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The recent advance in the development of various hybrid vehicle technologies comes along with the need of establishing optimal energy management strategies, in order to minimize both fuel economy and pollutant emissions, while taking into account an increasing number of state and control variables, depending on the adopted hybrid architecture. One of the objectives of this research was to establish benchmarking performance, in terms of fuel economy, for real time on-board management strategies, such as ECMS (Equivalent Consumption Minimization Strategy), whose structure has been implemented in a SIMULINK model for different hybrid vehicle concepts.

This paper presents an optimization algorithm, based on discrete dynamic programming, that aims to find the optimal control inputs both for energy and thermal management control strategies of a Plug-in Hybrid Electric Vehicle, in order to minimize the energy consumption over a given driving mission. The chosen vehicle has a complex P1-P4 architecture, with two electrical machines on the front axle and an additional one directly coupled with the engine, on the rear axle. In the first section, the algorithm structure is presented, including the cost-function definition, the disturbances, the state variables and the control variables chosen for the optimal control problem formulation. The second section reports the simplified quasi-static analytical model of the powertrain, which has been used for backward optimization. For this purpose, only the vehicle longitudinal dynamics have been considered.

As a result of CAFE (corporate average fuel economy) requirements, the trend in passenger car engine design is to smaller displacement engines of higher specific output which provide reductions in vehicle driving cycle fuel consumption without an accompanying decrease in maximum power output. Design features such as four valves per cylinder and compact combustion chambers give these engines significantly different combustion characteristics than traditional pushrod OHV (overhead valve) engines. In general, their combustion chambers are fast burning, enabling the use of higher compression ratios without knock on unleaded gasoline. Since fuel consumption decreases with increasing compression ratio, and since natural gas has a substantially higher octane rating than the best unleaded gasoline, it would appear to be desirable to operate with even higher compression ratios in a dedicated natural gas engine.

In order to reduce both polluting emissions and fuel costs, many countries allow mixing ethanol to gasoline either in fixed percentages or in variable percentages. The resulting fuel is labeled E10 or E22, where the number specifies the ethanol percentage. This operation significantly changes way the stoichiometric value, which is the air-to-fuel mass ratio theoretically needed to completely burn the mixture. Ethanol concentration must be correctly estimated by the Engine Management System to optimally control exhaust emissions, fuel economy and engine performance. In fact, correct fuel quality recognition allows estimating the actual stoichiometric value, thus allowing the catalyst system to operate at maximum efficiency in any engine working point. Moreover, also other essential engine control functions should be adapted in real time by taking into account the quality of the fuel that is being used.

Charge dilution is commonly used to reduce emissions of nitrogen oxides (NOx) from internal combustion engine exhaust gas. The question of whether to use air or exhaust gas recirculation (EGR) as a charge diluent for the natural gas-fuelled test engine is addressed first. The decision to use EGR is based on the potentially lower NOx and unburned hydrocarbon emissions that could be achieved if a three-way catalyst were applied to the engine. The effect of EGR on the spark advance for maximum brake torque (MBT), NOx, and unburned hydrocarbon emissions is then examined in detail. The effect on fuel efficiency is discussed briefly.

Thermoplastic Vulcanizate (TPV) is a special class of Thermoplastic Elastomers (TPEs) made of a rubber/plastic polymer mixture in which the rubber phase is highly vulcanized. It is prepared by melt mixing a thermoplastic with an elastomer and by in-situ crosslinking of the rubber phase. Currently, TPV is replacing EPDM rubber dramatically because of the impressive advantages for automotive sealing applications. Some of the advantages of TPV compared to that of EPDM rubber are good gloss, recyclability, improved colorability, shorter cycle time and design flexibility. The development of TPV foaming technology is to fulfill the requirement of achieving lower cost, lighter weight and better fuel economy. Foaming of TPV has not been investigated extensively.

Today, the contribution of the transportation sector on greenhouse gases is evident. The fast consumption of fossil fuels and its impact on the environment have given a strong impetus to the development of vehicles with better fuel economy. Hybrid electric vehicles fit into this context with different targets, starting from the reduction of emissions and fuel consumption, but also for performance and comfort enhancement. Lamborghini has recently invested in the development of a hybrid super sport car, due to performance and comfort reasons. Aventador series gearbox is an Independent Shift Rod gearbox with a single clutch and during gear shifts, as all the single clutch gearbox do, it generates a torque gap. To avoid the additional weight of a Dual Clutch Transmission, a 48V Electric Motor has been connected to the wheels, in a P3 configuration, to fill the torque gap, and to habilitate regenerative braking and electric boost functions.

Widely used in automotive industry, lightweight metallic structures are a key contributor to fuel efficiency and reduced emissions of vehicles. Lightweight structures are traditionally designed through employing the material distribution techniques sequentially. This approach often leads to non-optimal designs due to constricting the design space in each step of the design procedure. The current study presents a novel Multidisciplinary Design Optimization (MDO) framework developed to address this issue. Topology, topography, and gauge optimization techniques are employed in the development of design modules and Particle Swarm Optimization (PSO) algorithm is linked to the MDO framework to ensure efficient searching in large design spaces often encountered in automotive applications. The developed framework is then further tailored to the design of an automotive Cross-Car Beam (CCB) assembly.

The increasing use of natural gas as a vehicle fuel has generated considerable research activity to characterize the performance and emissions of engines utilizing this fuel. However, virtually all of the results reported have been for pushrod OHV spark ignition engines or SI conversions of heavy-duty diesel engines. Because of the pressure to improve fuel economy imposed by CAFE requirements, passenger cars are increasingly tending toward high specific output, small displacement engines. These engines employ such features as four valves per cylinder and centrally located spark plugs which give them a different dependence on operating variables than traditional pushrod OHV engines. In this study, experiments were carried out with a two-liter four-cylinder Nissan SR20DE engine representative of modern design practice. The engine was operated on gasoline and natural gas at six different loads and three different speeds. Some tests were also done with isooctane.

This paper shows the influence of different battery charge management strategies on the fuel economy of a hybrid parallel axle-split vehicle in a real driving scenario, for a vehicle control system that has the additional possibility to split the torque between front and rear axles. The first section regards the validation of a self-developed Model in the Loop (MiL) environment of a P1-P4 plug-in hybrid electric car, using experimental data of a New European Driving Cycle test. In its original version, which is implemented on-board the vehicle, the energy management supervisor implements a heuristic, or rule-based, Energy Management Strategy (EMS). During this project, a different EMS has been developed, consisting of a sub-optimal control scheme called Equivalent Consumption Minimization Strategy (ECMS), explained in detail in the second section.

New gasoline engine design is highly influenced by CO2 and emission limits defined by legislations, the demand for real conditions fuel economy, higher torque, higher specific power and lower cost. To reach the requirements coming from the end-users and legislations, especially for SI engines, several technologies are available, such as downsizing, including turbocharging in combination with direct injection. These technologies allow to solve the main issues of gasoline engines in terms of efficiency and performance which are knocking, part-load losses, and thermal stress at high power conditions. Moreover, other possibilities are under evaluation to allow further steps of enhancement for the even more challenging requirements. However, the benefits and costs given by the mix of these technologies must be accurately evaluated by means of objective tools and procedures in order to choose among the best alternatives.

While the Diesel Particulate Filter (DPF) is actually a quasi-standard equipment in the European Diesel passenger cars market, an interesting solution to fulfill NOx emission limits for the next EU 6 legislation is the application of a Selective Catalytic Reduction (SCR) system on the exhaust line, to drastically reduce NOx emissions. In this context, one of the main issues is the performance of the SCR system during cold start and warm up phases of the engine. The exhaust temperature is too low to allow thermal activation of the reactor and, consequently, to promote high conversion efficiency and significant NOx concentration reduction. This is increasingly evident the smaller the engine displacement, because of its lower exhaust system temperature (reduced gross power while producing the same net power, i.e., higher efficiency).