Multi-objective optimization of a hydrogen-fueled Wankel rotary engine based on machine learning and genetic algorithm

Wang, Huaiyu; Ji, Changwei; Cheng, Shen; Yang, Jinxin; Wang, Shuofeng; Ge, Yiyao; Chang, Ke; Meng, Hao; Wang, Xin

doi:10.1016/j.energy.2022.125961

Cited by 65 publications

(7 citation statements)

References 49 publications

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“…The impedances of each igniter component are expressed in Equations ( 12)-( 14). The calculation of the longitudinal vibration velocity is shown in Equations ( 15)-( 18), and the calculation of the vibration velocity ratio of the front and back mass of the igniter is shown in Equation (19).…”

Section: Calculation Methods Of Vibration Velocity Ratiomentioning

confidence: 99%

“…The optimal design of a high-energy ultrasonic igniter is carried out based on piezoelectric transducers. The non-dominated sorting genetic algorithm (NSGA-II) is widely used in engineering applications [19,20]. Based on the electromechanical equivalence method, Li et al accomplished the optimized design of an ultrasonic scalpel by using a response surface model and a multi-objective genetic algorithm [21].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Assessment of an Optimal Design Method for a High-Energy Ultrasonic Igniter Based on Multi-Objective Robustness Optimization

Sun

Zhi

et al. 2023

Sustainability

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The current deterministic optimization design method ignores uncertainties in the material properties and potential machining error which could lead to unreliable or unstable designs. To improve the design efficiency and anti-jamming ability of a high-energy ultrasonic igniter, a Six Sigma multi-objective robustness optimization design method based on the response surface model and the design of the experiment has been proposed. In this paper, the initial structural dimensions of a high-energy ultrasonic igniter have been obtained by employing one-dimensional longitudinal vibration theory. The finite element simulation method of COMSOL Multiphysics software has been verified by the finite element simulation results of ANSYS Workbench software. The optimal igniter design has been achieved by using the proposed method, which is based on the finite element method, the Optimal Latin Hypercube Design method, Grey Relational Analysis, the response surface model, the non-dominated sorting genetic algorithm, and the mean value method. Considering the influence of manufacturing errors on the igniter’s performance, the Six Sigma method was used to optimize the robustness of the igniter. The Eigenfrequency analysis and the vibration velocity ratio calculation were conducted to verify the design’s effectiveness. The results reveal that the longitudinal resonant frequency of the deterministic optimization scheme and the robustness optimization scheme are closer to the design’s target frequency. The relative error is less than 0.1%. Compared with the deterministic optimization scheme, the vibration velocity ratio of the robustness optimization scheme is 2.8, which is about 15.7% higher than that of the deterministic optimization scheme, and the quality level of the design targets is raised to above Six Sigma. The proposed method can provide an efficient and accurate optimal design for developing a new special piezoelectric transducer.

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Section: Calculation Methods Of Vibration Velocity Ratiomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Assessment of an Optimal Design Method for a High-Energy Ultrasonic Igniter Based on Multi-Objective Robustness Optimization

Sun

Zhi

et al. 2023

Sustainability

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“…The use of machine learning in engine optimization and calibration is becoming increasingly widespread and successful 27 . It is possible to use machine learning models to engine performance prediction and calibration.…”

Section: Calibration Map For Ic Enginementioning

confidence: 99%

Development of an ammonia-biodiesel dual fuel combustion engine's injection strategy map using response surface optimization and artificial neural network prediction

Elumalai,

Ravi,

Elumalai

et al. 2024

Sci Rep

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The study intends to calibrate the compression ignition (CI) engine split injection parameters as efficiently. The goal of the study is to find the best split injection parameters for a dual-fuel engine that runs on 40% ammonia and 60% biodiesel at 80% load and a constant speed of 1500 rpm with the CRDi system. To optimize and forecast split injection settings, the RSM and an ANN model are created. Based on the experimental findings, the RSM optimization research recommends a per-injection timing of 54 °CA bTDC, a main injection angle of 19 °CA bTDC, and a pilot mass of 42%. As a result, in comparison to the unoptimized map, the split injection optimized calibration map increases BTE by 12.33% and decreases BSEC by 6.60%, and the optimized map reduces HC, CO, smoke, and EGT emissions by 15.68%, 21.40%, 18.82, and 17.24%, while increasing NOx emissions by 15.62%. RSM optimization with the most desirable level was selected for map development, and three trials were carried out to predict the calibrated map using ANN. According to the findings, the ANN predicted all responses with R > 0.99, demonstrating the real-time reproducibility of engine variables in contrast to the RSM responses. The experimental validation of the predicted data has an error range of 1.03–2.86%, which is acceptable.

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“…As a result, there is an urgent need for the exploitation of other alternative sustainable energy sources. A promising alternative to future fossil fuel-based energy systems appears to be hydrogen energy [4]; hydrogen has a high energy density and its oxidation product consists of pure water, which is a sustainable green energy source with abundant reserves [5][6][7]. Moreover, hydrogen energy is also a widely discussed source of renewable energy with strong links to sustainability; it can be used as a clean energy source, and by using renewable energy sources, such as solar or wind, to generate hydrogen, dependence on conventional energy sources can be reduced.…”

Section: Introductionmentioning

confidence: 99%

Impact of the Structural Parameters on the Performance of a Regenerative-Type Hydrogen Recirculation Blower for Vehicular Proton Exchange Membrane Fuel Cells

Liang,

Kang,

Zeng

et al. 2024

Sustainability

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The compact structure and stable performance of regenerative blowers at small flow rates render them attractive for the development of hydrogen recirculation devices for fuel cells. However, its optimization of structural parameters has not been yet reported in the literature. Along these lines, in this work, a mechanistic study was carried out in terms of examining the role of the flow channel structure on the performance of a regenerative-type hydrogen recirculation blower for the fabrication of automotive fuel cells. A three-dimensional computational fluid dynamics (CFDs) model of the regenerative blower was established, and the accuracy of the proposed model was verified through experimental data. The impact of structural parameter interactions on the performance of the regenerative blower was investigated using CFD technology, response surface methodology (RSM), and genetic algorithm (GA). First, the range of the structural parameters was selected according to the actual operation, and the influence of a single geometric factor on the efficiency was thoroughly investigated using CFD simulation. Then, a second-order regression model was successfully established using RSM. The response surface model was solved using GA to obtain the optimized geometric parameters and the reliability of the GA optimization was verified by performing CFD simulations. From our analysis, it was demonstrated that the interaction of the blade angle and impeller inner diameter has a significant impact on efficiency. The entropy generation analysis showed also that the internal flow loss of the optimized regenerative blower was significantly reduced, and the design point efficiency reached 51.7%, which was significantly improved. Our work provides a novel solution for the design of a recirculation blower and offers a reference for the optimization of regenerative-type hydrogen blowers.

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Multi-objective optimization of a hydrogen-fueled Wankel rotary engine based on machine learning and genetic algorithm

Cited by 65 publications

References 49 publications

Assessment of an Optimal Design Method for a High-Energy Ultrasonic Igniter Based on Multi-Objective Robustness Optimization

Assessment of an Optimal Design Method for a High-Energy Ultrasonic Igniter Based on Multi-Objective Robustness Optimization

Development of an ammonia-biodiesel dual fuel combustion engine's injection strategy map using response surface optimization and artificial neural network prediction

Impact of the Structural Parameters on the Performance of a Regenerative-Type Hydrogen Recirculation Blower for Vehicular Proton Exchange Membrane Fuel Cells

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