Plug In Hybrid Electric Vehicle Modeling Prototype Realization, And Inverter Losses Reduction Analysisdocx

=== Plug-In Hybrid electric vehicle – modeling prototype realization, and inverter losses reduction analysis ===

598 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 57, NO. 2, FEBRUARY 2010

Plug-In Hybrid Electric Vehicle: Modeling, Prototype Realization, and Inverter Losses Reduction Analysis

Ferdinando Luigi Mapelli, Davide Tarsitano, and Marco Mauri, Member, IEEE

Abstract—Nowadays, the greatest part of the effort to reduce pollution emissions is directed toward the hybridization of auto- motive drive trains. In particular, the design of hybrid vehicles requires a complete system analysis, including the optimization of the electric and electronic devices installed on the vehicle and the design of all the mechanical connections between the different power sources to reach the required performances. The aim of this paper is to describe the design and prototype realization of a plug-in hybrid electrical vehicle (PHEV). Specifically, an energetic model was developed in order to analyze and optimize the power flux between the different parts. This model was experimentally validated using a prototype PHEV. In addition, in order to improve the driving range in an all-electric model (all-electric range), a detailed analysis of the inverter control was performed, because this component is one of the key components of the power train. In order to reduce inverter losses and dimensions, several control methods can be adopted. In this paper, a direct self-control strat- egy for reducing the inverter losses is presented and validated.

Index Terms—Direct self-control (DSC), energetic model, in- verter efficiency, inverter losses, modeling and simulation, plug-in hybrid electric vehicle (PHEV).

INTRODUCTION

N THE LAST few years, the problem of air pollution has become very important. One of the principal causes of this phenomenon is the exponential growth in the number of

vehicles with an internal combustion engine (ICE).

In order to obtain a wide-range full-performance high- efficiency vehicle and at the same time reduce pollutant emis- sions, the most feasible solution at present is the hybrid electrical vehicle (HEV), which combines batteries that feed an electrical drive with an ICE [1]. Furthermore, in the plug-in implementation [plug-in HEV (PHEV)], the vehicle can cover 30–60 km with no emissions, using only the electrical drive (all- electric range—AER). In a PHEV, a battery charger is installed onboard, allowing the batteries to be charged during the night directly from the electric power grid, thus increasing overall vehicle efficiency. Moreover, the availability of new energy storage devices, such lithium-ion batteries and ultracapacitors, can improve the vehicle’s electric performance. However, since these also introduce power-flux-management problems [2], [3], a strong multidisciplinary approach is needed to study, design, and optimize the PHEV configuration. Moreover, preliminary

Manuscript received February 27, 2009; revised July 27, 2009. First pub-

lished August 18, 2009; current version published January 13, 2010.

The authors are with the Department of Mechanical Engineering, Politecnico di Milano, 20156 Milano, Italy (e-mail: [anonimizat]; davide. [anonimizat]; [anonimizat]).

Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org.

Digital Object Identifier 10.1109/TIE.2009.2029520

simulations are very important in order to study the interactions between the system components and to assist the designer during the optimization phase and with the control-strategy development.

Different approaches and specific simulation tools have been developed to cope with this problem [4], but the need for a fully extensible model adaptable to any type of vehicle led us to realize a quickly reconfigurable model based on a commer- cial simulation tool, such as MATLAB/Simulink. To obtain a modular model, an object-oriented approach was adopted [5], [6]. The model (experimentally validated) was then used for studying and designing a prototype PHEV.

Since a PHEV requires a large battery pack to ensure a wide AER, the second part of this paper discusses a motor-control method based on the direct self-control (DSC) technique that was studied in order to reduce inverter losses. This reduction in losses allowed us to increase the overall efficiency and reduce the size of the inverter’s cooling system. The total energy benefits were evaluated using the developed PHEV simulation model and experimental results. The experimental PHEV prototype was obtained by starting from a conventional gasoline city car and adding a lithium-ion battery feeding an induction motor with an electrical drive based on a pulsewidth- modulation (PWM)–field-oriented control (FOC) [7], [8]. This vehicle can be schematically represented as a simple parallel hybrid system [7], [22]. The battery ensured 35 km of AER with a maximum speed in pure electric mode of 80 km/h. In Fig. 1, the plug-in hybrid configuration is schematically represented, showing the elements that have been added for the transformation from a conventional vehicle to a plug-in hybrid one.

ENERGETIC SIMULATION MODEL

The simulation model was developed using the object- oriented approach [4]–[6]: Every single device was modeled as an object connected to the others by means of input-signal and output-state variables.

The object set represents the entire vehicle power-train model. All of the devices shown in Fig. 1 will be considered: the driver, vehicle control system, lithium-ion battery, inverter, electric motor (EM), gear box, ICE, fuel tank, and auxiliary on- board electrical loads, while the mechanical model implements the longitudinal dynamic of the vehicle. A detailed description of each subsystem is reported in the following sections. All of the vehicle elements represented in the simulation model were included in a first-order thermal model and the temperature was used only for monitoring purposes. In the case of over

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MAPELLI et al.: MODELING, PROTOTYPE REALIZATION, AND INVERTER LOSSES REDUCTION ANALYSIS 599

Fig. 1. Block diagram of a PHEV.

TABLE I

BATTERY CHARGER DATA

TABLE II

RATING PARAMETERS FOR VEHICLE COMPONENTS

temperature, the torque demand in the EM was reduced to the rated one, and the maximum battery current was limited to the rated value equivalent to rated capacity. The battery charger was a high-frequency push–pull full-bridge converter and was not modeled in the simulated system, even though the energy needed to charge the battery was calculated by taking into

TABLE III

MODEL THERMAL PARAMETERS

output a signal representative of the throttle pedal position. The pilot model acts as a closed loop that compares the required speed to the instantaneous one and calculates the torque ref- erence that is necessary to reduce the difference. Depending on the traction-manager control, the torque request is split between the ICE motor and the electrical drive.

The traction manager can operate in different modes:

combustion-engine mode (CEM): in which the vehicle is propelled only by the thermal engine and the electrical drive traction system is disabled;

electric-vehicle mode (EVM): in which the vehicle works as a pure electrical vehicle using only the energy stored onboard;

start-and-stop mode (SSM): in which the vehicle is pro- pelled using the electrical drive system under a defined speed threshold and using the ICE when the speed is greater than this threshold.

In this block, through torque versus speed curves, the re- quired torque, both for the electrical motor and for the ICE, is saturated to the motor limit [9].

IV. ELECTRICAL DRIVE MODEL

The electrical drive model received as inputs the following:

1) the torque request coming from the traction manager; 2) the angular speed of the EM’s rotor; 3) the battery’s dc voltage vbatt; and 4) the ambient temperature. It gave as outputs the following: 1) the effective motor shaft torque Tel, and 2) the dc current required from the battery ibatt.

The electrical drive model was divided in two submodels, the FOC motor and the IGBT inverter, and a simple first-order thermal model was adopted for both components. The thermal coefficients used for this simulation are indicated in Table III.

A. FOC Motor Model

The model used for the electrical machine was a four- parameter model with stator short-circuit inductance and re- ferred to a rotating reference frame that was synchronous with a rotor-flux space vector ψr [10]

account the component efficiency. The charger data are reported

dψs

in Table I, and the rating parameters for the vehicle components are reported in Table II.

v¯s = Rs¯is + jθ˙ ψs +

(1)

dt

0 = R i + jθ˙ + dψr

(2)

PILOT AND DRIVE-TRACTION-MANAGER MODELS dt

The model received as input the drive cycle that the vehicle has to execute; this references a pilot model that gives as an

Tel = nIm(ψris) (3)

ψs = Lks¯is + ψr ψr = M (¯is + ¯ir )= M¯im (4)

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