Luciano Rolando

1.0k total citations
52 papers, 723 citations indexed

About

Luciano Rolando is a scholar working on Automotive Engineering, Fluid Flow and Transfer Processes and Electrical and Electronic Engineering. According to data from OpenAlex, Luciano Rolando has authored 52 papers receiving a total of 723 indexed citations (citations by other indexed papers that have themselves been cited), including 45 papers in Automotive Engineering, 26 papers in Fluid Flow and Transfer Processes and 18 papers in Electrical and Electronic Engineering. Recurrent topics in Luciano Rolando's work include Electric and Hybrid Vehicle Technologies (28 papers), Vehicle emissions and performance (27 papers) and Advanced Combustion Engine Technologies (26 papers). Luciano Rolando is often cited by papers focused on Electric and Hybrid Vehicle Technologies (28 papers), Vehicle emissions and performance (27 papers) and Advanced Combustion Engine Technologies (26 papers). Luciano Rolando collaborates with scholars based in Italy, France and United States. Luciano Rolando's co-authors include Federico Millo, Fabio Mallamo, Domenico Bianchi, Giorgio Rizzoni, Pengju Kang, Simona Onori, Lorenzo Serrao, Marco Badami, Andrea Piano and Riccardo Rossi and has published in prestigious journals such as Applied Energy, International Journal of Hydrogen Energy and Energy.

In The Last Decade

Luciano Rolando

48 papers receiving 681 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Luciano Rolando Italy 15 599 386 234 105 49 52 723
Fabio Mallamo Italy 13 449 0.7× 116 0.3× 413 1.8× 98 0.9× 52 1.1× 22 635
Eric Rask United States 12 418 0.7× 230 0.6× 150 0.6× 26 0.2× 101 2.1× 28 525
G. Pede Italy 13 456 0.8× 377 1.0× 60 0.3× 22 0.2× 42 0.9× 58 560
Sylvain Pagerit United States 14 538 0.9× 383 1.0× 81 0.3× 17 0.2× 60 1.2× 21 597
Manbae Han South Korea 14 314 0.5× 77 0.2× 334 1.4× 106 1.0× 47 1.0× 46 574
Surbhi Aggarwal India 9 88 0.1× 156 0.4× 111 0.5× 162 1.5× 50 1.0× 17 386
Ahu Ece Hartavi Karcı United Kingdom 6 255 0.4× 176 0.5× 105 0.4× 12 0.1× 129 2.6× 7 432
Stephanie Stockar United States 12 456 0.8× 334 0.9× 89 0.4× 14 0.1× 103 2.1× 49 567
Yusoff Ali Malaysia 11 97 0.2× 64 0.2× 94 0.4× 45 0.4× 33 0.7× 22 327
Massimiliano Muccillo Italy 14 119 0.2× 112 0.3× 159 0.7× 20 0.2× 89 1.8× 33 511

Countries citing papers authored by Luciano Rolando

Since Specialization
Citations

This map shows the geographic impact of Luciano Rolando's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Luciano Rolando with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luciano Rolando more than expected).

Fields of papers citing papers by Luciano Rolando

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Luciano Rolando. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Luciano Rolando. The network helps show where Luciano Rolando may publish in the future.

Co-authorship network of co-authors of Luciano Rolando

This figure shows the co-authorship network connecting the top 25 collaborators of Luciano Rolando. A scholar is included among the top collaborators of Luciano Rolando based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Luciano Rolando. Luciano Rolando is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Rolando, Luciano, et al.. (2025). A Cutting-Edge Energy Management System for a Hybrid Electric Vehicle relying on Soft Actor–Critic Deep Reinforcement Learning. Transportation Engineering. 19. 100308–100308. 2 indexed citations
2.
Prussi, Matteo, et al.. (2025). Life Cycle Assessment of Different Powertrain Alternatives for a Clean Urban Bus Across Diverse Weather Conditions. Energies. 18(17). 4522–4522. 1 indexed citations
3.
4.
Rolando, Luciano, et al.. (2024). Development of a Soft-Actor Critic Reinforcement Learning Algorithm for the Energy Management of a Hybrid Electric Vehicle. SAE International Journal of Advances and Current Practices in Mobility. 7(3). 1140–1151. 1 indexed citations
5.
Rolando, Luciano, et al.. (2024). Comparison of hydrogen-fueled powertrains for urban bus applications — design, modeling, and energy management. International Journal of Hydrogen Energy. 110. 560–574. 3 indexed citations
6.
Rolando, Luciano, et al.. (2024). Development of a deep Q-learning energy management system for a hybrid electric vehicle. Transportation Engineering. 16. 100241–100241. 11 indexed citations
7.
Piano, Andrea, et al.. (2024). Experimental and numerical investigation of abnormal combustion phenomena in high-performance hydrogen direct-injection engine operated in stochiometric conditions. International Journal of Engine Research. 26(7). 1017–1028. 4 indexed citations
8.
Rolando, Luciano, et al.. (2023). Eco-Driving Optimization Based on Variable Grid Dynamic Programming and Vehicle Connectivity in a Real-World Scenario. Energies. 16(10). 4121–4121. 3 indexed citations
9.
Arsie, Ivan, Michele Battistoni, Roberto Cipollone, et al.. (2023). A New Generation of Hydrogen-Fueled Hybrid Propulsion Systems for the Urban Mobility of the Future. Energies. 17(1). 34–34. 15 indexed citations
10.
Rolando, Luciano, et al.. (2023). Eco-Driving Optimization Based on Dynamic Programming and Vehicle Connectivity in a Real-World Scenario. SSRN Electronic Journal. 1 indexed citations
11.
Rolando, Luciano, et al.. (2023). Eco-Driving Optimization Based on Dynamic Programming and Vehicle Connectivity in a Real-World Scenario. SSRN Electronic Journal. 1 indexed citations
12.
13.
Irimescu, Adrian, et al.. (2022). Lean Burn Flame Kernel Characterization for Different Spark Plug Designs and Orientations in an Optical GDI Engine. Energies. 15(9). 3393–3393. 3 indexed citations
14.
Millo, Federico, et al.. (2022). Development of a neural network-based energy management system for a plug-in hybrid electric vehicle. Transportation Engineering. 11. 100156–100156. 41 indexed citations
15.
Millo, Federico, et al.. (2021). Energy Management System Optimization Based on V2X Connectivity. 2 indexed citations
16.
Millo, Federico, et al.. (2020). Methodological Approach for 1D Simulation of Port Water Injection for Knock Mitigation in a Turbocharged DISI Engine. Energies. 13(17). 4297–4297. 13 indexed citations
17.
Millo, Federico, et al.. (2016). Design and development of an hybrid light commercial vehicle. Energy. 136. 90–99. 31 indexed citations
18.
Millo, Federico, et al.. (2014). Analysis of Different Energy Management Strategies for Complex Hybrid Electric Vehicles. Computer-Aided Design and Applications. 11(sup1). S1–S10. 14 indexed citations
19.
Millo, Federico, et al.. (2013). Real CO2 emissions benefits and end user’s operating costs of a plug-in Hybrid Electric Vehicle. Applied Energy. 114. 563–571. 103 indexed citations
20.
Bianchi, Domenico, Luciano Rolando, Lorenzo Serrao, et al.. (2011). Layered control strategies for hybrid electric vehicles based on optimal control. International Journal of Electric and Hybrid Vehicles. 3(2). 191–191. 44 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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