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The continuous increase of pollutants and fine particulates is mainly caused by cars circulating worldwide. Therefore, it is necessary to replace internal combustion engines with the cleanest electric motors. The short term solution is represented by Hybrid Electric Vehicles (HEVs) due to its environmental and efficiency characteristics. In the present paper a dynamic feed-forward mathematical model for a hybrid vehicle performance analysis is proposed. Torque and power, pollutant emission, fuel consumption, battery pack state of charge, as well as speed and acceleration have been evaluated by means of simulation of United State and Japanese standard driving cycles. In order to carry out simulations on a real hybrid configuration, the model has been based on the powertrain installed on the Toyota Prius (Toyota Hybrid System - THS). A mathematical sub-model of each vehicle component has been implemented to simulate the real vehicle behavior in all possible running conditions.

One of the most important challenges in the design of a hybrid vehicle is the choice of the best control strategy for energy management. This work analyzes and discusses five different rules-based strategies. The authors' main targets were to understand how each strategy acts on the power split and how the operation points of both the Internal Combustion Engine and Electric Motor vary on efficiency maps. So, a critical review was produced of the strengths and weakness of different strategies found in scientific literature and out of it grew two new control plans.

The automotive industry needs a substantial revolution. It is necessary to replace conventional vehicles, equipped with highly polluting and very inefficient Internal Combustion Engines (if compared with the high efficiency of Electrical Motors), with clean, efficient electric vehicles (Zero Emission Vehicles). The electrical vehicles do not produce pollution and are characterized by high efficiency values (about 0.8) respect to ICE (about 0.27). In the transition from vehicles equipped with only ICE, to purely electrical vehicles, a fundamental step is represented by HEVs (Hybrid Electric Vehicles). This paper shows the development, the validation and the use of a numerical code for hybrid vehicle simulation. A quasi-static “backward” simulation code was developed and implemented for an ISA (Integrated Starter Alternator) configuration vehicle. The Willans line approach was implemented to create the HEV model.

In order to estimate the combustion process inside an Internal Combustion Engine it is fundamental to evaluate the molar fractions of the gases which constitute the burned mixture. A non linear set of equations must be solved to evaluate the mixture composition. The present paper deals with the study about the thermodynamics of combustion, using a new approach to solve the set of non linear equations by the Newton-Raphson method. In order to solve the non-linear set of equations describing the combustion process, a new first attempt solution for the Newton-Raphson numerical method has been evaluated and implemented. Starting from the combustion model presented in scientific literature by Benson, a new first attempt solution has been evaluated in order to have the numerical convergence of the model for a wide set of fuels and for a wide range of thermodynamic conditions. The combustion model is able to evaluate the molar fractions of the products of combustion.

In the current work, a heat release model, based on the First Law of the Thermodynamics, has been implemented using a genetic approach. Using this approach, the evaluation procedure of the calibration's constants becomes automatic and accurate. The more accurate is the evaluation of the calibration's constants, the more precise will be the calculation of the heat exchange between charge and cylinder walls, the evaluation of the gross heat release inside internal combustion engines, the evaluation of the rate of heat release, the mass fraction burned, as well as the combustion efficiency.

A new set of mathematical functions, that is able to describe gases' thermodynamic properties, has been developed. These functions have the form of a fifth order logarithmic polynomial (VoLP). They could be utilized for combustion processes, with “frozen composition” and “composition in equilibrium” evaluation. The VoLPs present several advantages: they are able to cover a wide range of temperatures with only a single mathematical function; they have an elevate accuracy and they present the possibility to extrapolate experimental data beyond the experimental temperature range. The VoLP coefficients have been evaluated through the least squares fit on the basis of experimental measurements (taken from scientific literature). The set of VoLPs gives the possibility to study the combustion phenomena and allows to describe specific heat at constant pressure, enthalpy, entropy and equilibrium constants for gases dissociation.

In this paper, the authors have investigated a new neural network application for the determination of thermodynamic properties for various gases for internal combustion engines applications. The Neural Network has been trained using experimental data available in literature (specific heat at constant pressure, enthalpy, entropy and equilibrium constants for thirteen gases of practical interest inside ICE applications). In the present study a two-layer Elman network feedback from the first-layer output to the first layer input as well as “tansig” neurons in its hidden and out layers has been implemented. After the training, neural network has been tested through a comparison with the NASA equations and JANAF equations, showing the capability to cover with a single model wide range of temperature with an accuracy equal or greater than others mathematical function. Thermodynamic properties of gases have been calculated depending on temperature.

It is well-known that the reliability of calculations in ICEs depends on the accuracy of gases thermodynamic properties model. Several relationships modeling the composition of unburned and burned mixtures have been developed for computer use. In this paper, the authors have determined new relationships suitable also for ICEs applications, in order to calculate the enthalpy for various gases, and mixtures. These relationships can be used in the models describing the processes of intake, compression, combustion and expansion, to simulate a complete engine cycle and to foresee engine performance. These relationships have the functional form of a “V order Logarithmic Polynomial”, and they can be used in temperature range of practical interest.