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Swirling flows are very dominant in applied technical problems, especially in IC engines, and their prediction requires rather sophisticated modeling. An adaptive low-pass filtering procedure for the modeled turbulent length and time scales is derived and applied to Menter' original k - ω SST turbulence model. The modeled length and time scales are compared to what can potentially be resolved by the computational grid and time step. If the modeled scales are larger than the resolvable scales, the resolvable scales will replace the modeled scales in the formulation of the eddy viscosity; therefore, the filtering technique helps the turbulence model to adapt in accordance with the mesh resolution and the scales to capture.

In the next years, the upcoming emission legislations are expected to introduce further restrictions on the admittable level of pollutants from vehicles measured on homologation cycles and real drive tests. In this context, the strict control of pollutant emissions at the cold start will become a crucial point to comply with the new regulation standards. This will necessarily require the implementation of novel strategies to speed-up the light-off of the reactions occurring in the after-treatment system, since the cold start conditions are the most critical one for cumulative emissions. Among the different possible technological solutions, this paper focuses on the evaluation of the potential of a burner system, which is activated before the engine start. The hypothetical burner exploits the lean combustion of an air-gasoline mixture to generate a high temperature gas stream which is directed to the catalyst section promoting a fast heating of the substrate.

The definition of the energy management strategy for a hybrid electric vehicle is a key element to ensure maximum energy efficiency. The ability to optimally manage the on-board energy sources, i.e., fuel and electricity, greatly affects the final energy consumption of hybrid powertrains. In the case of plug-in series-hybrid architectures, such as Range-Extender Electric Vehicles (REEVs), fuel efficiency optimization alone can result in a stressful operation of the range-extender engine with an excessively high number of start/stops. Nonetheless, reducing the number of start/stops can lead to long periods in which the engine is off, resulting in the after-treatment system temperature to drop and higher emissions to be produced at the next engine start.

The EcoCAR 2: Plugging into the Future team at the Ohio State University is designing a Parallel-Series Plug-in Hybrid Electric Vehicle capable of 50 miles of all-electric range. The vehicle features a 18.9-kWh lithium-ion battery pack with range extending operation in both series and parallel modes made possible by a 1.8-L ethanol (E85) engine and 6-speed automated manual transmission. This vehicle is designed to drastically reduce fuel consumption, with a utility factor weighted fuel economy of 75 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This report details the rigorous design process followed by the Ohio State team during Year 1 of the competition. The design process includes identifying the team customer's needs and wants, selecting an overall vehicle architecture and completing detailed design work on the mechanical, electrical and control systems. This effort was made possible through support from the U.S.

The flow field resulting from injecting a gas jet into a crossflow confined in a narrow square duct has been studied under steady regime using schlieren imaging and laser Doppler velocimetry (LDV). This transparent duct is intended to simulate the intake port of an internal combustion engine fueled by gaseous mixture, and the jet is issued from a round nozzle. The schlieren images show that the relative small size of the duct would confine the development of the transverse jet, and the interaction among jet and sidewalls strongly influences the mixing process between jet and crossflow. The mean velocity and turbulence fields have been studied in detail through LDV measurements, at both center plane and several cross sections. The well-known flow feature formed by a counter rotating vortex pair (CVP) has been observed, which starts to appear at the jet exit section and persists far downstream contributing to enhancing mixing process.

An experimental campaign is presented aiming at the characterization of thermal dissipation of batteries to be used on board of small satellites. A suitably designed device allows to manage automatically the orbital cycling simulation between battery cell charge and discharge. The cell thermal performance is characterized in various combinations of temperature, discharge current and Depth of Discharge. The gathered data are used for providing guidelines in the design of a family of Italian Small Satellites.

The design of a performance hybrid electric vehicle includes a wide range of architecture possibilities. A large part of the design process is identifying reasonable vehicle architectures and vehicle performance capabilities. The Ohio State University EcoCAR 3 team designed a plug-in hybrid electric vehicle (PHEV) post-transmission parallel 2016 Chevrolet Camaro. With the end-goal of reducing the environmental impact of the vehicle, the Ohio State Camaro has been designed with a 44-mile all-electric range. It also features an 18.9 kWh Li-ion energy storage system, a 119 kW 2.0L GDI I4 engine that runs on 85% ethanol (E85) fuel, a 5-speed automated manual transmission, and a 150 kW peak electric machine. This report details the design and modeling process followed by the Ohio State team during Year 1 of the competition. The process included researching the customer needs of the vehicle, determining team design goals, initial modeling, and selecting a vehicle architecture.

The Ohio State University EcoCAR 3 team is designing a plug-in hybrid electric vehicle (PHEV) post-transmission parallel 2016 Chevrolet Camaro. With the end-goal of reducing the environmental impact of the vehicle, the Ohio State Camaro has been designed to have a 44-mile all-electric range. The vehicle is to consist of an 18.9 kWh Li-ion energy storage system, a 119 kW 2.0L GDI I4 engine that runs on 85% ethanol (E85) fuel, a 5-speed automated manual transmission, and a 150 kW peak-power electric machine. This report details the model and controls development process followed by the Ohio State team during Year 1 of the EcoCAR 3 competition. The focus of the paper will be on overall development of a vehicle model, initial simulation results, and supervisory controls development. Finally, initial energy consumption results from the model and future improvements will be discussed.

Future aircraft will demand a significant amount of electrical power to drive primary flight control surfaces. The electrical system architecture needed to source these flight critical loads will have to be resilient, autonomous, and fast. Designing and ensuring that a power system architecture can meet the load requirements and provide power to the flight critical buses at all times is fundamental. In this paper, formal methods and linear temporal logic are used to develop a contactor control strategy to meet the given specifications. The resulting strategy is able to manage multiple contactors during different types of generator failures. In order to verify the feasibility of the control strategy, a real-time simulation platform is developed to simulate the electrical power system. The platform has the capability to test an external controller through Hardware in the Loop (HIL).

In recent years, many motorsports have been developing competitions based on electric vehicles. The demanding performance requires the battery pack to have the perfect balance between energy, power, and weight. This research paper presents a systematic methodology for the initial design of the battery pack (size and cell chemistry) by statistically analyzing the characteristics of the mission profile. The power profile for the battery pack of a motorsport vehicle can be estimated by considering the duty cycle of a racing car using the technical and sporting regulations and vehicle parameters. In this paper, many statistical metrics correlated to this power profile have been defined and analyzed (such as the max, mean, and standard deviation of the power profile, the total energy consumed, and the expected heat generation). These metrics have been used to estimate the cell energy and power density requirement and the pack sizing considering the weight constraints.

Physics-based electrochemical models and empirical Equivalent Circuit Models (ECMs) are well-established and widely used modeling techniques to predict the voltage behavior of lithium-ion cells. Electrochemical models are typically very accurate and require relatively little experimental data to calibrate, but present high mathematical and computational complexity. Conversely, ECMs are more computationally efficient and mathematically simpler, making them well-suited for applications in controls, diagnosis, and state estimation of lithium-ion battery packs. However, the calibration process requires extensive testing to calibrate the parameters of the model over a wide range of operating conditions. This paper bridges the gap between these two classes of models by developing a method to analytically define the ECM parameters starting from an already-calibrated Extended Single-Particle Model (ESPM).

This paper benchmarks three different lithium-ion (Li-ion) battery voltage modelling approaches, a physics-based approach using an Extended Single Particle Model (ESPM), an equivalent circuit model, and a recurrent neural network. The ESPM is the selected physics-based approach because it offers similar complexity and computational load to the other two benchmarked models. In the ESPM, the anode and cathode are simplified to single particles, and the partial differential equations are simplified to ordinary differential equations via model order reduction. Hence, the required state variables are reduced, and the simulation speed is improved. The second approach is a third-order equivalent circuit model (ECM), and the third approach uses a model based on a Long Short-Term Memory Recurrent Neural Network (LSTM-RNN)). A Li-ion pouch cell with 47 Ah nominal capacity is used to parameterize all the models.

Batteries are useful in Fuel Cell Hybrid Electric Vehicles (FCHEV) to fulfill transient demands and for regenerative braking. Efficient energy management strategies paired with optimal powertrain design further improves the efficiency. In this paper, a new methodology to simultaneously size the propulsive elements and optimize the power-split strategy of a Range Extended Battery Electric Vehicle (REBEV), using a Polymer Electron Membrane Fuel Cell (PEMFC), is proposed and preliminary studies on the effects of the driving mission profile and the auxiliary power loads on the sizing and optimal performance of the powertrain design are carried out. Dynamic Programming is used to compute the optimal energy management strategy for a given driving mission profile, providing a global optimal solution.

Battery packs used in electrified automotive powertrains support heavy electrical loads resulting in significant heat generation within them. Cooling systems are used to regulate the battery pack temperatures, helping to slow down battery aging. Vehicle-level energy consumption simulations serve as a first step for determining the specifications of a battery cooling system based on the duty cycle and interactions with the rest of the powertrain. This paper presents the development of a battery model that takes into account the energy impact of heating in the battery and demonstrates its use in a vehicle-level energy consumption simulator to set the specifications of a suitable cooling system for a vehicle application. The vehicle application used in this paper is a Class 6 Pickup and Delivery commercial vehicle with a Range-Extended Electric Vehicle (REEV) powertrain configuration.

In recent years the 2-wheelers engines companies have been focused on increasing the overall engine efficiency, that can be achieved amongst other by engine down-speeding, engine down-sizing and by reducing the frictions; however, to maintain or improve vehicle performance, it is necessary to provide a corresponding increase in specific power. In accordance with these trends, the studied approaches and methodologies have been exploited, during the development of the new Piaggio small scooter engine. In this work a multi-objective analysis has been applied to the valve train system design, in order to optimize the engine performance in terms of friction reduction, power curve and timing system response. Along with this optimization methodology, a robust design has been studied to make the peak cranking compression pressure insensitive to the engine starting device working.

The EcoCAR 2: Plugging into the Future team at The Ohio State University is designing a Parallel-Series Plug-in Hybrid Electric Vehicle capable of 44 miles of all-electric range. The vehicle features an 18.9-kWh lithium-ion battery pack with range extending operation in both series and parallel modes. This is made possible by a 1.8-L ethanol (E85) engine and 6-speed automated manual transmission. This vehicle is designed to drastically reduce fuel consumption, with a utility factor weighted fuel economy of 50 miles per gallon gasoline equivalent (mpgge), while meeting Tier II Bin 5 emissions standards. This paper details three years of modeling and simulation development for the OSU EcoCAR 2 vehicle. Included in this paper are the processes for developing simulation platform and model requirements, plant model and soft ECU development, test development and validation, automated regression testing, and controls and calibration optimization.

Vaporizing Foil Actuators (VFA) are based on the phenomenon of rapid vaporization of thin metallic foils and wires, caused by passage of a capacitor bank driven current on the order of 100 kA. The burst of the conductor is accompanied with a high-pressure pulse, which can be used for working metal at high strain rates. This paper focuses on the use of VFA for collision welding of dissimilar metals, in particular, aluminum and steel. Aluminum alloy 6061 sheets of 1 mm thickness were launched to velocities in excess of 650 m/s with input electrical energy of 8 kJ into 0.0762 mm thick, dog-bone shaped aluminum foil actuators. Target sheets made from dual phase steel (DP780) were impacted with the aluminum flyer sheet, and solid state impact welds were created. During mechanical testing, many samples failed outside the weld area, thereby indicating that the weld was stronger than the parent aluminum.

DC-fast charge (DCFC) may be amenable for widespread EV adoption. However, there are potential challenges associated with implementation and operation of the DCFC infrastructures. The integration of energy storage systems can limit the scale of grid installation required for DCFC and enable more efficient grid energy usage. In addition, second-life batteries (SLBs) can find application in DCFC, significantly reducing installation cost when compared to solutions based on new battery packs. However, both system architecture and control strategy require optimization to ensure an optimal use of SLBs, including degradation and thermal aspects. This study proposes an application of automotive SLBs for DCFC stations where high power grid connection is not available or feasible. Several SLBs are connected to the grid by means of low power chargers (e.g. L2 charging station), and a DC/DC converter controls the power to the EV power dispenser.

In this work, the possibility to perform a cold-flow simulation as a way to improve the accuracy of the starting conditions for a combustion simulation is examined. Specifically, a dual-fuel marine engine running on methanol/diesel and natural gas/diesel fueling conditions is investigated. Dual-fuel engines can provide a short-term solution to cope with the more stringent emission legislations in the maritime sector. Both natural gas and methanol appear to be interesting alternative fuels that can be used as main fuel in these dual-fuel engines. Nevertheless, it is observed that combustion problems occur at part load using these alternative fuels. Therefore, different methods to increase the combustion efficiency at part load are investigated. Numerical simulations prove to be very suitable hereto, as they are an efficient way to study the effect of different parameters on the combustion characteristics.

Hybrid-electric gas turbine generators are considered a promising technology for more efficient and sustainable air transportation. The Ohio State University is leading the NASA University Leadership Initiative (ULI) Electric Propulsion: Challenges and Opportunities, focused on the design and demonstration of advanced components and systems to enable high-efficiency hybrid turboelectric powertrains in regional aircraft to be deployed in 2030. Within this large effort, the team is optimizing the design of the battery energy storage system (ESS) and, concurrently, developing a supervisory energy management strategy for the hybrid system to reduce fuel burn while mitigating the impact on the ESS life. In this paper, an energy-based model was developed to predict the performance of a battery-hybrid turboelectric distributed-propulsion (BHTeDP) regional jet.