Degree “summa cum laude” in Mechanical Engineering (University of Salerno, March 2002). Ph.D. (since 2006), currently serves as assistant professor of Energy Conversion Systems at the Department of Industrial Engineering (DIIN) of University of Salerno (UNISA). From September 2003 to November 2004 he was visiting scholar at Center for Automotive Research of the Ohio State University, Columbus (OH, USA). The research activity mainly focuses on conventional and innovative propulsion systems and fuel cells for stationary power generation. ASME and SAE member, authored 78 scientific publications and regularly serves as reviewer for ISI journals and international conferences organized by IFAC, SAE, ASME and IEEE. Coordinates the research project “Provisional models of central office energy consumptions and their integration into the Energreen monitoring platform” with Telecom Italia. Coordinates one research line within the EU-FP7-JTI funded project DCODE; also participates as UNISA researcher to EU-FP7-JTI funded projects GENIUS and DESIGN. He owns the international patent “Kit for transforming a conventional motor vehicle into a solar hybrid vehicle, and relevant motorvehicle obtained by the kit”. Received the Best Paper Award from the Powertrain division at the AVEC '04 Symposium on Advance Vehicle Control Technologies. In 2010, he was awarded the "Energy and Mobility Prize" by the technical committee of the conference "H2Roma 2010". Teaching assistant and lecturer in the scientific area of Energy Conversion Systems at DIIN-UNISA, has been advisor or co-advisor of several bachelor and master theses. He is currently teaching staff member of the Ph.D. in Mechanical Engineering at DIIN-UNISA. He has lectured on “Model-Based Diagnosis for Solid Oxide Fuel Cells” in the "First Joint European Summer School on Hydrogen and Fuel Cell Technology" (Viterbo – Italy, August 2011).
Abstract: Reliability and lifetime are common issues for the development and commercialization of fuel cells technologies'. As a consequence, their improvement is a major challenge and the last decade has experienced a growing interest in activities that aims at understanding the degradation mechanisms and at developing fuel cell systems diagnosis tools.
Fault Tree Analysis (FTA) is one of the deductive tools that allow âlinkingâ an undesired state to a combination of lower-level events via a âtopâdownâ approach which is mainly used in safety and reliability engineering.
The objective of this paper is to give an overview of the use and the contribution of FTA to both SOFC and PEFC diagnosis.
Abstract: The exploitation of an SOFC-system model to define and test control and energy management strategies is presented. Such a work is motivated by the increasing interest paid to SOFC technology by industries and governments due to its highly appealing potentialities in terms of energy savings, fuel flexibility, cogeneration, low-pollution and low-noise operation.
The core part of the model is the SOFC stack, surrounded by a number of auxiliary devices, i.e. air compressor, regulating pressure valves, heat exchangers, pre-reformer and post-burner. Due to the slow thermal dynamics of SOFCs, a set of three lumped-capacity models describes the dynamic response of fuel cell and heat exchangers to any operation change.
The dynamic model was used to develop low-level control strategies aimed at guaranteeing targeted performance while keeping stack temperature derivative within safe limits to reduce stack degradation due to thermal stresses. Control strategies for both cold-start and warmed-up operations were implemented by combining feedforward and feedback approaches. Particularly, the main cold-start control action relies on the precise regulation of methane flow towards anode and post-burner via by-pass valves; this strategy is combined with a cathode air-flow adjustment to have a tight control of both stack temperature gradient and warm-up time. Results are presented to show the potentialities of the proposed model-based approach to: (i) serve as a support to control strategies development and (ii) solve the trade-off between fast SOFC cold-start and avoidance of thermal-stress caused damages.
Abstract: Since the model plays an important role in diagnosing solid oxide fuel cell (SOFC) system, this paper proposes a review of existing SOFC models for model-based diagnosis of SOFC stack and system. Three categories of modelling based on the white-, the black- and the grey-box approaches are introduced. The white-box model includes two types, i.e. physical model and equivalent circuit model based on EIS technique. The black-box model is based on artificial intelligence and its realisation relies mainly on experimental data. The grey-box model is more flexible: it is a physical representation but with some parts being modelled empirically. Validation of models is discussed and a hierarchical modelling approach involving all of three modelling methods is briefly mentioned, which gives an overview of the design for implementing a generic diagnostic tool on SOFC system.
Abstract: In the paper, the performances of a rule-based (RB) control strategy for series hybrid vehicles are assessed via comparison with a batch Genetic Algorithm-based (GA) optimization. The suitability of GA optimization as reference benchmark for series architecture is demonstrated through comparison with Dynamic Programming technique. Specifically in this paper, a hybrid solar vehicle (HSV) was considered, thus requiring to define the heuristic rules as function of both average traction power and current solar irradiation. The comparison with the reference GA benchmark confirms the suitability of the proposed RB strategy for HSV on-board energy management. Extensive simulations were performed to test the influence of driving cycle features, power-prediction time-horizon and solar irradiation on HSV fuel economy. Such simulation analysis, beyond providing useful indications about correct implementation of the RB strategy on both hybrid and solar hybrid cars, also demonstrates the potentialities offered by HSV powertrains in both urban and highway driving conditions.
Abstract: This paper deals with the development of a prototype of Hybrid Solar Vehicle (HSV) with series structure. This activity has been also conducted in the framework of the European
Union funded Leonardo project âEnergy Conversion Systems and Their Environmental Impactâ, a project with research and educational objectives. A study on supervisory control for hybrid solar vehicles and some preliminary tests performed on the road are presented. Previous results obtained by a model for HSV optimal design have confirmed the relevant benefits of such vehicles with respect to conventional cars in case of intermittent use in urban driving (city-car), and that economical feasibility could be achieved in a near future. Due to the series-powertrain adopted for the HSV prototype, an intermittent use of the ICE (Internal Combustion Engine) powering the electric generator is possible, thus avoiding part-load low-efficient engine operations. The best ICE power trajectory is determined via genetic algorithm optimization accounting for fuel mileage as well as battery state of charge, also considering solar contribution during parking mode. The experimental set up used for data logging, real-time monitoring and control of the prototype is also presented, and the results obtained with different road tests discussed.
Abstract: The paper focuses on the simulation, analysis and control of the energy flow in a parallel hybrid electric vehicle (HEV). HEVs operation is concerned with the on board conversion of chemical, electric and mechanic energy and its optimal control is essential in order to increase the global system efficiency.
A dynamic model is used to describe the driver-vehicle interaction for a generic transient and to simulate the vehicle driveline, the internal combustion engine (ICE) and the electric motor/generator (EM). An estimate of future vehicle load is performed with a neural network to optimize the supervisory control strategy during the estimated future time window.
A description of the whole model is presented and the simulation results carried out for a real driving cycle are reported.
Abstract: A study on optimal energy management on a Hybrid Solar Vehicle (HSV) with series structure is presented. Previous results obtained by optimal design analysis for HSV confirmed the relevant benefits of such vehicles with respect to conventional cars in case of intermittent use in urban driving (city-car), and that economical feasibility could be achieved in a near future. In order to develop a supervisory control for a HSV prototype under development at University of Salerno, a study on the performance achievable by an intermittent use of the ICE powering the electric generator is presented. In particular, the effects of engine thermal transients on fuel consumption and HC emissions are studied and discussed. The optimal ICE power trajectory is found by solving a non-linear constrained optimization that suitably accounts for fuel mileage and state of charge, also considering solar contribution during parking mode.
Abstract: Hybrid Solar Vehicles (HSV), derived by integration of Hybrid Electric Vehicles with Photo-Voltaic sources, may represent a valuable solution to face both energy saving and environmental issues, particularly in urban driving. Previous studies have also shown that economic feasibility could be achieved in a near future. After a presentation of the perspectives and the problems related to the use of such vehicles, the paper focuses on their management strategies, evidencing some significant differences with respect to the case of Hybrid Electric Vehicles. In order to develop a supervisory control for an HSV prototype under development at University of Salerno, a study on the performance achievable by an intermittent use of the ICE powering the electric generator is presented. The results obtained by the application of Genetic Algorithms (GA) to the optimal energy management of an HSV with series structure are discussed. The optimal powering strategy accounts for fuel mileage and state of charge, also considering solar contribution during parking mode and the effects of engine thermal transients on fuel consumption and HC emissions. The effects of power-train, vehicle and external variables on optimal strategies are also studied and discussed.
Abstract: The paper deals with the modeling, control and testing of a Hybrid Solar Vehicle (HSV) prototype. Vehicle set-up and instrumentation are accomplished at University of Salerno (UNISA), within an EU funded Leonardo project, starting from an existing electric vehicle. Suited experimental activities were performed to identify and validate a comprehensive model of the propulsion system resulting from the integration of a series hybrid powertrain with a photovoltaic (PV) array.
Then, a simulation analysis was performed to address on-board energy management issues as well as assess prototype performance over a selected driving cycle. Simulation results show that appropriate components sizing and supervisory control strategies concur in improving fuel economy significantly, up to 30 kilometers per liter of Diesel fuel.
Abstract: A comprehensive model for the study and the optimal design of a solar hybrid vehicle with series architecture has been presented. The model describes energy flows between horizontal and/or vertical solar panels, internal combustion engine, electric generator, electric motor and batteries, considering vehicle longitudinal dynamics and the effect of control strategies. Vehicle weight is predicted, starting from a database of commercial vehicles, considering the effects of power-train sizing, vehicle dimensions and possible use of aluminum. The effects of vehicle dimensions on aerodynamic losses and maximum panel area also can be accounted for. The model predicts the additional costs with respect to
conventional vehicles, and the pay-back.
It has been shown that significant savings in fuel consumption and emissions can be obtained with an intermittent use of the vehicle at limited average power, compatible with typical use in urban conditions during working days. This result has been obtained with commercial PV panels and with realistic data and
assumptions on the achievable net solar energy for propulsion. The future adoption of last generation photovoltaic panels, with nominal efficiencies approaching 35%, may result in an almost complete solar autonomy of this kind of vehicle for such uses. By adopting up to date technology for electric motor and generator, batteries and chassis, power to weight ratio comparable with the ones of commercial cars can be achieved, thus assuring acceptable vehicle performance.
Future developments may concern a systematic study of optimal configuration for various driving cycles and latitudes, also considering seasonal variations of the
solar energy, more accurate study of control strategies, including possible application of on-board optimization coupled with provisional methods for car load and solar energy based on Recurrent Neural Network. More detailed models for component weights and costs, including non-linear effects, also can be necessary, as well as further studies on the interactions between vehicle and propulsion system.
The results obtained by optimization analysis over a ECE/EUDC cycle have shown that the hybrid solar vehicles, although still far from economic feasibility, could reach acceptable payback values if large but not unrealistic variations in costs, prices and panel efficiency will occur: considering recent trends in renewable energy field and actual geo-political scenarios, it is reasonable to expect further reductions in costs for PV panels, batteries and advanced electric motors and generators, while relevant increases in fuel cost could not be excluded. Moreover, the recent and somewhat
surprising commercial success of some electrical hybrid cars indicates that there are grounds for hope that a significant number of users is already willing to spend
some more money to contribute to save the planet from pollution, climate changes and resource depletion. In order to validate the model, a prototype of Hybrid Solar Vehicle with series structure is being developed at DIMEC, within a project funded by EU.
Abstract: A model for the optimal design of a solar hybrid vehicle is presented. The model can describe the effects of solar panels area and position, vehicle dimensions and propulsion system components on vehicle performance, weight, fuel savings and costs for different sites. It is shown that significant fuel savings can be achieved for intermittent use with limited average power, and that economic feasibility could be achieved in next future considering expected trends in costs and prices.
Abstract: The present thesis focuses on the use of hierarchical modeling to simulate and control planar Solid Oxide Fuel Cells (SOFCs). Such an approach is motivated by the increasing research efforts devoted to improving SOFC materials and performances. The final aim is the enhancement of commercialization in both power generation and automotive fields. Particularly, the availability of suited modeling tools, meeting the conflicting needs of accuracy, affordable computational time and reduced experimental efforts, might improve the development of SOFC systems. This would significantly contribute to performing accurate balance of plant analyses, as well as defining optimal control strategies for SOFC auxiliary power units (APUs).
To this end, at the high level of the hierarchical structure is a onedimensional, steady state model, developed referring to the state of the art in the field of SOFC modeling. Validation is conducted referring to both experimental tests and standard references derived from literature. Due to its high physical
content, such model is suitable to perform âvirtual experimentsâ for a given SOFC unit, thus enlarging the data-set available for the definition of low-level non-physical models (i.e. black-box models).
Then, at the low-level of the structure is the control-oriented model, developed basing on the information provided by the higher-level model and assuming the SOFC behaves as a first-order system. The thermal dynamics is assumed much slower, thus dominant, with respect to the dynamics of electrochemistry and mass transfer. Therefore, SOFC dynamics is modeled
applying the conservation of energy principle (heat balance) to a lumped control volume, which includes air and fuel channels, as well as interconnect and solid
trilayer (i.e. electrolyte and electrodes). A state-space representation of the model also is provided, having the outlet temperature and the voltage as state variable and output variable, respectively.
Due to the lack of experimental data in the open literature, model validation was conducted by comparing the fuel cell response to load (i.e. current density) variations with data generated by means of a physical comprehensive model, previously published by Achenbach (1995).
Extensive simulation of the fuel cell dynamic behavior was performed to analyze in detail the SOFC dynamics with respect to changes in load and excess air. Furthermore, an application example is given, dealing with the development of a PI controller to limit temperature rise across the cell within a safe range.
Potential areas of application of the approach proposed are highlighted throughout the thesis. In several fields the hierarchical approach can be used as a reference tool for optimal design and sizing, as well as for the energy management of hybridized (i.e. supported by batteries or supercap) SOFC-based
power units.
Abstract: A model-based Fault Detection and Isolation (FDI) scheme for Solid Oxide Fuel Cell (SOFC)-based systems is proposed. FDI schemes are based on the redundancy concept, whose main idea is to increase and/or complete the information available about the actual system status. The core of the diagnostic system relies on the inference analysis to detect and localize the fault either at stack or at system level. Specifically in this work, the Parity Equations technique is adopted, which is particularly suitable to develop FDI tools in presence of MIMO (Multi-Input-Multi-Output) processes, as SOFC functioning is. According to this technique for each k-th variable, associated to an FDI scheme, a residual estimation has to be performed as function of actual measurement and model prediction. From the above residuals useful information about faults can be derived by appropriately defining fault isolation logic as function of residuals themselves. The adopted model, previously developed by the authors, simulates the dynamical behaviour of a planar co-flow SOFC stack coupled with its auxiliary devices, namely air compressor/blower, regulating pressure valves, heat exchangers, pre-reformer and post-burner. Due to its gray-box nature, such model allows predicting the dependence between stack performance and both input and exogenous variables with satisfactory accuracy and computational burden. Therefore, it is suitable for implementation into a real-time parity equation FDI scheme. Extensive simulations will be performed to test the validity of the approach proposed for SOFC systems destined to a wide application area.
Abstract: This patent focuses on the development of equipments, along with associated techniques and methodologies, aimed at converting conventional car into hybrid solar vehicles (Mild-Solar-Hybrid). Mild-hybridization will be performed by installing in-wheel electric motors on the rear wheels (in case of front wheel drive) and by the integration of photovoltaic panels on the roof. The original architecture will be upgraded with the storage device (battery pack) and an additional control unit to be faced with the engine management system by the OBD port, and not interfering with the original engine control unit. Details on the web page http://www.hysolarkit.com.
