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

H Wang, C Ji, C Shi, J Yang, S Wang, Y Ge, K Chang… - Energy, 2023 - Elsevier
Hydrogen is a promising way to achieve high efficiency and low emissions for Wankel rotary
engines. In this paper, the intake and exhaust phases and excess air ratios (λ) were …

Optimizing photovoltaic thermal solar systems efficiency through advanced artificial intelligence driven thermal management techniques

WM Shaban, AE Kabeel, MEH Attia… - Applied Thermal …, 2024 - Elsevier
Abstract Photovoltaic Thermal (PV/T) solar systems have the capacity to convert solar
radiation into both electrical and thermal energy. Solar cells convert solar radiation into …

Energy management strategy for plug-in hybrid electric vehicles based on driving condition recognition: a review

C Liu, Y Liu - Electronics, 2022 - mdpi.com
Appropriate energy management strategies (EMSs) have been selected for plug-in hybrid
electric vehicles (PHEVs) based on driving-condition recognition (DCR) according to the …

Artificial neural network for predicting the thermal conductivity of soils based on a systematic database

KQ Li, Q Kang, JY Nie, XW Huang - Geothermics, 2022 - Elsevier
Thermal conductivity is a significant soil property that affects subsurface temperature
distribution and plays an essential role in geotechnical engineering. Accurate evaluation of …

[HTML][HTML] Artificial neural networks-based performance and emission characteristics prediction of compression ignition engines powered by blends of biodiesel derived …

S Patnaik, N Khatri, ER Rene - Fuel, 2024 - Elsevier
Compression ignition engines are essential for power generation, yet the use of fossil fuels
like petrol and diesel results in the emission of harmful toxins into the atmosphere, leading to …

Prediction of cold start emissions for hybrid electric vehicles based on genetic algorithms and neural networks

D Tang, Z Zhang, L Hua, J Pan, Y **ao - Journal of Cleaner Production, 2023 - Elsevier
The emission of hybrid electric vehicles deteriorates during cold start, and it is a cost-
effective method to reduce pollutant emissions during cold start of hybrid electric vehicles …

Machine learning assisted analysis of an ammonia engine performance

Z Liu, J Liu - Journal of Energy Resources …, 2022 - asmedigitalcollection.asme.org
Currently, the interest in utilizing ammonia in internal combustion engines stems from the
trend toward decarbonization, as ammonia is a zero-carbon footprint fuel. Existing studies …

Prediction of the transient emission characteristics from diesel engine using temporal convolutional networks

J Liao, J Hu, P Chen, L Zhu, Y Wu, Z Cai, H Wu… - … Applications of Artificial …, 2024 - Elsevier
In order to predict the transient emission characteristics from diesel engine accurately and
quickly, a novel prediction model, based on temporal convolutional networks (TCN) that …

[HTML][HTML] Application of Bayesian regularization back propagation neural network in sensorless measurement of pump operational state

D Wu, H Huang, S Qiu, Y Liu, Y Wu, Y Ren, J Mou - Energy Reports, 2022 - Elsevier
Under the strategic framework of global carbon emission reduction, it is urgent to reduce the
energy consumption of centrifugal pumps. Monitoring pump's operational states can …

[HTML][HTML] Performance and safety of transport vehicles fueled with alternative fuels in plateau environment: A review

W Guo, H Wang, H Chen, B Yu, Y Wang… - Journal of traffic and …, 2022 - Elsevier
Alternative fuels including natural gas, alcohols and biodiesel for transport vehicles have
been applied worldwidely. However, the performance and safety of alternative fuel vehicles …