Method of Turbocharger Emulation on Engine Test and Application to Turbocompound System Opti-

misation

K. Zhanga,1, G. Subramaniana,2, P. Garimellab,3 and S. Akehurstc,4

a Cummins Turbo Technologies St.Andrews Road, Huddersfield, HD1 6RA, United Kingdom b Cummins Inc., Cummins Tech Centre, Columbus, United States c University of Bath Claverton Down, Bath, BA2 7AY, United Kingdom

Abstract: Matching turbocharging systems to an internal combustion en-gine plays an important role in engine development to meet stringent emission legislations and customer demands such as specific power output and fuel economy. Advanced turbocharging solutions such as variable ge-ometry turbochargers, two-stage and turbocompound systems require an extensive simulation and hardware testing on engine dynamometer. GT-Power simulations were performed to evaluate the fuel economy po-tential of a turbocompound system compared to an equivalent rating heavy duty diesel engine. Simulation results were promising at rated speed and load. However at part loads, turbocompound results were less promising. This paper describes a novel engine testing approach that in-volves a virtual turbocharger emulator incorporated into an engine test facility via hardware-in-loop (HIL) testing system. The HIL testing offers engine performance optimisation without extensive hardware testing at a moderate cost in a shorter timeframe. Engine tests were conducted with real time control of a power turbine emulator valve for turbocompound system performance evaluation, and simulation results were validated against test data.

Key Words: turbocompound; turbocharger emulator; real-time turbocharger modelling; hardware-in-loop testing

1 E-mail: kai.zhang@cummins.com, URL: www.cummins.com/turbos 2 E-mail: ganesan.subramanian@cummins.com, URL: www.cummins.com/turbos 3 E-mail: phanindra.garimella@cummins.com, URL: www.cummins.com 4 E-mail: S.Akehurst@bath.ac.uk, URL: www.pvrc.ac.uk

1 Introduction In order to meet tightening toxic emission regulations and increasing needs of lower fuel consumption and CO2 emissions, turbocharging is playing a vital role in internal combustion engine development. Turbo-compounding has been known for decades as a method of further recover-ing waste heat energy that leaves the main turbocharger turbine. Turbo-compound engine systems include a secondary turbine in the exhaust sys-tem downstream of the turbocharger which enables additional power from the hot exhaust gas to be transmitted to the engine crankshaft mechani-cally or electrically. It is therefore possible to increase engine specific power output as well as reduce fuel consumption. Cummins Turbo Tech-nologies have been working with various engine OEMs to develop turbo-compound systems [1, 2] in the last two decades, with applications cover-ing both on and off highway at the latest emission legislations. Turbocompound engines offer better fuel efficiency on applications where the engine spends a majority of its time running at high loads. However, turbocharger matching involves extensive analytical and experimental work. This is to optimise target engine operating points due to the com-plexity of interactions with engine sub-systems such as fuel injection, inlet/exhaust valve train, Exhaust Gas Recirculation (EGR) ratio, exhaust temperature management, etc. Moreover, power turbine size optimisation and the gear ratio selection for turbocompound engines is a complex and time consuming task. In addition, mechanical design of a suitable gear train system may cause long lead time to test the prototype turbocom-pound engine in an engine test cell. A novel engine test approach using virtual power turbine emulation on engine testing can reduce turbocom-pound engine development cost and time significantly. This paper details an advanced turbocompound system emulation involv-ing real-time simulation techniques, hardware-in-the-loop (HIL) systems and an engine back pressure valve with full control authority to achieve the aforementioned goals. Previous research [3] using a variable geome-try turbocharger (VGT) emulation to control a Charge Air Handling Unit (CAHU) to assess engine performance indicated considerable accuracy compared with real engine test results. In this paper, an advanced power turbine emulator model was developed with better stability and controlla-bility, and the system was evaluated experimentally on a heavy duty die-sel engine in conjunction with turbocompound engine performance analy-sis and system optimisation.

2 Engine Cycle Simulation of a Turbocompound Engine

Turbocompounding is not a new concept and has been well known for decades as a viable concept for recovering exhaust energy and supplying it back to the engine crankshaft. A downstream power turbine, which can be axial or radial, is mounted downstream of the turbocharger and is me-chanically connected to the crankshaft by a gear train. The power turbine can be connected to a turbine generator, referred to as an electric turbo-compound system [4]. The electrical option offers better flexibility in power turbine operation and no need of additional coupling for power transmission between high-speed turbine to low-speed engine crankshaft. Typical levels of fuel economy benefit from turbocompounding have been claimed by many engine OEMs to be approximately between 3 to 10% de-pending on the duty cycle and power turbine design speed [5]. However, aggressive engine performance and emission targets drives modern heavy-duty diesel engines to use emission solutions such as cooled EGR, Selective Catalytic Reduction (SCR) and Diesel Oxidation Catalyst (DOC) plus Diesel Particulate Filtration (DPF) after treatment devices. This pro-duces challenges for meeting air handling demands of the engine. For ex-ample, a heavy-duty EGR engine requiring high EGR levels (e.g. 30%) re-duces the amount of energy available in the exhaust stream to the power turbine and further after treatment back pressure makes a net power gain difficult. Moderate levels of EGR flow are used for Euro II to IV diesel engines com-pared to Euro V and Euro VI typical EGR levels. Hence the power turbine can recover more than the power lost from higher pumping work caused by the high exhaust manifold pressures necessary for EGR on a Euro IV diesel engine. However, typical back pressure levels and EGR rates make achieving the balance between pumping work increase and power recov-ery more difficult on modern Euro VI engines [1, 6]. In order to understand the sensitivity of a turbocompound (TCPD) system, fuel consumption (BSFC) benefits to major engine parameters – namely engine power, EGR rate, exhaust back pressure and turbo machinery effi-ciency – a number of engine cycle simulation studies using GT-Power have been performed to evaluate the potential benefits of a TCPD system on various ratings of a heavy-duty diesel engine. The baseline simulations were performed by varying engine power (340, 400, 460 and 520HP), back pressure (1.0, 1.1, 1.2 and 1.3 bar), EGR levels (0, 10, 20 and 30%). In this study, analysis was done only at full load B100 and C100 load points. Figure 1 shows the GT-Power prediction results of the net BSFC benefit from a turbocompound engine compared to an equivalent baseline engine.

GT-Power results showed that if the engine has high EGR (~30%), high back pressure and low power, turbocompounding isn’t very at-tractive as the balance of pumping work increase is much higher than the net power recovered.

Predictions showed about 5% benefit at B100 with 520HP TCPD en-gine at 0% EGR engine and 200mbar backpressure (Figure 1). How-ever this benefit disappears for the same rating at about 20% EGR.

Figure 1: GT-Power simulation results of Net BSFC benefit as a function of

engine power and EGR levels.

Figure 2: DOE analysis of engine BSFC at different levels of EGR ratio,

back pressure

Net BSFC benefit at B100

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EGR rate (%)

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efit

(%

)

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Figure 2 shows the predicted BSFC benefit as a function of EGR levels and power turbine back pressure. As seen from Figure 2, a 460HP engine with typical Euro III and Euro IV levels of EGR and back pressure (15% EGR and 100mbar back pressure) showed a BSFC benefit of between 2.5% to 5% with TCPD system. However it becomes almost zero or negative with use on a modern engine of 30% EGR and 200mbar back pressure. However, it should be noted that engine parameters such as injection pressure, timing and injection profile have not been optimised for the BSFC benefit evaluation study. Hence the BSFC benefit may vary depend-ing on the engine. It is important to specify that the benefit varies also with the application duty cycle. If the engine operates most of the time at its full load and full speed, it may be possible to see the above BSFC fig-ures in practical use. On the other hand, if an engine runs mostly at part load, on a cycle-average basis BSFC benefit will be further reduced based on its duty cycle. The validation of simulation results is essential due to limitations in modelling of NOx and particulate emissions. Moreover, vali-dating above simulation results within the reasonable amount of develop-ment time and cost would be more beneficial. However, development of a turbocompound engine from an existing baseline engine is much more complex and expensive. The following sections of the paper present the development of a real-time HIL emulation system that was developed and utilized to assess the impact of the TCPD system on the engine perform-ance to enable rapid air-handling and turbo system selection.

3 Hardware-in-the-loop Development for Tur-bocompound System Emulation

The schematic of the HIL system used for the emulation is shown in Figure 3. A heavy-duty diesel engine is utilised as the test bed for understanding the impact of a TCPD system. The engine turbine is a traditional variable geometry system (VGT) with the VGT position overridden to stay at a fixed position. The impact of the power turbine on the engine is twofold: it generates additional power that is provided to the turbine and has an im-pact on the back pressure that acts on the engine as a function of the ex-haust flow. The impact of the power turbine on the engine behaviour is captured using a model of the power turbine embedded in the dSPACE system. The calcu-lated power turbine power that is utilized in the real-time embedded model is given in equation 1.

mechisin

outinexh

P

PTCpmP

1

1 Eq. 1

P … Power turbine power

exhm

Cp

Tin

Pin

Pout ηis ηmech

… … … … … … …

Exhaust mass flow rate Specific heat capacity at constant pressure Turbine inlet temperature Turbine inlet pressure Turbine outlet pressure Turbine isentropic efficiency (total-to-static) Transmission mechanical efficiency

Since the power turbine has an impact on the back pressure which changes with the operating condition of the engine, the dSPACE system also controls a back-pressure valve to meet the target turbine outlet pres-sure as estimated by the embedded model of the power turbine. The block diagram in Figure 4 schematically describes the algorithm that is embed-ded in the dSPACE system. This algorithm provides a real-time model of the power turbine which predicts both the additional shaft power that is provided to the engine and the additional back pressure due to power tur-bine. In addition to the signals that are measured using engine mounted sen-sors (e.g. engine speed, fuel-mass flow, and fresh-air flow), we also utilise measurements of instrumentation grade sensors for the measurement of pressure and temperature at the inlet and outlet of the exhaust back-pressure control valve. Because the flow is highly turbulent in this area, a number of sensors are mounted as shown in Figure 5.

Figure 3: Schematic of the HIL system used for the turbocompound emulator.

Turbo-compounded

system embedded model

Prediction of the power provided to

shaft

Prediction of engine back-

pressure

Communicated to test-cell data

acquisition system

Control of the back-pressurecontrol valve

Exhaust throttle

Engine Signals

PositionCmd to Exhaust Throttle

Figure 4: Flowchart of the algorithm that is utilised to predict engine back-pressure and the power turbine power added to the engine shaft.

Figure 5: Mounting of the temperature and pressure sensors at the inlet and outlet of the exhaust back-pressure control valve.

In order to control the exhaust throttle to target a particular back pres-sure as estimated by the embedded real-time power-turbine model, a controller is designed with feed-forward, feedback controller design. The feed-forward controller is based on an orifice flow model and the feedback controller is a PI controller, which helps with measurement uncertainty and system variations during the tests. In Figure 6, we show the behav-iour of the turbine back-pressure controller as some snap throttle tests that modify the commanded torque are conducted.

Figure 6: Behaviour of the back-pressure control system in meeting the commanded back pressure as estimated by the real-time power-turbine

emulator.

4 Real-time Power Turbine Model

4.1 Overview of Modelling Approaches

In terms of presenting turbine performance in a model, there are mainly two approaches: experimental and analytical methods. Experimental method refers to turbine performance data gathered on test facilities with outputs in a format of reduced mass flow rate, shaft rotational speed, gas pressure ratio, and isentropic efficiency. Analytical methods calculates the fluid conditions in each turbine stage (e.g. turbine housing, nozzle, wheel, exducer) and can be simulated spatially in one, two or three dimensions depending on computational speed vs cost constraints. HIL requires the model to be able to transmit signals with sensors, actuators, engine control module (ECM) and engine test data acquisition system in real time, which means that no delay is allowed when processing the power turbine simulation. Hence, due to the operating speed and accuracy demand, turbine maps in a format of tabulated data measured by experimental tests are applied to the real-time power-turbine model.

4.2 Turbine Map Data Enhancement

Turbine experimental data provided by Cummins Turbo Technologies are based on data acquired by a turbine dynamometer. Compared with con-ventional gas stand tests, this unique mapping approach allows turbines to be tested in a much wider operating region without the restrictions from attached compressors. Although this testing method provides wider and denser turbine map data range, it remains a challenge to produce turbine maps at very low flows and turbine speeds. This is due to mini-mum power absorption of the dynamometer and measurement stability, caused by flow fluctuation from the radial inflow turbine at low pressure and speed conditions. The accuracy and density of turbine performance data is crucial to achieve better accuracy in 1D engine cycle simulation (ECS) analysis. An in-house tool was therefore programmed to support engine OEMs’ simulation work, via interpolation and extrapolation by curve-fitting turbine data based on experimental test results. This map tool can generate the final format according to the requirements from en-gine cycle simulation programs (e.g. GT-Power), and also to simplify the data handling in ECS and to improve the prediction of turbocharger and subsequent engine performance. The turbine map conversion tool is based on mathematical approaches, mainly multi-variant non-linear regression techniques to interpolate and extrapolate turbine efficiency and mass flow rate. The whole process is focused on normalising each map data point with its peak efficiency and using regression as a tool to predict the performance at non-tested re-gions. To ensure the quality of maps, at any stage of the data conversion process, curve-fit standard deviation is monitored to ensure the curve fit accuracy within predefined limits. A snapshot of the curve-fit results is shown in Figure 7.

Figure 7: Turbine map data interpolation and extrapolation (red is experi-mental data; blue is curve fit results)

4.3 Power Turbine Model in Real Time

The power turbine model was developed in the Simulink environment of MATLAB. It was then compiled to a real-time capable model in C code us-ing MATLAB’s real-time workshop, so that the power turbine model can be executed on the dSPACE platform in real time. The power turbine model is fed with input signals, such as engine speed, turbine inlet pressure turbine inlet temperature, air/fuel ratio, mass flow rate, and turbine outlet pres-sure. Subsequently the model works out turbine efficiency, pressure ratio, turbine inlet pressure set point and other parameters, using linear interpo-lation and extrapolation from look-up tables consisting of the enhanced turbine map data. This turbine modelling system has been assessed from previous research at University of Bath [7, 8], and good agreement has been observed against real engine experimental data at steady-state conditions. How-ever, previous research [3] indicated that the input signal of turbine inlet pressure, which is used to calculate reduced mass flow and speed pa-rameters in turbine maps, may interfere with the model control output signal (i.e. turbine inlet pressure set point) and thus affect the system controllability and stability. Therefore a new model was created using an

iterative loop to work out turbine inlet pressure based on input signals of exhaust mass flow rate and turbine inlet temperature and the flow charac-teristics from turbine maps. Due to the demand of real-time operation, at each time step, the model is required to compute and supply output sig-nals faster than the actual time step. This task has been accomplished by using a variable time step iterative loop in the model to calculate turbine inlet pressure which runs faster than real time. This is necessary in order to provide converged turbine inlet pressure signal output with a high level of accuracy and stability to emulate the exhaust back-pressure valve hardware and process data in the subsequent calculations. This feature was achieved by implementing a fixed pressure step increment with error tolerance equals to 0.2% in MATLAB Simulink. A snapshot of the real-time power turbine model with iterative loop calculation is demonstrated in Fig-ure 8. This design enables the engine exhaust back-pressure valve to be emulated in a control system with more stable and accurate set points. Power turbine design parameters such as wheel size and housing flow ca-pacity are also implemented into the power turbine model through similar-ity by using truly non-dimensional variables (i.e. reduced speed and flow rate). Therefore, the power turbine flow size can be changed and evalu-ated in order to optimise the turbocompound engine at targeted operating points.

Figure 8: Advanced power turbine in Simulink with iterative loop to calcu-late turbine inlet pressure.

1

Turbo Speed

z

1

Unit Delay2

z

1

Unit Delay1

z

1

Unit Delay

Engine_Speed_rpm

P_prePT_bar_abs

T_prePT_K

M_f uel_kg/s

P_post_PT_bar_abs

M_air_kg/s

P_PT_inlet

Power_PT

Ef f _turbine

U/C

Turbo Speed

Gear train loss

Turbine_model

<

RelationalOperator1

<=

RelationalOperator

Pressure Difference

|u|

P_diff

In1 Out1

P_PT_inlet_sp5

In1 Out1

P_PT_inlet_sp4

In1 Out1

P_PT_inlet_sp3

In1 Out1

P_PT_inlet_sp2

In1 Out1

P_PT_inlet_sp1

In1 Out1

P_PT_inlet_sp

Geartrain_loss

Data StoreWrite5

BSR

Data StoreWrite4

Eff_turbine

Data StoreWrite3

Power_PT

Data StoreWrite2

P_PT_diff

Data StoreWrite1

P_PT_inlet

Data StoreWrite

1

Constant

f()

function

6

Pressure_increment

5

M_air_kg/s

4

P_post_PT_bar_abs

3

M_fuel_kg/s

2

T_prePT_K

1

Engine_Speed_rpm

4.4 Power Turbine Transmission Loss Model

The prediction of energy losses in the power turbine transmission plays an important role when assessing the overall performance of a TCPD system for fuel efficiency. The energy losses in the power transmission system involve bearing shaft loss, gear losses (mesh loss, churning loss and windage loss), and fluid coupling slip losses. A complete simulation for a power turbine drive train system would need an accurate model of each gear train stage. Therefore due to the absence of a detailed physical model of each gear train component from the gearbox manufacturer, a prediction of energy loss via experimental data gathered in a turbine test cell was applied. In the power turbine test cell, a gear box with fluid cou-pling is connected between the power turbine and the turbine dynamome-ter that measures the shaft torque and power output. The gross specific power output from the power turbine is calculated from measured gas mass flow rate, inlet/outlet pressures and temperatures where sensors are carefully adjusted to avoid the uncertainties caused by flow distribution at the turbine exit. The lubrication oil temperatures at inlet and outlet of dy-namometer are also monitored to avoid excessive heat transfer, which may lead to errors in the power calculation. Energy losses in the power turbine transmission system were subsequently modelled based on rela-tionships (Eq. 2) between the energy loss at each component and power turbine speed or load. A comparison of power turbine energy losses in test data and simulation results is shown in Figure 9. It can be observed that the accuracy of the power turbine drive-train model is higher than 95%. Eq. 2

grossPtP _

newPtP _

PtTq

max_PtTq

a,b,c,d

…

…

…

…

…

…

Power turbine power (gross)

Power turbine power (net)

Power turbine torque

Maximum power turbine torque

Power turbine speed

Coefficients

Figure 9: Power turbine energy loss (simulation vs. test results).

dTq

TqcPaPP

Pt

PtbgrossPtgrossPtnetpt )1)(1(

max____

5 Test Results and Discussion The turbocompound emulation system shown in Figure 3 was developed and successfully tested to investigate turbocompound BSFC benefit num-bers that are seen from full GT-Power system simulations. For this pur-pose, engine tests were carried out on a heavy-duty diesel engine at three engine operating points, such as cruise point speed and load, and two speed points at full load. A suitable flow control valve was installed down-stream of the turbocharger turbine to act as a power turbine and con-trolled by the real-time HIL system as explained in section 3. A variable geometry turbocharger (VGT) was used on the engine upstream of the back-pressure valve. A turbine with variable swallowing capacity allows the engine boost pressure, and hence the combustion air-to-fuel ratio, to be controlled with different back pressures caused by the gas ex-pansion through the power turbine. This enables optimisation work to be conducted by varying the power turbine size in the real-time power tur-bine model through parameters of turbine diameter and/or turbine hous-ing size. Moreover, to ensure a fair comparison between baseline architec-ture and a compounded system, it is important to make sure turbo ma-chinery used on both turbocharger and power turbine cases are optimised in terms of flow size and turbine efficiency. This is because the turbocharger turbine in turbocompound version needs to be smaller in size to achieve the same torque curve and air-handling requirements. This problem can be handled easily with VGT turbocharger by varying turbine flow size so that target engine operating conditions like engine torque, air-fuel ratio and EGR levels can be kept the same for both baseline and turbocompound test cases. The analytical power turbine model estimates the power turbine power contribution depending on the pressure and temperature boundary condi-tions measured upstream and downstream of the emulator valve. The predicted power turbine power is fed back to the engine control system so that fuelling can be appropriately modified to maintain total system power (reciprocator power plus power-turbine power) at the same level as a baseline engine. NOx and particulate emissions were measured using in-dustry standard emissions measurement systems. EGR levels were varied for a given engine-out NOx emission level, and the tests were conducted for the best possible system optimisation at test points. Figure 10 shows the test results at cruise speed condition where the en-gine is at approximately 40% of load. Total system power output and power turbine power contribution, EGR fraction and air-to-fuel ratio levels are shown against engine-out brake-specific NOx levels. The engine-open cycle and closed-cycle efficiency values are plotted in the same figure to characterise the power-turbine power recovery and pumping work bal-

ance. Brake thermal efficiency and associated BSFC results are also shown in the same figure. It can be seen that power turbine contribution is rela-tively small at 2 to 4g/kWh engine-out NOx solutions. It corresponds to EGR fractions nearly 25 to 30%. Under these conditions of high EGR, al-though closed-cycle efficiency is higher by a few points (~4 points), the net benefit is negated by pumping work as seen from lower open-cycle efficiency than baseline. This is translated into higher BSFC and lower brake thermal efficiency at low engine-out NOx solutions. At higher engine out NOx levels of 10 to 12g/kWh, EGR levels are low, and an approximate 5-point increase in closed-cycle efficiency can be seen from the same figure. However, pumping work is not as high as before with a 2g/kWh NOx solution, and hence nearly 2 to 3 points higher in brake thermal efficiency, which in turn presented as ~1 point improve-ment in BSFC. This is in close agreement with simulations showing that higher EGR levels will reduce the margin available for net positive power recovery.

Figure 10: Engine performance comparisons between turbocompound and baseline engine at cruise conditions.

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Turbocompound Engine

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Air to Fuel ratio vs BSNOx

Baseline Engine

Turbocompound Engine

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BSNOx (g/kW‐hr)

Turbo compound power vs BSNOx

Baseline Engine

Turbocompound Engine

Figure 10: Engine performance comparisons between turbocompound and baseline engine at cruise conditions. The engine test results of rated condition are plotted in Figure 11. Total system power output, turbocompound power contribution, EGR, air-to-fuel ratio, closed and open cycle engine efficiency and brake thermal efficiency with BSFC figures are given. In order to achieve 2g/kWh NOx solution EGR rates are about 25%. The power turbine contribution at rated condition is moderate, about 5% of reciprocator power. At low BSNOx solution (high EGR level conditions), the air-to-fuel ratio is a limiting factor with the TCPD system. In this case the air-to-fuel ratio was found close to 19. Closed-cycle efficiency is almost similar to baseline at rated condition, which means in-cylinder pressure characteristics are similar. However, open-cycle efficiency is about 2 points higher which means net power con-tribution is higher than its pumping loss. Hence brake thermal efficiency is better, and therefore 2 to 3% BSFC improvement is seen at rated condi-tions. These results are in good agreement with predicted results from GT-Power simulations presented in section 2.

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BSNOx (g/kW‐hr)

Closed cycle efficiency vs BSNOx 

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Turbocompound Engine0.95

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BSNOx (g/kW‐hr)

Open cycle efficiency vs BSNOx

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Brake thermal efficiency vs BSNOx

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Turbocompound Engine

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BSFC (g/kW‐hr)

BSNOx (g/kW‐hr)

BSFC vs BSNOx

Baseline Engine

Turbocompound Engine

Figure 11: Engine brake-specific fuel consumption comparison between turbocompound engine and baseline engine at rated condition.

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EGR Fraction vs BSNOx

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Total system power output vs BSNOx

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Turbocompound Engine

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Air to Fuel ratio vs BSNOx

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Turbocompound Engine

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Baseline Engine

Turbocompound Engine

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BSNOx (g/kW‐hr)

Closed cycle efficiency vs BSNOx 

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BSNOx (g/kW‐hr)

Open cycle efficiency vs BSNOx

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Turbocompound Engine

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0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0

Brake therm

al efficiency (%)

BSNOx (g/kW‐hr)

Brake thermal efficiency vs BSNOx

Baseline Engine

Turbocompound Engine

190.0

192.0

194.0

196.0

198.0

200.0

202.0

204.0

206.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0

BSFC (g/kW‐hr)

BSNOx (g/kW‐hr)

BSFC vs BSNOx

Baseline Engine

Turbocompound Engine

6 Conclusion GT-Power simulations were performed to evaluate the fuel economy po-tential of a TCPD system compared to an equivalent baseline heavy-duty diesel engine. Predictions showed about 5% benefit at B100 with 520HP TCPD engine at 0% EGR engine and 200mbar backpressure. However this benefit disappears for the same rating at about 20% EGR. If the engine has high EGR (~30%), high back pressure and low power density, turbo-compounding becomes less attractive as the balance of pumping-work in-crease is much higher than the net power recovered. TCPD engine development involves careful selection of the turbocharger turbine and power turbine size to optimise the overall system within the confined space of fuel economy, additional pumping work and the air flow targets. In this context a novel turbocharger emulation approach was de-veloped and applied in TCPD engine system development. A real-time power turbine model allows the engine back-pressure valve to act as a power turbine and can be controlled with a high level of stability and accu-racy for size variation. Finally, the turbocompound emulation system was tested on a heavy-duty engine. Test results are in good agreement with the simulation results showing 2 to 3% BSFC improvement at rated condi-tions for a 2g/kWh engine-out NOx solution. At cruise speed, net benefit is compensated by higher engine pumping work resulting in a marginal in-crease in BSFC at the same engine-out NOx levels of 2g/kWh. However, BSFC advantage of a TCPD system may vary depending on the engine, and is very specific to application duty cycle. Therefore careful evaluation of overall system potential is necessary.

Acknowledgement The authors would like to thank to Mr. T. Powell, and Mr. O.A. Ryder at Cummins Turbo Technologies for their contributions.

References [1] Tennant, D. W. H., Walsham, B. E., The turbocompound Diesel

engine (SAE Paper 890647, 1989)

[2] Ryder, O., Sharp, N.; The impact of future engine and vehicle drivetrains on turbocharging system architecture, IMechE turbocharging conference 2010,London.

[3] Zhang, K., Diesel Engine Emulation (PhD thesis, University of Bath, Bath, United Kindom) 2010

[4] Vuk, C.T., Electric turbo compounding, DEER conference, 2006. www1.eere.energy.gov/vehiclesandfuels/pdfs/deer_2006/session6/2006_deer_vuk.pdf

[5] Kruiswyk, R.W., Milam, D. M., Engine system approach to exhaust energy recovery, DEER conference, 2006.

[6] Subramanian, G., Jondhale, M., The latest trend of turbocharging technologies for emissions compliance and fuel economy, IMechE conference, 2011, Pune, India

[7] Zhang, K., Akehurst, S., Pennycott, A., & Hawley,J.G., Steady state emulation of a diesel engine air charge system through real-time turbocharger modelling. (IMechE, journal part d, Submitted)

[8] Akehurst, S and Piddock, M, A multiple factor simulation and emulation approach to investigate advanced air handling system for future diesel engines (SAE, 2008)