1

INVESTIGATION OF THE POTENTIAL OF

GAS TURBINES FOR VEHICULAR APPLICATIONS

Henrique Cunha

Department of Mechanical Engineering – IDMEC, Instituto Superior Técnico,

Technical University of Portugal (TULisbon), Av. Rovisco Pais, 1049-001 Lisboa, Portugal;

e-mail: henriquefecunha@gmail.com

ABSTRACT

Nowadays, the reduction of fuel consumption and

pollutant emissions has become a top priority for society and

economy. In the past decades, some of the environmental

advantages of the gas turbine have led some car

manufacturers to evaluate the potential of this type of engine

as prime mover. This paper suggests a strategy to assess the

fuel consumption of gas turbines applied in road vehicles.

Based on a quasistatic approach, a model was crated that

can simulate road vehicles powered by gas turbines, and

thereafter a comparison was established with reciprocating

engines. The system developed also allows the simulation of

hybrid configurations using gas turbines as range extenders,

a solution that some car manufacturers consider to be the

most promising in the coming years.

Keywords: Gas Turbine, Road Vehicle, Fuel Consumption,

Computational Simulation

NOMENCLATURE

CO2 Carbon Dioxide

CVT Continuously Variable Transmission

ECE Urban Driving Cycle (European)

EUDC Extra-urban Driving Cycle (European)

HC Hydrocarbon

IC Internal Combustion

NEDC New European Driving Cycle

NOx Nitrogen Oxide

OOL Optimal Operation Line

SUV Sport Utility Vehicle

1. INTRODUCTION

The increasing number of passenger cars worldwide and

the increasing rate of global oil consumption, urgently

demands for the development of more efficient power

generation systems for the transportation sector. For the first

time ever, the number of vehicles in operation worldwide

surpassed the 1 billion-unit mark in 2010 [1], a number that is

expected to be 2.5 billion by 2050. This trend will further

increase the pressure on fuel prices and cause serious

problems to the environment. For these and more reasons, the

reduction of fuel consumption and pollutant emissions has

become a top priority for society and economy.

In the past decades, some of the environmental advantages of

the gas turbine, such as low concentration of hydrocarbon and

carbon monoxide emissions, have led some car manufactures

to evaluate the potential of this type of engine as prime

mover.

The development of new powertrain systems involves high

costs. However, these costs can be mitigated by utilizing,

during design, simulation tools that can predict the

performance of the vehicle and its on-board subsystems under

a variety of driving conditions.

The main purpose of this paper is focused on the assessment

of the potential of gas turbine engines for vehicular

applications, in terms of fuel economy. A review of relevant

literature has been performed, regarding different gas turbine

configurations, the past efforts with respect to this type of

engine applied in road vehicles, as well as the simulation

approaches used to predict a vehicle’s fuel consumption. The

methodology adopted in the simulation of both gas turbine

and vehicle models are also described, the results from the

simulations are reported, the conclusions are discussed, and

some future work is proposed.

Previous research has shown the utility of simulation tools in

the prediction of fuel consumption of conventional vehicles

powered by reciprocating engine [2]. This study pretends to

allow this same assessment but for gas turbine engines (in

multiple configurations), operating as prime movers in road

vehicles, in a wide range of simulation conditions.

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2. LITERATURE REVIEW

2.1 Gas Turbine Engine

Since the successful introduction as power plants for

airplanes during the Second World War, gas turbines have

had an immeasurable impact upon society. The favourable

power-output-to-weight ratio makes this type of engine

suitable for several applications, ranging from electric power

generation, mechanical drive systems and jet propulsion.

2.1.1 Single and Twin-Shaft Configurations Gas turbines can be arranged either in single-shaft or

twin-shaft configurations. The single-shaft arrangement

requires the turbine to provide power to drive both the

compressor and the load, which means that the compressor is

influenced by the load, as illustrated in fig. 1. By its turn, in a

twin-shaft configuration the sole function of the first-stage

turbine is to drive the compressor at steady speed without

being influenced by the load, while the net power of the gas

turbine is produced by a free turbine, as it is shown in fig. 2.

2.1.2 Road Vehicle Applications Since road vehicle engines operate at continuously

variable loads and speeds, the twin-shaft configuration, due to

its operating mode, seems to be the most suitable gas turbine

arrangement for this type of application. In fact, considering

its characteristics, a twin-shaft configuration offers excellent

torque at low engine output speeds, which better matches the

vehicle requirements, especially for hill climb and

acceleration conditions. Contrarily to the twin-shaft gas

turbine, the reciprocating engine (the most common

powertrain used for vehicular purposes) has a torque profile

that builds up to a maximum in the mid-speed range and then

declines.

A comparison between the torque-speed profiles of three

different types of engine - a single-shaft gas turbine, a twin-

shaft gas turbine and a reciprocating engine, also called

piston engine - is shown in fig. 3.

2.1.3 Gas Turbine Advantages Beyond its better torque capability (twin-shaft

configuration), the main benefits of the gas turbine,

considering vehicular applications, are its light weight,

compactness and reliability. Its high reliability results from

the reduced number of moving parts (approximately 80% less

than a piston engine), which means a vibration free engine

operation with few balancing problems (absence of

reciprocating and rubbing), low lubricating oil consumption

and lower on-going costs due to the reduced maintenance.

Another advantage of a gas turbine engine, over the spark and

compression-ignition engines, is its capability of operating

satisfactorily with a variety of fuels, including kerosene,

diesel fuel, natural gas, hydrogen and others [4].

2.1.4 Gas Turbine Disadvantages The major disadvantage of the gas turbine is its

extremely low efficiency under no load or partial load, which

constitutes a considerable fraction of the actual operation in

an automotive application. Even at idle conditions, turbines

turn at very high rotational speeds (around 20000 rpm) and

thus consume considerable amounts of fuel. Another

drawback that can be pointed out is the relatively long time

that gas turbine spools require for accelerating from idle to

full load. This slow throttle response, usually called

acceleration lag, is even more pronounced in a twin-shaft

configuration, where the acceleration time depends upon the

free turbine inertia, as well as the inertia and loading

characteristics of the driven equipment [3]. A final problem of

employing gas turbines as automotive power plants is their

high production costs. An estimate from the 70's reveals that

a production volume of 400 gas turbines per day would cost

two and a half times more than an equivalent piston engine

production [5]. Ingersoll [6] points out a cost of $125 per hp

for a mass production of automotive gas turbines, a cost that

is still five or six times higher than the cost of a good spark

ignition engine.

Figure 3. Torque vs. Output Speed (based on data from [3])

Figure 1. Single-Shaft Gas Turbine

Figure 2. Twin-Shaft Gas Turbine

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2.1.5 Previous Projects In the late 1960's, research scientists in California

managed to relate the smog in the air of certain U.S. cities

with some chemical compounds found in automotive exhaust

gases (NOx and HC). This scientific discovery led to strict

national legislation in terms of pollutant emissions, affecting

significantly the automotive industry. Due to the

environmental advantages of the gas turbine, a considerable

amount of work was done in this field with a great support

from the US Government. Chrysler Corporation was the

American car manufacturer that conducted the largest number

of experiences with gas turbine-powered cars [4]. As result,

several prototypes were developed, including the Chrysler

Gas Turbine, as shown in fig. 4.

Interest in gas turbines was also high among truck

manufacturers. The 1965 Chevrolet Turbo Titan III and the

1972 GMC Astro Gas Turbine are some of the many

operational prototypes, aiming at a possible future production

[7]. However, the high manufacturing costs, the continuing

technology refinement of gas turbine engines and the

Government regulations concerning NOx emissions, which

could not be complied, determined the end of these projects.

By the end of the 70’s, almost all gas turbine vehicle

programs were cancelled [8].

The gas turbine also left its mark on the racing track. The first

racing turbine car, the Rover-BRM, participated in 1963 at the

24 hours of Le Mans, achieving a top speed of 235 km/h.

Some years later, this type of engine also made its appearance

in Formula 1 (1971), through the Lotus Team (Lotus 56). In

this car, the gas turbine used was smaller and lighter than a

regular piston engine, the drivetrain was simpler and there

was no need for cooling system; however, the acceleration lag

associated to gas turbines operation determined the end of

this project two years after its first race [9].

During the last two decades, however, the interest in gas

turbines has been revived, with the use of this type of engine

associated with an electric drive system, in a hybrid

configuration. This solution poses as a compromise between

reducing environmental pollution and the limited range

capability of today’s purely electric vehicles. In this

configuration, the gas turbine is only used for maximum

power and for charging the vehicle’s propulsion batteries.

This configuration solves many of the drawbacks previously

attributed to this type of engine, such as the slow throttle

response or the low efficiency under partial load. The most

recent study presented by the automotive industry is the

Jaguar C-X75, as illustrated in fig. 5. This concept car uses a

pair of twin-shaft micro-turbines acting as range extenders, a

solution that Jaguar claims to be even cleaner than the current

hybrids, with just 28g of CO2 emitted per km [10].

2.2 Vehicle Energy and Fuel Consumption

2.2.1 Vehicle Performance Analysis To move a vehicle forward, a propulsive force must be

delivered by the engine. This force is also known as tractive

force (Ft) and it must be such to overcome the resisting

forces, which can be described as the sum of the following:

Aerodynamic Drag Force (Fd)

Rolling Resistance Force (Fr)

Gravitational Force (Fg)

Acceleration Force (Fa)

A schematic representation of these forces is given in fig. 6.

2.2.2 Methods for the Prediction of Fuel

Consumption In order to analyse the efficiency of the propulsion

system for a road vehicle, and consequently its fuel

consumption, there are three possible approaches [11]:

Average Operating Point Approach

Quasistatic Approach

Dynamic Approach

From these three methods, the most used ones are the

Quasistatic and the Dynamic approach. The Average

Operating Point method uses one single representative

average engine operating point (based on a specific test

Figure 4. Chrysler Gas Turbine (1964) [4]

Figure 5. Jaguar C-X75 (2011) [10]

Figure 6. Schematic representation of forces acting on a vehicle in motion

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Figure 9. Diagram of Chrysler Gas Turbine [4]

cycle) in order to assess the mean fuel consumption, a

procedure that makes this a limited model, only suitable for

simple powertrains. The two other methods use a calculation

scheme to generate outputs of the vehicle’s velocity and

energy use, in every time step of a given simulation.

A Quasistatic approach is driven by the required vehicle

velocity, which means that the force required to accelerate the

vehicle through the time step is calculated directly from the

speed trace of the driving cycle. The Quasistatic method may

also be designated as backward-facing approach since the

calculation proceeds backwards, i.e. from the tire/road

interface through the drivetrain, ending with the energy

source (engine and fuel tank), as it is shown in figure 7. Since

this backwards formulation assumes that the vehicle meets

the required speed trace, this method is not suited to analyse

best-effort performance, such as acceleration tests.

In contrast to the Quasistatic approach, the Dynamic

approach begins with a driver model that inputs the throttle

position and braking based on the desired speed. The

computation proceeds forward from the engine, through the

transmission till the wheels, resulting in the calculation of a

tractive force at the tire/road interface, as illustrated in fig. 8.

The versatility of this method, which can also be called

forward-facing approach, makes it desirable in detailed

control simulations and hardware development.

However, the relatively high computational demand

associated to this method turns it into a too much time-

consuming solution for preliminary design. For that reason,

the Quasistatic approach is the most used method for

predicting vehicles fuel consumption and is also the method

utilized within this study [11].

3. METHODOLOGY

3.1 Gas Turbine Modelling

3.1.1 Proposed Models In this paper an attempt is made to assess the

applicability of gas turbines in road vehicles. As a starting

point, an engine model (model 1) was developed based on a

spec-sheet of a gas turbine developed by Chrysler

Corporation for automotive applications, during the 60’s [4].

This model, illustrated in figure 9, uses a regenerator (heat-

exchanger) that recovers much of the heat from the exhaust

gases, enabling the achievement of acceptable exhaust

temperatures and fuel consumption, at least for that period.

To assess the influence of heat-exchangers in the

thermodynamic cycle of a gas turbine when used as an

automotive power plant, a similar gas turbine was also

modelled, but without regenerator (model 2).

Although relevant to this study, the Chrysler gas turbine is an

“antique” model with component efficiencies substantially

lower to what can be achieved with the latest technology. In

order to establish a fair comparison with modern

reciprocating engines, a third engine was modelled

representing the modern gas turbine (model 3). The major

change carried out, compared with the Chrysler model, was

in terms of turbine inlet temperature, the parameter with the

most pronounced effect on the overall gas turbine

performance [12]. The change of the turbine inlet

temperature, at nominal conditions, implies the selection of

overall pressure ratio and the re-calculation of

compressor/turbines efficiency. A parametric study was

performed, in which the variation of the specific fuel

consumption was evaluated in a range with different

compressor pressure ratios.

The thermodynamic cycle of the three different gas turbine

models was assessed using an in-house performance code, for

both design and off-design point operating conditions.

However, due to some limitations associated with the version

of this software it was not possible to assess engine behaviour

in the full range of output speed and power. In order to get

the full performance spectrum, the results generated by the

performance code were post-processed.

3.1.2 Post-Processing Data An algorithm was developed with the purpose of

conceiving engine maps for any gas turbine configurations,

and thus to assess its fuel consumption when operating as a

road vehicle powertrain. The first part of this algorithm

consists of reading the data generated by the performance

code, and then extrapolate (based on several assumptions) in

order to get the output torque and shaft speed values for the

entire spectrum of operating conditions, as shown in fig. 10.

Figure 7. Quasistatic Approach Diagram

Figure 8. Dynamic Approach Diagram

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The second part consists of filling the sparse data matrixes,

through the use of linear interpolations, to enable the

assessment of the fuel consumption necessary to sustain any

torque/speed combination, as illustrated in fig. 11.

3.1.3 Gas Turbine Engine Map In figure 11, the engine map is represented in terms of

fuel mass flow (kg/s). This map is useful for assessing the

engine fuel consumption. Nevertheless it is inappropriate for

comparing fuel efficiency between different engines.

Therefore, the engine performance is represented in terms of

specific fuel consumption (g/kWh). In figure 12, the

efficiency map of gas turbine model 1 is illustrated, in which

it is possible to verify that this type of engine achieves its

highest efficiency at maximum output speed and power. At

lower rotational speeds, the pressure of the compressed air

decreases, resulting in a dramatic drop in thermal efficiency.

On the other hand, reciprocating engines are typically more

efficient at maximum torque.

3.2 Vehicle Modelling The purpose of this study is to attempt the evaluation and

comparison of the performance, in terms of fuel consumption,

of several road vehicles powered with different internal

combustion engines, with a special focus on gas turbines. To

do so, an existing simulation tool was used, known as QSS

[13]. For creating a simulation model that can describe all

aspects of the vehicle significant for estimating fuel

consumption. The QSS toolbox was developed by ETH

(Zurich) and consists of a collection of Simulink blocks and

m-files. This tool permits the design of powertrain systems in

a flexible manner and allows a fast and simple estimation of

the fuel consumption of such systems. There are several

parameters that can be set in these simulation blocks,

concerning the driving pattern, the chassis of the vehicle, its

type of engine, the gear system used or the type of fuel, as

illustrated in fig. 13.

3.2.1 Vehicle Model powered by Gas

Turbine The sub-models described above were used to model a

vehicle powered by a gas turbine, as illustrated in fig. 14.

Figure 14. Simulink model of a vehicle

powered by a gas turbine

Figure 13. QSS toolbox library [13]

Figure 11. Algorithm Diagram – part 2

Figure 10. Algorithm Diagram – part 1

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Driving Cycle

It is of interest to simulate the vehicle under different driving

cycles; different driving conditions imply different demands

and consequently distinct results. Therefore, three default

driving cycles were chosen: an urban, extra-urban and

combined driving. Furthermore, a custom driving cycle was

created in order to analyse the vehicle model at constant

speed conditions. Regarding the default driving cycles, these

were the three European regulated cycles: ECE (urban),

EUDC (extra-urban) and NEDC (combined).

Vehicle Category

With the aim of making a meaningful and relevant study,

three different vehicle categories were chosen: a small, a

medium and a large sized car, with the respective

designations of city car, family car and SUV. Most of the

parameters input, as detailed in table 1, were taken from

spec-sheets of vehicles that are currently in production.

Gas Turbine Engine

One of the main limitations of the QSS toolbox is the lack of

a block simulating a gas turbine engine. Significant changes

were performed in the Combustion Engine block in order to

simulate the gas turbine operation, and thus assess its

performance and fuel consumption. The default fuel

consumption map corresponding to piston engines was

replaced by an executable code that generates the fuel

consumption of a gas turbine; an efficiency map is presented

in figure 12. The developed code is generic in the sense that

it is capable of simulating the fuel consumption of any gas

turbine modelled with a performance code.

It is important to note that there are some important

differences between reciprocating engines and twin-shaft gas

turbines that need to be taken in consideration. For instance,

while a piston engine only has one rotating output shaft, a

twin-shaft gas turbine has two different sets of rotating parts,

the high and low pressure spools. Since there is no

mechanical connection between these two spools, their speed

can be considered independent from each other. This fact

makes the assessment of the inertia force of the engine

difficult. This is an important parameter used in the

determination of the vehicle performance. In this model,

although the inertia forces are exclusively calculated based on

the low pressure spool acceleration, a somehow higher inertia

was used as an input in an attempt to account for the inertial

forces generated when varying high pressure spool speed.

Gear System

The drivetrain is an essential system in the whole vehicle

model, since it is responsible for the transmission of the

mechanical work between the gas turbine and the wheels. The

great influence of this system in the engine operation, and

thus in the vehicle fuel economy, requires special attention to

its modelling. Considering vehicular applications, the ideal

power plant should have a performance characteristic with a

constant output power over the entire vehicle speed range.

This constant power characteristic provides the vehicle with a

high tractive effort at low speeds, as illustrated in figure 15,

i.e. in situations where demands for acceleration or grade

climbing capacity are high [14].

In the case of reciprocating engines, the torque-speed profile

is almost flat compared to an ideal power plant, as previously

illustrated in figure 3. Therefore, a multi-gear transmission is

usually coupled to piston engines in order to convert its

torque characteristic close to the ideal one, as illustrated in

figure 16.

Figure 12. Efficiency Map – g.t. model 1

Table 1. Vehicle Parameters

Figure 15. Ideal performance characteristics for a vehicle traction power plant [14]

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As described in section 2.1.2, a twin-shaft gas turbine offers

excellent torque at low speeds for hill climb and vehicle

acceleration. Since its speed-torque profile is much closer to

the ideal one, twin-shaft gas turbines only require a small

number of gears, as shown in fig. 17.

Rather than a manual gearbox, a Continuously Variable

Transmission (CVT) was chosen for the gas turbine.

Although CVTs typically offer lower efficiencies than manual

gearboxes, their operation depends less on the driving style,

i.e. driver behaviour. A CVT system is mechanically designed

to provide an infinite number of gear ratios, which enables

the engine to operate close to the called Optimal Operation

Points1, resulting in an increased fuel economy. The CVT

operation requires the use of a controller containing an

algorithm that determines the ideal gear ratio depending on

the power demanded [15].

Additional to that, due to the extremely high rotational speeds

of the power turbine, a reduction gear needs to be

implemented in the transmission, in order to reduce the

output shaft speed.

CVT Controller

The Continuous Variable Transmission makes part of a group

of gear systems characterized by an automatic operating

mode. This mode requires the use of a controller that replaces

the driver in the selection of the most adequate gear ratio

during the drive. In this model, a completely new CVT

controller was developed, with the purpose of: i) allowing its

“interface” with the gas turbine data generated by the

performance code and ii) ensuring a more accurate

calculation of the power required to drive the vehicle.

The main function of the controller is to determine the

optimal CVT gear ratio. This procedure starts with the

1 The Optimal Operation Points are the engine torque-speed

combinations in the entire engine power range, with the minimum specific

fuel consumption.

assessment of the power required by the vehicle to perform

the speed trace pre-defined in the driving cycle. This

assessment is based on the resisting forces actuating on the

vehicle in motion (section 2.2.1), the losses associated to the

drivetrain system, and inertia forces due to the vehicle

acceleration. After calculating the power required to drive the

vehicle, the CVT controller determines at which speed the

engine should be operating. This assessment is performed by

a code that defines the Optimal Operation Points of each gas

turbine engine being analysed, based on the correspondent

engine map, as illustrated in fig. 18. The connection of all

these points sets the Optimal Operation Line (OOL), a quite

irregular curve that results from the very small fluctuation of

fuel consumption levels over a large operating region.

As previously mentioned, the transient performance of a gas

turbine is characterized by a slow throttle response. With this

in mind, it was decided to implement in this new CVT

controller, a function that allows the operator to input the

adequate acceleration lag, i.e. the time that gas turbine

spools take from idle to full load, after the accelerator pedal

is depressed. This improvement aims to simulate the gas

turbine operation more realistically.

Figure 16. Tractive effort characteristics of a 96 kW reciprocating engine

Figure 18. Efficiency Map of g.t. model 1 with the correspondent OOL

Figure 17. Tractive effort characteristics of a 102 kW twin-shaft gas turbine

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Figure 21. Operation points of g.t. model 3 powering the city car in the NEDC

3.2.2 Vehicle Model powered by

Reciprocating Engine A model simulating conventional vehicles, i.e.

powered by a reciprocating engine and coupled to a manual

gearbox, was implemented, as illustrated in fig.19.

Thereafter, the results obtained were compared with results

for the gas turbine, in terms of fuel consumption, for several

driving conditions.

4. RESULTS

The first simulations were performed using the default

driving cycles earlier mentioned: ECE, EUDC and NEDC.

The results are illustrated in figure 20.

According to the results presented, the fuel consumption is

always higher in an urban drive (ECE). In this driving cycle,

the start-stop traffic conditions, found in the congested urban

networks, are simulated through the immobilization of the

vehicle in several occasions over time. These idling situations

have a severe effect on the average fuel consumption, since

the engine is working, i.e. consuming fuel, for a distance

covered equal to zero.

The results for the two Chrysler gas turbine versions (model

1 and 2) allow as also to assess the importance of the heat-

exchanger in the overall efficiency of a gas turbine. For a

combined driving cycle (NEDC), model 2 (without heat-

exchanger) consumes 178% more fuel than model 1 that

recovers part of the energy stored in exhaust gases through a

regenerator. An even higher fuel economy can be achieved

with the gas turbine model 3 that has components

(compressor and turbines) with higher efficiencies and

operates at an inlet turbine temperature 150º higher than the

one used in the Chrysler models. With this model the fuel

economy improves 34% when compared with model 1 in the

NEDC.

Since model 3 is the gas turbine with the best performance, in

terms of fuel consumption, a detailed comparison was carried

out between this model and the results corresponding to the

vehicles powered by a reciprocating engine, as shown in table

2.

Although model 3 has the best fuel economy among all gas

turbine models simulated, it still has a fairly poor

performance compared to the reciprocating engine. For the

city car, model 3 demonstrates fuel consumption values about

118% higher than the corresponding piston engine model. In

turn, for the SUV this difference is reduced to 75%. As a

matter of fact, it can be observed that the difference between

the gas turbine and piston engine reduces as the vehicle

weight increases. This trend can be explained by the fact that,

in heavier vehicles, more power is required from the engine.

In other words, for heavy vehicles, like an SUV, the gas

turbine operates closer to its nominal conditions, i.e. the

operating conditions for which it was designed. Basically, it is

appropriate to conclude that the gas turbine has a better

relative fuel consumption in the SUV, due to the higher

operational efficiencies achieved in the simulations (lower

overall specific fuel consumption). This statement can be

confirmed by figures 21 and 22, where one can observe how

the gas turbine operates at substantially better efficiency as

engine load increases.

Figure 19. Simulink model of a vehicle powered by a reciprocating engine

- 34%

+ 178%

Figure 20. Simulation results for the default driving cycles

Table 2. Fuel consumption results correspondent to reciprocating eng. models and g.t. model 3

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From these last two figures it is also possible to verify the

increased proximity of the engine operation points (white

dots) to the Optimal Operation Line, in the case of the city

car for a larger part of the driving cycle. This is a

consequence of the higher acceleration lag of the heavier

vehicle. In situations where the free power turbine cannot

operate at its ideal speed for a given power requirement,

represented by the OOL, the high pressure spool increases its

speed, in order to increase the output power delivered, and

thus achieve the requirements imposed by the driving cycle.

It is important to note that in both figures there are the same

number of dots. However, because the operation points are

closer to the OOL in the city car, they are overlapped, and

thus less visible.

To get a more detailed comparison between the reciprocating

engine and model 3, the evolution of the fuel consumption of

both engines powering the SUV along the NEDC is plotted in

fig. 23. The extremely high fuel consumption found for both

engines, at the early stages of the driving cycle are attributed

to idle operating conditions, which represent those situations

when the engine is running but the vehicle is immobilized.

From figure 23 it is also possible to observe that model 3 has

a higher idle fuel consumption than the reciprocating engine.

This means that there are little benefits in using gas turbines

in urban driving conditions.

In order to understand some of the uncertainties in these

results it is important to assess the percentage of operation

points that were calculated based on either the extrapolation

or linear interpolation of the data generated by the

performance code. This assessment is relevant since it can

address two different sources of error in the gas turbine data.

On one hand, one has the data generated by the linear

interpolation of the original data, which have a higher level of

certainty. On the other hand, one also has the data obtained

by extrapolation (assumptions) and whose accuracy is rather

difficult to assess. Depending on the type of vehicle in

analysis, the percentage of operation points found inside the

“original data” area (the most reliable data) varies. Since

heavier vehicles require more power from the engine, the

SUV has a higher percentage of operation points inside this

area than the city or family car, as it is shown in table 3. In

this same table, the percentage of fuel consumed in the

NEDC, that is associated to this area, is also given. The

percentages achieved reflect the better level of uncertainty

associated with the simulation of those vehicle and driving

cycle combinations that force the engine to operate closer to

its design point, i.e. in demanding situations.

In order to provide a better understanding of these two

different groups of results, the operation points associated to

gas turbine model 3 powering the SUV in the NEDC are

illustrated in figure 24. In this figure, the operation points

located inside the “original data” area, i.e. the data generated

by interpolation, are represented by dark points, while the

remaining points (outside this area) have a white coloration.

Figure 22. Operation points of g.t. model 3 powering the SUV in the NEDC

Table 3. Percentage of operation points (NEDC) located inside the “original data” area of model 3

Figure 23. Fuel consumption evolution of SUV along the NEDC

Figure 24. Operation points of g.t. model 3 powering the SUV (NEDC)

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Apart from the three default driving cycles used, a

customized one was also created with the purpose of

simulating a vehicle running at constant speed (100km/h).

The fuel consumption of the SUV when powered by either

the reciprocating engine or the gas turbine (model 3) was

assessed. At this driving condition, it was verified that the gas

turbine is less efficient, requiring some 3.6 litres more of fuel

per 100km.

It is also important to note that the predictions for the

vehicles powered by piston engines are quite similar to the

fuel consumption values provided by some car

manufacturers.

5. CONCLUSIONS & FUTURE WORK

The simulations performed generated quite distinct

results for the different vehicles categories, driving patterns

and engine models simulated. From these results it is possible

to identify different trends, and hence draw some interesting

conclusions:

The absence of heat-exchanger in gas turbines

applied in road vehicles increases the fuel

consumption in 178%, on average.

A modern gas turbine can be 34% more efficient

than the Chrysler gas turbine model from 1964.

Vehicles equipped with a gas turbine have higher

fuel consumption than the ones with reciprocating

engines, independently of the driving conditions

simulated: urban, extra-urban or combined driving.

For a given power, gas turbines have a better relative

fuel consumption when applied in heavier vehicles,

since the engine operates closer to its design point,

resulting in a higher overall efficiency.

At idle conditions, gas turbines have a substantially

higher fuel consumption compared to reciprocating

engines. This fact indicates a limited benefit from

the use of gas turbines in urban driving conditions

where the vehicle immobilization occurs frequently.

Exception to this could be a hybrid configuration.

Operating at a constant regime, when the SUV is

moving at a constant speed of 100km/h, the modern

gas turbine requires some 3.6 litres more of fuel per

100km than the reciprocating engine.

It would be of added value to compare the fuel consumption

between gas turbines and reciprocating engines, in

demanding driving conditions, such as acceleration tests.

However, in order to proceed with an accurate analysis, a

dynamic approach would need to be implemented in the

simulation model compared to the quasistatic approach

utilized within this study.

The methodology developed in this work sets the framework

for performing system assessments and providing first

estimates for the fuel economy of different powertrain

topologies. Some car manufacturers argue that the use of a

gas turbine operating as range extender in a series hybrid

configuration is the most promising solution in the coming

years. Looking at potential future work, the developed

platform could be used for modelling and simulating hybrid

powertrains, combining electric propulsion with gas turbines.

Furthermore, innovative cycles could also be investigated,

such as: i) an intercooled-recuperated cycle with variable

geometry vanes in the power turbine, and ii) a combined

cycle configuration, i.e. a gas turbine with a heat-exchanger

on the hot side recovering part of waste heat of exhaust gas to

a steam cycle.

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