138 research outputs found
Influence of pentanol and dimethyl ether blending with diesel on the combustion performance and emission characteristics in a compression ignition engine under low temperature combustion mode
Get PDFDimethyl ether (DME) and n-pentanol can be derived from non-food based biomass feedstock without unsettling food supplies and thus attract increasing attention as promising alternative fuels, yet some of their unique fuel properties different from diesel may significantly affect engine operation and thus limit their direct usage in diesel engines. In this study, the influence of n-pentanol, DME and diesel blends on the combustion performance and emission characteristics of a diesel engine under low-temperature combustion (LTC) mode was evaluated at various engine loads (0.2–0.8 MPa BMEP) and two Exhaust Gas Recirculation (EGR) levels (15% and 30%). Three test blends were prepared by adding different proportions of DME and n-pentanol in baseline diesel and termed as D85DM15, D65P35, and D60DM20P20 respectively. The results showed that particulate matter (PM) mass and size-resolved PM number concentration were lower for D85DM15 and D65P35 and the least for D60DM20P20 compared with neat diesel. D60DM20P20 turned out to generate the lowest NOx emissions among the test blends at high engine load, and it further reduced by approximately 56% and 32% at low and medium loads respectively. It was found that the combination of medium EGR (15%) level and D60DM20P20 blend could generate the lowest NOx and PM emissions among the tested oxygenated blends with a slight decrease in engine performance. THC and CO emissions were higher for oxygenated blends than baseline diesel and the addition of EGR further exacerbated these gaseous emissions. This study demonstrated a great potential of n-pentanol, DME and diesel (D60DM20P20) blend in compression ignition engines with optimum combustion and emission characteristics under low temperature combustion mode, yet long term durability and commercial viability have not been considered.Postprint (author's final draft
Nonlinear model predictive control for thermal management in plug-in hybrid electric vehicles
Get PDF© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.A nonlinear model predictive control (NMPC) for the thermal management (TM) of Plug-in Hybrid Electric Vehicles (PHEVs) is presented. TM in PHEVs is crucial to ensure good components performance and durability in all possible climate scenarios. A drawback of accurate TM solutions is the higher electrical consumption due to the increasing number of low voltage (LV) actuators used in the cooling circuits. Hence, more complex control strategies are needed for minimizing components thermal stress and at the same time electrical consumption. In this context, NMPC arises as a powerful method for achieving multiple objectives in Multiple input- Multiple output systems. This paper proposes an NMPC for the TM of the High Voltage (HV) battery and the power electronics (PE) cooling circuit in a PHEV. It distinguishes itself from the previously NMPC reported methods in the automotive sector by the complexity of its controlled plant which is highly nonlinear and controlled by numerous variables. The implemented model of the plant, which is based on experimental data and multi- domain physical equations, has been validated using six different driving cycles logged in a real vehicle, obtaining a maximum error, in comparison with the real temperatures, of 2C. For one of the six cycles, an NMPC software-in-the loop (SIL) is presented, where the models inside the controller and for the controlled plant are the same. This simulation is compared to the finite-state machine-based strategy performed in the real vehicle. The results show that NMPC keeps the battery at healthier temperatures and in addition reduces the cooling electrical consumption by more than 5%. In terms of the objective function, an accumulated and weighted sum of the two goals, this improvement amounts 30%. Finally, the online SIL presented in this paper, suggests that the used optimizer is fast enough for a future implementation in the vehicle.Accepted versio
Experimental Investigation of the Cavitation Effects on the Heat Generation in a Closed Loop Pumping System
Get PDFA series of tests were carried out in the cavitation tunnel of the Laboratory for Water and Turbine Machines of the University of Ljubljana in order to investigate the effects of cavitation in the water heating process of closed loop pumping systems. For that, the water temperature was measured at the low pressure reservoir during runs of about 10 minutes. As expected, a constant temperature increase was observed which was proportional to the pump’s rotation speed. Then, the results obtained while keeping the same pump operating point and flow conditions with and without cavitation in the Venturi test section were compared. Surprisingly, it was found that the temperature increase rate was slightly higher when cavitation is present in the system. Moreover, the heat power was always higher than the hydraulic one for all the tests up to a certain cavitation level. However, this trend was inversed for higher cavitation numbers and lower hydraulic powers. Both results seem to prove that there is a clear influence of cavitation in heat generation process. Therefore, a new test rig will be built in Barcelona by the Spanish company Condorchem Envitech, S. L. with the help of Universitat Politècnica de Catalunya BarcelonaTech to continue the current researchPostprint (published version
Analysis of the sensible and total ventilation energy recovery potential in different climate conditions. Application to the Spanish case
Get PDFEnergy recovery elements play a major role in the efficiency and sustainability of building ventilation systems. The use of a sensible or total energy recovery ventilator is a key decision for ventilation systems designers. However, there is a lack of technical tools and developments to support this decision. The authors present a procedure to develop a simple decision tool for designers based on hourly values of the outdoor weather conditions and that can be applied to any kind of building. Results of the procedure are presented in simple-to-use isoline maps and tables. In order to assess credibility of the model used in the procedure, data published in the literature have been used as a reference, showing good accordance. As an example, the procedure has been applied to the Spanish area considering 48 different locations. Results have been presented and discussed. Their analysis shows as the market-accepted recommendation of using energy recovery ventilators in locations with high relative humidity during the summer should be reconsidered.Peer ReviewedPostprint (author's final draft
Thermal Management in Plug-In Hybrid Electric Vehicles: a Real-Time Nonlinear Model Predictive Control Implementation
Get PDF© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.A real-time nonlinear model predictive control (NMPC) for the thermal management (TM) of the electrical components cooling circuit in a Plug-In Hybrid Electric Vehicle (PHEV) is presented. The electrical components are highly temperature-sensitive and therefore working out of the ranges recommended by the manufacturer can lead to their premature aging or even failure. Consequently, the goals for an accurate and efficient TM are two: to keep the main component, the Li-ion battery, within optimal working temperatures, and to consume the minimum possible electrical energy through the cooling circuit actuators. This multi-objective requirement is formulated as a finite-horizon optimal control problem (OCP) that includes a multi-objective cost function, several constraints and a prediction model especially suitable for optimization. The associated NMPC is performed on real-time by the optimization package MUSCOD-II and is validated in three different repeatable test-drives driven with a PHEV. Starting from identical conditions, each cycle is driven once being the cooling circuit controlled with NMPC and once with a conventional approach based on a finite-state machine. Compared to the conventional strategy, the NMPC proposed here results in a more accurate and healthier temperature performance, and at the same time, leads to reductions in the electrical consumption up to 8%.Postprint (author's final draft
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