eqs. (4-6). The different models are based on the definition of a 'turbulent burning velocity', Sb, and of a flame burning-front area Abf, whereas the flame-brush thickness is generally neglected. The flame area is often modelled assuming a spherical shape of the flame front, which gradually intersects the combustion chamber surfaces as it grows (see, among others, Baratta et al., 2008; Bozza et al., 2005; Wahiduzzaman et al., 1993). This assumption has been confirmed by experiments, at least for combustion chambers with sufficiently low swirl and tumble ratios. In a thermo-dynamic modelling approach, this is also the most reasonable a priori choice. In fact, a sub-model for the flame deformation by the in-cylinder flow would need detailed information on the flow motion characteristics,

The evolution equation for the burned-gas mass fraction xb can be derived adopting two

which is not compatible with the thermo-dynamic nature of the overall model.

The slight difference between the calculated and the measured brake torque at the transient end (Fig. 6f) can primarily be ascribed to an underestimation of the gas pressure contribution to the friction mean effective pressure under full-load operations.

(Baratta & Spessa, 2009) modified the previous model with reference to the engine installation on a commercial vehicle for urban transportation. The model was extensively revised by modifying the pertinent pipe, bend and 'flowsplit' objects. In addition, the following differences were considered with respect to the dyno test-bed configuration:


The new model was tuned on the basis of a specific test, in which the hydraulic torque converter of the considered urban bus was kept under stall conditions by means of the vehicle brakes, while a quick opening of the throttle valve was actuated. Throughout this transient process, the engine torque demand was thus proportional to N2. As an example, Fig. 7 compares the experimental (black solid line) and simulated (red dotted line) timehistories of the boost pressure, mass flow rate and engine speed for a load step from N / Nmax = 0.3 to 0.8. The same EM profile versus PR was used as in (Baratta et al., 2010).

## **3. Predictive 0-D combustion models**

The reliability of the 1-D approach can be improved if predictive 0-D combustion models are used to predict the heat-release rate within the engine combustion chamber. The turbulent combustion process is a complex phenomenon that involves many chemical, thermodynamic and fluid-dynamic aspects, which should be studied by adopting a three-dimensional approach. However, as discussed in great detail by (Lipatnikov & Chomiak, 2002), even in this case, the development of a fundamentally substantiated model, that is, a model which is based only on the application of 'first principles', is very difficult. A possible, practical solution is that of shifting from the first principles to phenomenology, i.e., in the use of well established experimental facts and approximate descriptions of selected combustion-process characteristics which are assumed to be the main controlling factors. Similarly, predictive 0-D combustion models, which are the topic of this section, are based on a phenomenological description of the turbulent combustion process of a premixed fuelair mixture. Although they generally need a preliminary tuning procedure, they can potentially predict the dependence of the heat-release rate on, among other factors, incylinder flow, combustion chamber geometry, mixture composition, thermodynamic state, and spark timing. Since the pioneering work of (Blizzard & Keck, 1974), a large number of papers have been published, which have focused on the development and/or the application of predictive combustion models to SI engines. A rather good review of the main aspects that have to be faced in a thermodynamic combustion model formulation can be found in (Velherst & Sheppard, 2009).

Fig. 7. Load step for an engine coupled to a stalled torque converter (Baratta & Spessa, 2009): experimental (solid black line) and simulated (red dotted line) time histories. Each quantity is normalized to a specific value.
