Premixed and Compression Ignition Combustion in Heavy Duty Diesel Engine

2002 ◽  
Vol VIII.02.1 (0) ◽  
pp. 328-329
Author(s):  
Yuzo AOYGI
2019 ◽  
Vol 21 (3) ◽  
pp. 470-483 ◽  
Author(s):  
Mojtaba Ebrahimi ◽  
Mohammad Najafi ◽  
Seyed Ali Jazayeri

The aim of this study is to implement the multi-input–multi-output optimization of reactivity-controlled compression-ignition combustion in a heavy-duty diesel engine running on natural gas and diesel fuel. A single-cylinder heavy-duty diesel engine with a modified bathtub piston bowl profile is set on operation at 9.4 bar indicated mean effective pressure and running at a fixed engine speed of 1300 r/min. A certain amount of diesel fuel mass per cycle is fed into the engine at a fixed equivalence ratio without any exhaust gas recirculation. The optimization targets include reduction in engine emissions as much as possible, avoiding diesel knock occurrence, and achieving low temperature combustion concept with the least or no engine power losses. To implement the optimization, the effects of three control factors on the engine performance are assessed by the design of experiment concept—fractional factorial method. These selected control factors are intake temperature and intake pressure (both at intake valve closing) and the diesel fuel start of injection timing. Some randomized treatment combinations of chosen levels from the three selected control factors are employed to simulate reactivity-controlled compression-ignition combustion. Based on the engine’s responses derived from the simulation, reactivity-controlled compression-ignition combustion’s mathematical model is identified directly using an artificial neural network. Next, an optimization process is conducted using two different optimization algorithms, namely, genetic algorithm and particle swarm optimization algorithm. For assessing and validating the obtained optimal results, the obtained data are used to simulate reactivity-controlled compression-ignition combustion as the engine input factors. The results show that the proposed artificial neural network design is effectively capable of identifying reactivity-controlled compression-ignition combustion’s mathematical model. Also, by optimizing reactivity-controlled compression-ignition combustion through different optimization algorithms, the optimal range of the engine operation at 9.4 bar indicated mean effective pressure is well estimated and extended.


2017 ◽  
Vol 19 (7) ◽  
pp. 774-789 ◽  
Author(s):  
Mojtaba Ebrahimi ◽  
Mohammad Najafi ◽  
Seyed Ali Jazayeri ◽  
Ali Reza Mohammadzadeh

The aim of this study is to investigate in details the effects of a number of combustion parameters to optimize the reactivity controlled compression ignition operation running on natural gas and diesel fuel. In the present work, a single-cylinder heavy-duty diesel engine with a specially modified bathtub piston bowl profile for reactivity controlled compression ignition operation is studied and simulated through commercial software. A broad load range from 5.6 to 13.5 bar indicated mean effective pressure at a constant engine speed of 1300 r/min, fixed amount of diesel fuel mass, and with no exhaust gas recirculation is considered. The results from the developed model confirm that the model can accurately simulate the reactivity controlled compression ignition combustion. Also, by focusing on the time of formation of certain important radicals in combustion, the start of combustion and the time of natural gas dissociation are accurately predicted. Furthermore, the influence of some parameters such as different diesel fuel injection strategies, intake temperature, and intake pressure on the reactivity controlled compression ignition combustion is evaluated and the limitation of the engine operation at low temperature combustion is investigated.


Author(s):  
Yu Zhang ◽  
Yuanjiang Pei ◽  
Meng Tang ◽  
Michael Traver

Abstract This study computationally investigates the potential of utilizing gasoline compression ignition (GCI) in a heavy-duty diesel engine to address a future ultra-low tailpipe NOx standard of 0.027 g/kWh while achieving high fuel efficiency. By conducting closed-cycle, full-geometry, 3-D computational fluid dynamics (CFD) combustion simulations, the effects of piston bowl geometry, injector spray pattern, and swirl ratio (SR) were investigated for a market gasoline. The simulations were performed at 1375 rpm over a load range from 5 to 15 bar BMEP. The engine compression ratio (CR) was increased from 15.7 used in previous work to 16.5 for this study. Two piston bowl concepts were studied with Design 1 attained by simply scaling from the baseline 15.7 CR piston bowl, and Design 2 exploring a wider and shallower combustion chamber design. The simulation results predicted that through a combination of the wider and shallower piston bowl design, a 14-hole injector spray pattern, and a swirl ratio of 1, Design 2 would lead to a 2–7% indicated specific fuel consumption (ISFC) improvement over the baseline by reducing the spray-wall interactions and lowering the in-cylinder heat transfer loss. Design 1 (10-hole and SR2) showed a more moderate ISFC reduction of 1–4% by increasing CR and the number of nozzle holes. The predicted fuel efficiency benefit of Design 2 was found to be more pronounced at low to medium loads.


Author(s):  
Meng Tang ◽  
Yuanjiang Pei ◽  
Hengjie Guo ◽  
Yu Zhang ◽  
Roberto Torelli ◽  
...  

Abstract A design optimization campaign was conducted to search for improved combustion profiles that enhance gasoline compression ignition in a heavy-duty diesel engine with a geometric compression ratio of 17.3. Three-dimensional computational fluid dynamics simulations were employed using the software package CONVERGE. A large-scale design of experiments (DoE) approach was used for the optimization. The main parameters explored include geometric features, injector specifications, and swirl motion. Both stepped-lip bowls and re-entrant bowls were included in the optimization effort in order to assess their respective performance implications. A total of 256 design candidates were prepared using the software package CAESES for automated and simultaneous geometry generation and combustion recipe perturbation. The design optimization was conducted for three engine load points representing light to medium load conditions. The design candidates were evaluated for fuel efficiency, emissions, fuel-air mixing characteristics, and global combustion behavior. Simulation results show that the optimum designs were all stepped-lip bowls, which exhibited better overall performance than re-entrant bowls due to improvements in fuel-air mixing, as well as reduced heat loss and emissions formation. Improvements in indicated specific fuel consumption of up to 3.2% were achieved while meeting engine-out NOx emission targets of 1–1.5 g/kW·hr. Re-entrant bowls performed worse compared to the baseline design, and significant performance variations occurred across the load points. Specifically, the re-entrant bowls were on par with the stepped-lip bowls under light load conditions, but significant deteriorations occurred under higher load conditions. As a final task, selected optimized designs were then evaluated under simulated full-load conditions.


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