Transient emission simulation and optimization of turbocharged diesel engine

Abstract

In order to alleviate the pressure of experimental research of turbocharged diesel engine under transient operations, a whole process simulation platform for turbocharged diesel engine under transient operations was established based on the multi-software coupling technologies of Matlab/Simulink, GT-Power, STAR-CD and artificial neural network. Aimed at the contradiction of NO_x and soot emission control with exhaust gas recirculation (EGR) of turbocharged diesel engine under transient operations, on this simulation platform, a transient EGR valve control strategy was proposed, which adjusted the EGR valve in adjacent level based on the feedback of its opening according soot control limit under transient operations. Simulation and experimental results prove that the transient emission optimization effect of this control strategy is obvious. On the one hand, compared with the previous control strategy, which closed the EGR valve during the whole transient operations, soot emission is slightly increased by 9.5%, but it is still 9% lower than the control limit. On the other hand, compared with the previous control strategy, NO_x transient emission is reduced by 44%.

Keywords

diesel engine / transient simulation / emission / control strategy / exhaust gas recirculation (EGR)

Introduction

In order to meet the increasingly stringent emission regulations, combustion and emission performances of turbocharged diesel engine under transient operations become the research focus. It is very urgent to reduce transient emissions [1,2]. The effective combination of cleaning in-engine and out-engine is the main emission control technical route for diesel engine. Exhaust gas recirculation (EGR) is a cleaning in-engine technology of turbocharged diesel engine for reducing NO_x emission, but it will make soot emission deteriorated. Diesel particulate filters (DPF) can reduce soot emission out of the engine, but the cleaning effect cannot be 100%. Therefore, to reduce NO_x emission by EGR method, soot emission should be controlled below a certain limit so that with the aid of after-treatment system, the cleaning effect could meet the dual demands of NO_x and soot of transient emission regulations.

Constant speed increase torque (CSIT), as typical transient operations, is the research foundation of European transient cycle (ETC). Therefore, CSIT transient operations were taken as the research focus [3]. Experiments show that the contradiction between NO_x and soot emission is more serious under these operations. Thus, the purpose of this paper is to explore an effective control strategy to improve NO_x and soot trade-off relationship of turbocharged diesel engine with EGR system under CSIT operations.

Compared with the traditional experimental method, simulation method has the advantages of reducing test equipment investment, simplifying test process and shortening test time. Based on a large amount of transient and steady-state experimental data, a whole process simulation platform of turbocharged diesel engine under transient operations has been established. On this simulation platform, control strategies can be proposed, which would be verified by bench test in order to guide the simulation and modification of subsequent control strategies.

Establishment of the transient simulation platform of turbocharged diesel engine

Transient experimental measured and control platform

The experimental engine in this study is a 6DL2-35E3 turbocharged inter-cooled diesel engine equipped with high-pressure common rail, whose specifications are presented in Table 1.

As shown in Fig. 1, the electronic control system cooperated with the electric eddy current dynamometer can realize sampling control, EGR control and transient operation control. The EGR system is a low pressure loop system, of which the EGR valve can be controlled precisely with an error below 3% [4,5]. The A/D sampling system, which is made of millisecond timescale A/D data acquisition card and high-speed sensors, can sample the real-time measurement parameters, including speed, torque, intake/exhaust temperature and pressure, smoke opacity, emissions, and etc..

Backbone of transient simulation platform

GT-Power, a professional industry-standard engine simulation tool, can construct the engine model more quickly and accurately to predict the engine performance under steady-state or transient operations. Simulink, an important visual simulation tool of Matlab, can help user to build dynamic system feedback and control models.

Simulink can be coupled with GT-power to simulate the integrated working process of the electric control unit and diesel engine. On the one hand, the electric control unit (Simulink module) gathers the working process parameters (such as pressure, temperature, torque and speed, etc.) from the diesel engine (GT-Power module). On the other hand, the control commands return to the diesel engine, which are generated by the special control algorithms of the electric control unit. Therefore, the controllable parameters, such as fuel injection, injection timing, injection pressure, EGR valve opening, etc. can be adjustment through control strategies.

The establishing process of transient simulation platform includes three stages. In the first stage, the diesel engine model was established in the GT-Power. The simulation model would be verified and modified by the experimental data of various steady-state engine operations until the simulation results meet well with the experimental ones.

In the second stage, the status parameters of some important components were decoupled from the master control parameter set and written into their own parameters MAP, which can increase the flexibility of these components. Thus the quasi-transient simulation model was established. It is the foundation of transient simulation model.

In the last stage, based on the coupling technology of Simulink and GT-Power, the dynamometer of engine test bed was simulated to realize typical transient operations, such as CSIT. Furthermore, the engine parameters of GT-Power engine module were sent to the Simulink control unit module, and the control commands from the Simulink control unit were sent back to the GT-Power engine module. Thus, the transient simulation platform began to take shape.

Figure 2 describes the simulation results of engine parameters compared with the experimental results under CSIT operations without EGR. It is seen from Fig. 2 that during the period between the 5th and the 10th second, the speed remains constant at 1650 r/min, and the torque increases from 10% load torque (approximately 134 N·m) to 90% load torque (approximately 1265 N·m). The fuel injection keeps rising during the increasing torque process, but the air-fuel ratio reduces as a concave down curve. This is caused by the slow increase in the turbo speed, which leads to a delay of the intake response compared to fuel injection and causes the deterioration of combustion and emissions. It is also seen that, compared with the experimental results, not only the transient response time, but also the values of initial steady-state and target steady-state were simulated accurately, whose differences were less than 5% [6].

Transient complete parameters simulation platform

The GT-Power/Simulink simulation platform can simulate one-dimensional flow inside the cylinders and pipes accurately, but it cannot perform three-dimensional simulation. Therefore, to study the combustion process and pollutants formation mechanism, STAR-CD is adopted, which gains widespread acceptance for its excellent adaptability, accuracy, convergence and stability. Because the intake and exhaust process can be simulated by the couple of Simulink and GT-Power, STAR-CD was used in this study to explore the combustion and emissions reaction mechanism of the in-cylinder three-dimensional space from a microcosmic view. The boundary transient parameters of the intake and exhaust pipes of the engine were acquired from the GT-Power and Simulink simulation platform, and were defined in STAR-CD, such as the fuel injection quantity, air quantity, EGR rate, cylinder pressure, intake/exhaust temperature and pressure, etc. Thus, a transient complete parameters simulation platform was formed.

Figures 3 and 4 show a comparison of the STAR-CD simulation results and the experimental results on heat release rate and in-cylinder pressure under the operation condition of 1650 r/min, 50% load, and single-point 120 MPa fuel injection. It is observed from Figs. 3 and 4 that the simulation results conform with the experiment results, which proves that the partition of meshes, the selection of submodel algorithm and the setting of boundary condition parameters of the STAR-CD model are reasonable [7]. Consequently, coupled with the simulation platform backbone, the STAR-CD can be used to further explore the in-cylinder combustion and emissions of turbocharged diesel engine under transient operations.

Transient whole process simulation platform

To ensure the accuracy of study of the transient emissions of the turbocharged diesel engine, the transient simulation should involve in the simulation of the in-cylinder working process, the flow characteristics of the working medium in the pipe and the characteristics of transient response. Based on the ideal gas equation, mass conservation equation and energy conservation equation, STAR-CD can uncover the temperature variation and the flow characteristics of the working medium with the changes of the crank angle. But it has two drawbacks. On the one hand, because of the complexity of turbocharged diesel system, some assumption parameters restrict the accuracy of the calculation. On the other hand, in order to describe the inhomogeneity of temperature and concentration in the real cylinder, the whole cylinder volume is divided into many meshes, each of which should be calculated individually. It would take a long time to compute, which restricts the transient responsive performance of the model. Therefore, STAR-CD is not suitable for the research of transient emissions control strategies.

Artificial neural network (ANN) is a bionics computing model, which imitates the characteristics of the structure function of human being brain. It consists of a large amount of connecting neurons which can perform task of the information processing in parallel. Since ANN is adaptable, fault tolerant, accurate and anti-jamming, it has been widely used in the fields of automotive engine performance analysis, such as fault diagnosis, electronic control, expert systems, engine modeling etc. But it is not widely used in emissions prediction and control of turbocharged diesel engine under transient operations.

In this study, based on the back propagation (BP) algorithm, the input layer points include speed, torque, air-fuel ratio, EGR rate and composite transient rate ({\dot{C}}_{T\alpha }, described in Eq. (1)), and the output layer points can be the emission parameters, such as NO_x and soot. The nonlinear mapping relationships between the input layer and output layer were described by double hidden layers. Thus, the ANN transient emission module was formed. Coupled with it, a transient whole process simulation platform was established.

(1){\dot{C}}_{T\alpha }=\left({\dot{T}}_{\mathrm{tq}}+\dot{\alpha }a\right)b,

where {\dot{T}}_{\mathrm{tq}}is the torque variation in unit time during transient process (N·m/s), \dot{\alpha } is the air-fuel rate variation in unit time [1/s], a and b are both constants, which can be adjusted appropriately according to different transient operations.

Figures 5 and 6 show the comparison of the results of NO_x and soot between the simulation and the experiment under transient operations where the load increases by 40% during different transient times and the EGR rate is 7%. It can be seen that the experimental transient trends can be described by simulation, and the peak differences are less than 4%. The accuracy and rapid response ability of the transient whole process simulation platform are excellent for the study of emissions control strategies [8].

The simulation and experimental results show jointly that compared with the longer torque transient time (lower torque transient rate), the shorter transient torque time (higher torque transient rate) would cause more response delay of the turbocharger, which would lead to a lower transient oxygen concentration. Therefore, the decrease in NO_x emission and increase in soot emission became more obvious. It points out that the research focus of transient emission control strategies is to solve the trade-off relationship between NO_x and soot under high torque transient rate operations.

Dual optimization of NO_x and soot of turbocharged diesel engine under transient operations

EGR is an effective method to reduce the NO_x emission, but it would result in the deterioration of soot emissions, especially under CSIT operations. For this reason, appropriate control strategies should be developed to improve the trade-off relationship between NO_x and soot.

Under CSIT transient operations, the original EGR control strategy was to close the EGR valve at the beginning and open the EGR valve at the ending of the transient process [9,10]. Though it can effectively inhibit the rise of soot, it also causes the degradation of NO_x emission. Therefore, it cannot meet the duel optimization demands of NO_x and soot.

In order to facilitate the implementation of the control strategy, five kinds of EGR rates (11%, 9%, 7%, 3% and 0%) are described as corresponding EGR valve levels (the 5th level, the 4th level, the 3rd level, the 2nd level and the 1st level). In addition, experimental and simulation results are dimensionless to better contrast optimization effect. Equation (2) describes the dimensionless method.

(2)\overline{x_i}={\displaystyle \frac{x_i-x_{\min }}{x_{\max }-x_{\min }}}\times \mathrm{100}\%,

where x_i is the measurement value at one time point of transient emission, x_max and x_min indicate the maxima and minima, respectively, during the whole transient process, and \overline{x_i}is the dimensionless result.

Figure 7 introduces the idea of the EGR control strategy for the dual optimization of NO_x and soot. First, soot control limit was given according to actual need, which demands that soot should not exceed the control limit in the transient process.

As illustrated in Fig. 7(a), at the initial stage of the transient process, because of the lower soot emission, the larger EGR rate can be used, corresponding to the EGR valve at the 4th level. As the transient process continues, soot emission begins to rise. When it reaches the soot control limit, the EGR valve should be adjusted to the 3rd level, and, consequently, soot emission is decreased corresponding to the EGR valve at the 3rd level. When soot emission of the EGR valve at the 3rd level also reaches the control limit, the EGR valve should be adjusted to the 2nd level, and the like. In this process, as displayed in Fig. 7(b), NO_x emission increases step by step from of the time when the EGR valve is adjusted from the 4th level to the 3rd level, and the 2nd level. In the second half of the transient process, the lag of intake air behind fuel injection is alleviated, and soot begins to decrease from the peak. At that time, the EGR valve level can be increased step by step to reduce NO_x emissions.

The transient EGR valve control strategy module in Simulink is demonstrated in Fig. 8. First, the torque and EGR valve opening were acquired from the GT-Power engine to the Simulink control strategy module. The torque transient rate was computed by the torque and transient time. The soot control limit was input and the EGR valve opening was changed to the corresponding EGR valve level.

Secondly, fast soot and estimated soot would be calculated. The fast soot and the soot are both simulated based on artificial neural network technology, but the input layer parameters of the fast soot are the high transient responsive parameters, such as the torque, the torque transient rate and the EGR valve level. It makes the simulating speed of the fast soot faster than the soot. It is conducive to timely implement the control strategy. The simulating method of estimated soot is similar to the fast soot except that the input layer parameter, the torque, is coming from the next sample time. It would predict the soot value before the adjustment of the EGR valve and avoid the meaningless adjustment of the EGR valve.

Next, the EGR valve would be adjusted according to the torque transient rate, the current EGR valve level and the soot control limit. In high torque transient rate operation, when fast soot is higher than the control limit and the EGR valve is not at the lowest level, the EGR valve should be reduced a level. When fast soot is lower than the control limit and EGR valve level is not at the highest level, EGR valve could add a level. But it should ensure that the estimated soot would not exceed the limit after the EGR valve is increased to a level. Under other conditions, the EGR valve level remains unchanged. In low torque transient rate operation, the soot control limit can be extended to a control area. When fast soot is beyond this control area and the estimated soot is within the control area after the adjustment of the EGR valve, the EGR valve level will be changed, otherwise it should be kept still.

Finally, the EGR valve level will be changed back to the EGR valve opening and the feed back to the GT-Power engine module to control the EGR valve moving. Thus, the closed-loop control strategy based on the EGR valve opening feedback is formed.

Figure 9 is a comparison of soot simulation results and experimental ones when the engine speed is 1650 r/min and engine load is increased from 50% to 90% in 2 s (and 9.5 s). The horizontal line represents the dimensionless soot control limit. For clear comparison, the experimental results of the EGR valve which remains at constant levels are also exhibited. It is observed from Fig. 9 that the simulation results conform to the transient experimental trend and magnitude. During the CSIT transient process, along with the adjustment of the EGR valve level, soot emission is kept below the control limit consistently. Figure 10 shows the result of NO_x control. The transient trend simulation of NO_x emission is basically correct, except that the peak value is slightly lower than that of the experiment, which might be caused by the accuracy and responsive limitation of exhaust gas analysis equipment. Thus, the soot and NO_x emissions can be simultaneously optimized by the control strategies.

Aided by Eq. (3), the effect of the control strategy of dual optimization can be estimated from the total emission of NO_x or soot. On the one hand, compared with the original control strategies (during the transient process, when the EGR valve was completely closed), though soot increased by 9.5%, it is still 9% lower than the control limit, achieving the purpose of pruning the soot peak. On the other hand, NO_x is decreased by 44%.

(3)E={\displaystyle \underset{t_{\mathrm{1}}}{\overset{t_{\mathrm{2}}}{\int }}f(t)dt},

where f (t) is the curve of NO_x or soot emission under different control strategies, t₁ and t₂ are the beginning and ending time of the transient process, respectively, and E is the total emission of NO_x or soot during the transient process.

Conclusions

In order to reduce the investment in test equipment, simplify the test process and shorten the test time, a transient simulation platform of turbocharged engine is established based on the multi-software coupling technologies of Matlab/Simulink, GT-Power, STAR-CD and artificial neural network. Compared with the experimental results of the test diesel engine under different transient operations, the simulation results can describe the transient trends successfully, and the peak differences are less than 4%, which proves that the transient simulation platform is reasonable and effective.

Aimed at the contradiction between NO_x and soot emission control based on the EGR technology of turbocharged diesel engine under CSIT transient operations, a transient EGR valve control strategy is proposed, which adjusts the EGR valve in adjacent level based on the feedback of the EGR valve opening. The optimization effect of this control strategy for NO_x and soot emission is obvious. On the one hand, compared with the previous control strategy, which closed the EGR valve during the whole transient operations, soot emission is slightly increased by 9.5%, but it is still 9% lower than the control limit. On the other hand, compared with the previous control strategy, NO_x transient emission is reduced by 44%.

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