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Effect of Engine Start and Clutch Slip Losses on the Energy Management Problem of a Hybrid DCT Powertrain

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Abstract

A Dynamic Programming (DP) formulation is developed to find the global optimal solution to the energy management of a parallel Plug-in Hybrid Electric Vehicle (PHEV) equipped with a Dual-Clutch Transmission (DCT). The effects of integrating in the DP formulation the losses accounting for gearshifts and engine starts are studied in terms of the overall fuel consumption; the optimal control solutions obtained depends on the occurrence of these transient events. These sources of dissipation are modeled through physical considerations thus enabling the DP algorithm to decide when it is more convenient, in terms of minimizing the total energy consumption, to perform either a gearshift or an engine start. This capability differentiates the DP formulation here presented from those presented in previous studies.

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Abbreviations

a :

vehicle acceleration

A v :

vehicle cross section

c a :

aerodynamic drag coefficient

c r :

rolling resistance coefficient

E :

energy

f :

generic function

F a :

aerodynamic resistance

F g :

slope gradient resistance

F in :

inertia force

F r :

rolling resistance

g:

gravitational acceleration

GN :

gear number

GS :

gearshift

I :

current

J :

mass moment of inertia

M :

vehicle mass

ṁ f :

fuel consumption

L :

instantaneous cost function

r w :

wheel radius

P :

power

R :

electric resistance

Q :

electric charge

QD x :

quick disconnect clutch status

SOC :

state of charge

t :

time

T s :

time step

T :

torque

TSF :

torque split factor

u :

command

U :

commands domain

v :

vehicle speed

V :

voltage

W :

lost power

x :

state variable

X :

state variables domain

Y :

cost-to-go

α :

road grade angle

Δx :

range of state variables

ρ :

air density

η :

efficiency

Ψ :

performance index

τ :

transmission ratio

ω :

angular speed

ω̇ :

angular acceleration

B :

battery

BR :

mechanical brakes

EM :

electric motor

GB :

DCT gearbox

FD :

final drive

INV :

inverter

ICE :

internal combustion engine

c :

clutch

cd :

cold start

References

  • Amisano, F., Galvagno, E., Velardocchia, M. and Vigliani, A. (2014). Automated manual transmission with a torque gap filler Part 1: Kinematic analysis and dynamic analysis. Proc. Institution of Mechanical Engineers, Part D: J. Automobile Engineering228, 11, 1247–1261.

    Google Scholar 

  • Bellman, R. E. and Dreyfus, S. E. (2015). Applied Dynamic Programming. Princeton University Press. Princeton, New Jersey, USA.

    MATH  Google Scholar 

  • Bertsekas, D. (1995). Dynamic Programming and Optimal Control. Athena Scientific. Belmont, Massachusetts, USA.

    MATH  Google Scholar 

  • Bianchi, D., Rolando, L., Serrao, L., Onori, S., Rizzoni, G., Al-Khayat, N., Hsieh, T.-M., and Kang, P. (2010). A rulebased strategy for a series/parallel hybrid electric vehicle: An approach based on dynamic programming. Proc. ASME Dynamic Systems and Control Conf., Cambridge, Massachusetts, USA.

    Google Scholar 

  • Böhme, T. J. and Frank, B. (2017). Hybrid Systems, Optimal Control and Hybrid Vehicles: Theory, Methods and Applications. 1st edn. Springer. Cham, Switzerland.

    MATH  Google Scholar 

  • Bovee, K. M. (2015). Optimal Control of Electrified Powertrains with the Use of Drive Quality Criteria. Ph. D. Thesis. Ohio State University. Ohio, USA.

    Google Scholar 

  • Boyd, S. P. and Vendenberghe, L. (2004). Convex Optimization. Cambridge University Press. Cambridge, UK.

    Google Scholar 

  • Elbert, P., Nüesch, T., Ritter, A., Murgovski, N. and Guzzella, L. (2014). Engine on/off control for the energy management of a serial hybrid electric bus via convex optimization. IEEE Trans. Vehicular Technology63, 8, 3549–3559.

    Google Scholar 

  • Engbroks, L., Knappe, P., Goerke, D., Schmiedler, S., Goedecke, T. and Geringer, B. (2019). Energetic costs of ICE starts in (P)HEV–Experimental evaluation and its influence on optimization based energy management strategies. SAE Paper No. 2019-24-0203.

    Google Scholar 

  • Galvagno, E., Guercioni, G. R. and Vigliani, A. (2016). Sensitivity analysis of the design parameters of a dualclutch transmission focused on NVH performance. SAE Paper No. 2016-01-1127.

    Google Scholar 

  • Galvagno, E., Velardocchia, M. and Vigliani, A. (2011). Dynamic and kinematic model of a dual clutch transmission. Mechanism and Machine Theory46, 6, 794–805.

    MATH  Google Scholar 

  • Galvagno, E., Velardocchia, M. and Vigliani, A. (2018). Transient response and frequency domain analysis of an electrically variable transmission. Advances in Mechanical Engineering10, 5, 1–12.

    Google Scholar 

  • Gao, B., Lei, Y., Ge, A., Chen, H. and Sanada, K. (2011). Observer-based clutch disengagement control during gear shift process of automated manual transmission. Vehicle System Dynamics: Int. J. Vehicle Mechanics and Mobility49, 5, 685–701.

    Google Scholar 

  • Guercioni, G. R. and Vigliani, A. (2019). Gearshift control strategies for hybrid electric vehicles: A comparison of powertrains equipped with automated manual transmissions and dual-clutch transmissions. Proc. Institution of Mechanical Engineers, Part D: J. Automobile Engineering233, 11, 2761–2779.

    Google Scholar 

  • Guiggiani, M. (2014). The Science of Vehicle Dynamics: Handling, Braking, and Ride of Road and Race Cars. 1st edn. Springer. The Netherlands.

    Google Scholar 

  • Guzzella, L. and Amstutz, A. (1999). CAE tools for quasistatic modeling and optimization of hybrid powertrains. IEEE Trans. Vehicular Technology48, 6, 1762–1769.

    Google Scholar 

  • Guzzella, L. and Sciarretta, A. (2013). Vehicle Propulsion Systems: Introduction to Modeling and Optimization. 3rd edn. Spriger-Verlag Berlin Heidelberg. Heidelberg, Germany.

    Google Scholar 

  • Johannesson, L., Asbogard, M. and Egardt, B. (2007). Assessing the potential of predictive control for hybrid vehicle powertrains using stochastic dynamic programming. IEEE Trans. Intelligent Transportation Systems8, 1, 71–83.

    Google Scholar 

  • Khodabakhshian, M., Feng, L. and Wikander, J. (2013). Optimization of gear shifting and torque split for improved fuel efficiency and drivability of HEVs. SAE Paper No. 2013-01-1461.

    Google Scholar 

  • Kim, N. and Rousseau, A. (2012). Sufficient conditions of optimal control based on Pontryagin’s minimum principle for use in hybrid electric vehicles. Proc. Institution of Mechanical Engineers, Part D: J. Automobile Engineering226, 9, 1160–1170.

    Google Scholar 

  • Kim, N., Cha, S. and Peng, H. (2011). Optimal control of hybrid electric vehicles based on pontryagin’s minimum principle. IEEE Trans. Control Systems Technology19, 5, 1279–1287.

    Google Scholar 

  • Kirk, D. E. (1998). Optimal Control Theory–An Introduction. Dover Publications. San José, California, USA.

    Google Scholar 

  • Lin, C. C., Filipi, Z., Louca, L., Peng, H., Assanis, D. and Stein, J. (2004). Modelling and control of a mediumduty hybrid electric truck. Int. J. Heavy Vehicle Systems11, 3, 349–371.

    Google Scholar 

  • Lin, C. C., Peng, H., Grizzle, J. W. and Kang, J. M. (2003). Power management strategy for a parallel hybrid electric truck. IEEE Trans. Control Systems Technology11, 6, 839–849.

    Google Scholar 

  • Ngo, V. D., Hofman, T., Steinbuch, M. and Serrarens, A. (2012a). Effect of gear shift and engine start losses on control strategies for hybrid electric vehicles. Proc. 26th Electric Vehicle Symp. and Exposition, Los Angeles, California, USA.

    Google Scholar 

  • Ngo, V. D., Hofman, T., Steinbuch, M. and Serrarens, A. (2012b). Optimal control of the gearshift command for hybrid electric vehicles. IEEE Trans. Vehicular Technology61, 8, 3531–3543.

    Google Scholar 

  • Ngo, V. D., Navarrete, J. A. C., Hofman, T., Steinbuch, M. and Serrarens, A. (2013). Optimal gear shift strategies for fuel economy and driveability. Proc. Institution of Mechanical Engineers, Part D: J. Automobile Engineering227, 10, 1398–1413.

    Google Scholar 

  • Onori, S. and Tribioli, L. (2015). Adaptive pontryagin’s minimum principle supervisory controller design for the plug-in hybrid GM chevrolet volt. Applied Energy, 147, 224–234.

    Google Scholar 

  • Onori, S., Serrao, L. and Rizzoni, G. (2010). Adaptive equivalent consumption minimization strategy for hybrid electric vehicles. Proc. ASME Dynamic Systems and Control Conf., Cambridge, Massachusetts, USA.

    Google Scholar 

  • Onori, S., Serrao, L. and Rizzoni, G. (2016). Hybrid Electric Vehicles: Energy Management Strategies. 1st edn. Springer-Verlag London. London, UK.

    Google Scholar 

  • Opila, D. F., Wang, X., McGee, R. and Grizzle, J. W. (2012b). Real-time implementation and hardware testing of a hybrid vehicle energy management controller based on stochastic dynamic programming. J. Dynamic Systems, Measurement, and Control135, 2, 021002.

    Google Scholar 

  • Opila, D. F., Wang, X., McGee, R., Cook, J. A. and Grizzle, J. W. (2009). Performance comparison of hybrid vehicle energy management controllers on real-world drive cycle data. Proc. American Control Conf., St. Louis, Missouri, USA.

    Google Scholar 

  • Opila, D. F., Wang, X., McGee, R., Gillespie, R. B., Cook, J. A. and Grizzle, J. W. (2012a). An energy management controller to optimally trade off fuel economy and drivability for hybrid vehicles. IEEE Trans. Control Systems Technology20, 6, 1490–1505.

    Google Scholar 

  • Ostertag, E. (2011). Mono- and Multivariable Control and Estimation: Linear, Quadratic and LMI Methods. 1st edn. Spriger-Verlag Berlin Heidelberg. Heidelberg, Germany.

    MATH  Google Scholar 

  • Piccolo, A., Ippolito, L., Galdi, V. and Vaccaro, A. (2001). Optimisation of energy flow management in hybrid electric vehicles via genetic algorithms. Proc. IEEE/ASME Int. Conf. Advanced Intelligent Mechatronics, Como, Italy.

    MATH  Google Scholar 

  • Rizzoni, G., Guzzella, L. and Baumann, B. M. (1999). Unified modeling of hybrid electric vehicle drivetrains. IEEE/ASME Trans. Mechatronics4, 3, 246–257.

    Google Scholar 

  • Salmasi, F. R. (2007). Control strategies for hybrid electric vehicles: Evolution, classification, comparison, and future trends. IEEE Trans. Vehicular Technology56, 5, 2393–2404.

    Google Scholar 

  • Sciarretta, A., Back, M. and Guzzella, L. (2004). Optimal control of parallel hybrid electric vehicles. IEEE Trans. Control Systems Technology12, 3, 352–363.

    Google Scholar 

  • Serrao, L., Onori, S. and Rizzoni, G. (2011). A comparative analysis of energy management strategies for hybrid electric vehicles. J. Dynamic Systems, Measurement, and Control133, 3, 31012.

    Google Scholar 

  • Sundström, O. and Guzzella, L. (2009). A generic dynamic programming matlab function. Proc. IEEE Int. Conf. Control Applications, St. Petersburg, Russia.

    Google Scholar 

  • Tutuianu, M., Bonnel, P., Ciuffo, B., Haniu, T., Ichikawa, N., Marotta, A., Pavlovic, J. and Steven, H. (2015). Development of the world-wide harmonized light duty test cycle (WLTC) and a possible pathway for its introduction in the European legislation. Transportation Research Part D: Transport and Environment, 40, 61–75.

    Google Scholar 

  • Waschl, H., Kolmanovsky, I., Steinbuch, M. and del Re, L. (2014). Optimization and Optimal Control in Automotive Systems. 1st edn. Springer. London, UK.

    MATH  Google Scholar 

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Authors and Affiliations

  1. Dipartimento di Ingegneria Meccanica e Aerospaziale, Politecnico di Torino, Torino, 10129, Italy

    Enrico Galvagno, Guido Guercioni, Mauro Velardocchia & Alessandro Vigliani

  2. Department of Mechanical and Aerospace Engineering, Ohio State University, Ohio, OH, 43210, USA

    Giorgio Rizzoni

Authors
  1. Enrico Galvagno
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  2. Guido Guercioni
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  3. Giorgio Rizzoni
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  4. Mauro Velardocchia
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  5. Alessandro Vigliani
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Correspondence to Alessandro Vigliani.

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Galvagno, E., Guercioni, G., Rizzoni, G. et al. Effect of Engine Start and Clutch Slip Losses on the Energy Management Problem of a Hybrid DCT Powertrain. Int.J Automot. Technol. 21, 953–969 (2020). https://doi.org/10.1007/s12239-020-0091-y

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  • DOI: https://doi.org/10.1007/s12239-020-0091-y

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