Cooling Loss Reduction in a High-Compression-Ratio HD Diesel Engine with an Optimized Combustion Chamber and a High Flow Rate Nozzle

Tomoyuki Mukayama･Noboru Uchida (New A.C.E. Institute)

To achieve even higher thermal efficiency in heavy-duty commercial diesel engines, achieving a higher compression ratio and developing novel designs and technologies, which can drastically reduce escalating cooling loss with increased compression ratio, are essential. In this study, following numerical investigation of an optimized combustion chamber geometry at a compression ratio of 23.5, the achieved design guideline was applied to a compression ratio of 26. As a result, significant cooling loss reduction effect was also experimentally confirmed with the prototype high-compression-ratio piston combined with a high flow rate nozzle with larger orifice diameter by utilizing a single-cylinder heavy-duty diesel engine.

CNN-Based Virtual Sensing of Rate of Heat Release for Fuel-Robust Diesel Engine Control (First Report)
-Rate of Heat Release Estimation and Improvement in Estimation Accuracy-

Ryo Sekiguchi･Takeshi Okamoto･Hisashi Ozawa (Isuzu Advanced Engineering Center)･Akihiro Yanai･Ratnak Sok･Jin Kusaka (Waseda University)

To enable the future use of diverse carbon-neutral fuels, robust combustion control is required to achieve target engine performance regardless of fuel properties, without fuel-specific engine calibration. In this study, RHR-based combustion control logic for feedback correction of engine control variables was developed using a convolutional neural network (CNN) -based rate of heat release (RHR) estimation method. The accuracy of RHR estimation was evaluated for diesel fuels with different cetane numbers using in-cylinder pressure and rotary-encoder-derived crank-angle acceleration. The results clarify the influence of training conditions and image resolution on estimation accuracy and demonstrate the feasibility of fuel-robust combustion control.

Effects of Fuel Physical Properties on Spray and Combustion Characteristics in a Diesel Engine
-Part1: Effects of Fuel Properties on Air Entrainment Near the Nozzle in Diesel Sprays-

Ryota Kobayashi･Gakuto Aizawa･Yoshio Zama (Gunma University)･Takeshi Hashizume (Toyota Motor)

The application of carbon-neutral (CN) fuels to compression-ignition engines has been expected to further reduce environmental impact. There is possibility that physical properties of CN fuels such as surface tension are different from those of conventional diesel fuel, and it is expected that characteristics of air entrainment induced by a spray are changed due to differences in the physical properties. Therefore, the surroundings gas flow of the spray near the nozzle exit was evaluated using a fluorescent PIV technique, and the effect of fuel physical properties on the air entrainment in a spray was investigated.

Effects of Fuel Physical Properties on Spray and Combustion Characteristics in a Diesel Engine
-(Part 2) Effects of Fuel Physical Properties on Combustion and Exhaust Gas Emission Characteristics-

Yuma Endo･Mitsuki Shida (Waseda University)･Takeshi Hashizume (Toyota Motor)･Jin Kusaka (Waseda University)

In this study, experiments were conducted using five fuels with different physical properties in order to clarify the effects of fuel physical properties on diesel combustion. A single-cylinder diesel engine was used as the test engine, and the air entrainment rate was estimated using a two-zone model. The results showed that earlier air entrainment enabled particulate matter reduction even at lower injection pressures than those used conventionally.

A study on Optimization of Combustion Chamber Geometry in Large Diesel Engines Using CFD and Machine Learning

Ryo Matsumae･Tomohiro Matsuda･Jin Kusaka (Waseda University)

Optimization of diesel engine combustion chamber geometry, including lip diameter, lip depth, and re-entrant angle, was conducted using thermal efficiency, soot, and NOx emissions as objective indices. An ANN-based surrogate model was developed to estimate the relationship between combustion chamber geometry and performance metrics, and PSO was applied for optimization. Sensitivity analysis clarified the influence of each geometric parameter, and chamber geometries achieving both improved thermal efficiency and reduced emissions were explored.

A study on Optimization of Combustion Chamber Geometry in Large Diesel Engines Using CFD and Machine Learning
-Analysis of the optimal shape that reflects the design intent-

Ryo Matsumae･Tomohiro Matsuda･Jin Kusaka (Waseda University)

This study evaluates the in-cylinder phenomena of two combustion chamber shapes optimized using Particle Swarm Optimization (PSO). For the balanced shape, suppressing excessive flow velocity reduced wall heat loss, achieving both low emissions and high thermal efficiency. In contrast, the efficiency-priority shape enhanced initial combustion and late-stage oxidation through increased turbulence and fuel spray collision with the lip edge. These results provide a physical basis for PSO-optimized designs and demonstrate that specific combustion strategies can be realized by adjusting the weighting factors of the objective functions in the PSO evaluation.