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Abstract

This chapter reviews recent advances in HEV and PHEV research, spanning Trip Planning algorithms, EMS strategies, and cruise control techniques. It also investigates approaches to improve control system efficiency. The chapter concludes with a summary of the relevant literature and an overview of the significant contributions of the designed energy-optimal control system.

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References

  1. Shen L., Huang, M.: Assessing dynamic neural networks for travel time prediction. In: Applied Informatics and Communication International Conference, pp. 469–477 (2011)

    Google Scholar 

  2. Park, B., Malakorn, K., Lee, J.: Quantifying benefits of cooperative adaptive cruise control toward sustainable transportation system. Technical Report. May, Center for Transportation Studies, University of Virginia, Charlottesville, VA (2011)

    Google Scholar 

  3. Park, J., Chen, Z., Kiliaris, L., Kuang, M., Masrur, M., Phillips, A., Murphey, Y.: Intelligent vehicle power control based on machine learning of optimal control parameters and prediction of road type and traffic congestion. IEEE Trans. Veh. Technol. 58, 4741–4756 (2009)

    Article  Google Scholar 

  4. Keulen, T.V., Jager, B.D., Foster, D., Steinbuch, M.: Velocity trajectory optimization in hybrid electric trucks. In: American Control Conference, pp. 5074–5079 (2010)

    Google Scholar 

  5. Keulen, T.V., Jager, B.D., Steinbuch, M.: Optimal trajectories for vehicles with energy recovery options. In: 18th IFAC World Congress Milano, pp. 3831–3836 (2011)

    Google Scholar 

  6. Keulen, T.V., Naus, G., Jager, B.D., Molengraft, V., Steinbuch, M., Aneke, E.: Predictive cruise control in hybrid electric vehicles. World Electr. Veh. J. 3, 1–11 (2009)

    Article  Google Scholar 

  7. Keulen, T.V., Jager, B.D., Serrarens, A., Steinbuch, M.: Optimal energy management in hybrid electric trucks using route information. Oil Gas Sci. Technol. 65, 103–113 (2010)

    Article  Google Scholar 

  8. Gong, Q., Li, Y., Peng, Z.: Trip-based optimal power management of plug-in hybrid electric vehicles. IEEE Trans. Veh. Technol. 57, 3393–3401 (2008)

    Article  Google Scholar 

  9. Gong, Q., Li, Y., Peng, Z.: Optimal power management of plug-in HEV with intelligent transportation system. In: IEEE/ASME International Conference on Advanced Intelligent Mechatronics, pp. 1–6 (2007)

    Google Scholar 

  10. Gong, Q., Tulpule, P., Marano, V., Rizzoni, G.: The role of ITS in PHEV performance improvement. In: American Control Conference, pp. 2119–2124 (2011)

    Google Scholar 

  11. Bin, Y., Li, Y., Gong, Q.: Multi-information integrated trip specific optimal power management for plug-in hybrid electric vehicles. In: American Control Conference, pp. 4607–4612 (2009)

    Google Scholar 

  12. Katsargyri, G., Kolmanovsky, I., Michelini, J., Kuang, M., Phillips, A., Rinehart, M., Dahleh, M.: Path dependent receding horizon control policies for hybrid electric vehicles. In: American Control Conference, pp. 4613–4617 (2009)

    Google Scholar 

  13. Katsargyri, G.: Optimally controlling hybrid electric vehicles using path forecasting. Master of Science, Massachusetts Institute Of Technology (2008)

    Google Scholar 

  14. Rousseau, A., Pagerit, S., Gao, D.: Plug-in hybrid electric vehicle control strategy parameter optimization. J. Asian Electr. Veh. 6, 1125–1133 (2008)

    Article  Google Scholar 

  15. Lin, C., Jeon, S., Peng, H., Moo Lee, J., Moo, J.: Driving pattern recognition for control of hybrid electric trucks. Veh. Syst. Dyn. Int. J. Veh. Mech. Mobility 42, 41–58 (2004)

    Article  Google Scholar 

  16. Bashash, S., Arbor, A., Moura, S.J.: Battery health-conscious plug-in hybrid electric vehicle grid demand prediction. In: ASME 2010 Dynamic Systems and Control Conference, pp. 1–9 (2010)

    Google Scholar 

  17. Moura, S.J., Stein, J.L., Fathy, H.K.: Battery-health conscious power management in plug-in hybrid electric vehicles via electrochemical modeling and stochastic control. IEEE Trans. Control Syst. Technol. 1(3), 1–16 (2013)

    Google Scholar 

  18. Moura, S.J., Fathy, H., Callaway, D., Stein, J.: A stochastic optimal control approach for power management in plug-in hybrid electric vehicles. IEEE Trans. Control Syst. Technol. 19, 545–555 (2011)

    Article  Google Scholar 

  19. Murphey, Y.: Intelligent vehicle power management: an overview. Comput. Intell. Automot. Appl. SE 10(190), 169–190 (2008)

    Google Scholar 

  20. Manzie, C., Watson, H., Halgamuge, S.: Fuel economy improvements for urban driving: Hybrid versus intelligent vehicles. Transp. Res. Part C Emerg. Technol. 15, 1–16 (2007)

    Article  Google Scholar 

  21. Kim, T.C, Manzie, C., Sharma, R.: Two-stage optimal control of a parallel hybrid vehicle with traffic preview. In: The 18th IFAC World Congress, vol. 2, pp. 2115–2120 (2011)

    Article  Google Scholar 

  22. Bartholomaeus, R., Klingner, M., Lehnert, M.: Prediction of power demand for hybrid vehicles operating in fixed-route service. In: Proceedings of the 17th IFAC World Congress, pp. 5640–5645 (2008)

    Article  Google Scholar 

  23. Ichikawa, S., Yokoi, Y., Doki, S., Okuma, S., Naitou, T., Shiimado, T., Miki, N.: Novel energy management system for hybrid electric vehicles utilizing car navigation over a commuting route. In: Proceedings of the 2004 IEEE Intelligent Vehicles Symposium, pp. 161–166 (2004)

    Google Scholar 

  24. Gonder, J., Markel, T., Simpson, A., Thornton, M.: Using GPS travel data to assess the real world driving energy use of plug-in hybrid electric vehicles (PHEVs). Transp. Res. Rec. 2017, 26–32 (2007)

    Article  Google Scholar 

  25. Gonder, J.: Route-Based Control of Hybrid Electric Vehicles. In: SAE SP, vol. 2199 (2008)

    Google Scholar 

  26. Serrao, L., Onori, S., Rizzoni, G.: A comparative analysis of energy management strategies for hybrid electric vehicles. J. Dyn. Syst. Meas. Control 133 (2011)

    Article  Google Scholar 

  27. Lin, C., Peng, H., Grizzle, J., Liu, J., Busdiecker, M.: Control system development for an advanced-technology medium-duty hybrid electric truck. In: SAE paper, vol. 20 (2003)

    Google Scholar 

  28. Lin, C., Peng, H., Grizzle, J.: Power management strategy for a parallel hybrid electric truck. IEEE Trans. Control Syst. Technol. 11, 839–849 (2003)

    Article  Google Scholar 

  29. Gonder, J., Markel, T.: Energy management strategies for plug-in hybrid electric vehicles. Energy 1 (2007)

    Google Scholar 

  30. O’Keefe, M., Markel, T.: Dynamic programming applied to investigate energy management strategies for a plug-in HEV. Technical Report, National Renewable Energy Laboratory (2006)

    Google Scholar 

  31. Razavian, R.S.: Design and hardware-in-the-loop testing of optimal controllers for hybrid electric powertrains. Ph.D. thesis, University of Waterloo (2012)

    Google Scholar 

  32. Razavian, R.S., Taghavipour, A., Azad, N.L., McPhee, J.: Design and evaluation of a real-time fuel-optimal control system for series hybrid electric vehicles. Int. J. Electr. Hybrid Veh. 4, 260–288 (2012)

    Article  Google Scholar 

  33. Ebbesen, S., Elbert, P., Guzzella, L.: Battery state-of-health perceptive energy management for hybrid electric vehicles. IEEE Trans. Veh. Technol. 16, 2893–2900 (2012)

    Article  Google Scholar 

  34. Re, L., Ortner, P., Alberer, D.: Chances and challenges in automotive predictive control, 1–22 (2010)

    Google Scholar 

  35. Wang, L.: Model Predictive Control System Design and Implementation Using MATLAB. Springer (2009)

    Google Scholar 

  36. Kim, T.S., Manzie, C., Sharma, R.: Model predictive control of velocity and torque split in a parallel hybrid vehicle. In: IEEE International Conference on Systems, Man and Cybernetics, pp. 2014–2019 (2009)

    Google Scholar 

  37. Borhan, H., Vahidi, A., Phillips, A.M., Kolmanovsky, I.: Predictive energy management of a power-split hybrid electric vehicle. In: American Control Conference, pp. 3970–3976 (2009)

    Google Scholar 

  38. Borhan, H., Vahidi, A., Phillips, A.M., Kuang, M.L., Kolmanovsky, I.V., Di Cairano, S.: MPC-based energy management of a power-split hybrid electric vehicle. IEEE Trans. Control Syst. Technol. 20, 593–603 (2012)

    Article  Google Scholar 

  39. Taghavipour, A., Azad, N.L., McPhee, J.: An optimal power management strategy for power split plug-in hybrid electric vehicles. Int. J. Veh. Des. 60, 286–304 (2012)

    Article  Google Scholar 

  40. Taghavipour, A., Masoudi, R., Azad, N.L., McPhee, J.: High-fidelity modeling of a power-split plug-in hybrid electric powertrain for control performance evaluation. In: ASME: International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 1–9 Aug 2013 (2013)

    Google Scholar 

  41. Kouramasa, K.I., Panosa, C.: Fascab, N.P., Pistikopoulos, E.N.: An algorithm for robust explicit/multi-parametric model predictive control. Automatica 49, 381–389 (2013)

    Article  MathSciNet  Google Scholar 

  42. Lee, J.: Model predictive control: review of the three decades of development. Int. J. Control Autom. Syst. 9, 415–424 (2011)

    Article  Google Scholar 

  43. Alessio, A., Bemporad, A.: A survey on explicit model predictive control. Lecture Notes in Control and Information Sciences, vol. 384, pp. 345–369 (2009)

    Google Scholar 

  44. Bemporad, A., Morari, M., Dua, V., Pistikopoulos, E.N.: The explicit linear quadratic regulator for constrained systems. Automatica 38, 3–20 (2002)

    Article  MathSciNet  Google Scholar 

  45. Di Cairano, S., Bemporad, A., Kolmanovsky, I., Hrovat, D.: Model predictive control of magnetically actuated mass spring dampers for automotive applications. Int. J. Control 80, 1701–1716 (2000)

    Article  MathSciNet  Google Scholar 

  46. Bemporad, A.: Model-based predictive control design: New trends and tools. In: 45th IEEE Conference on Decision and Control (CDC), pp. 6678–6683 (2006)

    Google Scholar 

  47. Borrelli, F., Bemporad, A., Fodor, M., Hrovat, D.: A hybrid approach to traction control. In: Di Benedetto, M.D., Sangiovanni-Vincentelli, A.L. (eds.) In: HSCC 2001. Lecture Notes in Computer Science, vol. 2034, pp. 162–174 (2001)

    Chapter  Google Scholar 

  48. Borrelli, F., Bemporad, A., Fodor, M., Hrovat, D.: An mpc/hybrid system approach to traction control. IEEE Trans. Control Syst. Technol. 14, 541–552 (2006)

    Article  Google Scholar 

  49. Nausa, G., Ploegb, J., Van de Molengrafta, M., Heemelsa, W., Steinbuch, M.: Design and implementation of parameterized adaptive cruise control: an explicit model predictive control approach. Control Eng. Pract. 18, 882–892 (2000)

    Article  Google Scholar 

  50. Stewart, G., Borrelli, F.: A model predictive control framework for industrial turbodiesel engine control. In: 48th IEEE Conference on Decision and Control (CDC), pp. 5704–5711 (2008)

    Google Scholar 

  51. Widd, A., Hsien-Hsin, L., Gerdesand, J., Tunestal, P., Johansson, R.: Highspeed on-line MPC based on a fast gradient method applied to power converter control. In: American Control Conference (ACC), pp. 420–425 (2011)

    Google Scholar 

  52. Di Cairano, S., Liang, W., Kolmanovsky, I.V., Kuang, M.L., Phillips, A.M.: Engine power smoothing energy management strategy for a series hybrid electric vehicle. In: American Control Conference (ACC), pp. 2101–2106 (2011)

    Google Scholar 

  53. Andersen, H., Kummel, M.: Evaluating estimation of gain directionality parts 1: methodology and 2: a case study of binary distillation. J. Process Control 2, 59–86 (1992)

    Article  Google Scholar 

  54. Jacobsen, E., Skogestad, S.: Inconsistencies in dynamic models for ill-conditioned plants application to low-order models of distillation columns. Ind. Eng. Chem. Res. 33, 631–640 (1994)

    Article  Google Scholar 

  55. Koung, C., MacGregor, J.: Design of identification experiments for robust control: a geometric approach for bivariate processes. Ind. Eng. Chem. Res. 32, 1658–1666 (1993)

    Article  Google Scholar 

  56. Lee, H., Rivera, D.E.: An integrated input signal design and control-relevant parameter estimation approach for highly interactive multivariable systems. In: American Control Conference (ACC) (2006)

    Google Scholar 

  57. Rivera, D.E., Morari, M.: Control-relevant model reduction problems for siso \(h_2\), \(h_{\infty }\), and \(\mu \)-controller synthesis. Int. J. Control 46, 505–527 (1987)

    Article  Google Scholar 

  58. Rivera, D.E., Morari, M.: Plant and controller reduction problems for closed-loop performance. In: 27th IEEE Conference on Decision and Control (CDC), pp. 1143–1148 (1988)

    Google Scholar 

  59. Rivera, D.E., Webb, C., Morari, M.: A control-relevant identification methodology. In: Annual AIChE Meeting (1987)

    Google Scholar 

  60. Schrama, R.: Approximate identification and control design with application to a mechanical system. Ph.D. dissertation, Delft University of Technology (1992)

    Google Scholar 

  61. Zang, Z., Bitmead, R., Gevers, M.: \(h_2\) iterative model refinement and control robustness enhancement. In: 30th IEEE Conference on Decision and Control (CDC), pp. 279– 284 (1991)

    Google Scholar 

  62. Hakvoort, R.G., Schrama, R., Van den Hof, P.: Approximate identification with closed-loop performance criterion and application to LQG feedback design. Automatica 30, 679–690 (1994)

    Article  MathSciNet  Google Scholar 

  63. Hjalmarsson, H., Gevers, M., Gunnarsson, S., Lequin, O.: Iterative feedback tuningtheory and applications. IEEE Control Syst. Mag. 18, 26–41 (1998)

    Google Scholar 

  64. de Callafon, R.A., Van den Hof, P., Steinbuch, M.: Control relevant identification of a compact disc pick-up mechanism. In: 32nd IEEE Conference on Decision and Control (CDC), pp. 2050–2055 (1993)

    Google Scholar 

  65. Partanen, A.G., Bitmead, R.R.: The application of an iterative identification and controller design to a sugar cane crushing mill. Automatica 31, 1547–1563 (1995)

    Article  MathSciNet  Google Scholar 

  66. Zang, Z., Bitmead, R., Gevers, M.: Iterative weighted least-squares identification and weighted LQG control design. Automatica 31, 15771594 (1995)

    Article  MathSciNet  Google Scholar 

  67. Michelberger, P., Bokor, J., Palkovics, L., Nandori, E., Gaspar, P.: Iterative identification and control design for uncertain parameter suspension system. In: IFAC Transportation Systems. Preprints of the 8th IFAC/IFIP/IFORS Symposium, vol. 2, pp. 464–469 (1997)

    Article  Google Scholar 

  68. Jun, K.S., Rivera, D.E., Elisante, E., Sater, V.E.: A computer-aided design tool for robustness analysis and control-relevant identification of horizon predictive control with application to a binary distillation column. J. Process Control 6, 177–186 (1996)

    Article  Google Scholar 

  69. Verboven, P., Guillaume, P., Cauberghe, B.: Multivariable frequencyresponse curve fitting with application to modal parameter estimation. Automatica 41, 1773–1782 (2005)

    Article  MathSciNet  Google Scholar 

  70. Liu, J., Peng, H.: Control optimization for a power-split hybrid vehicle. In: American Control Conference (2006)

    Google Scholar 

  71. Liu, J., Peng, H.: Modeling and control of a power-split hybrid vehicle. IEEE Trans. Control Syst. Technol. 16, 1242–1251 (2008)

    Article  Google Scholar 

  72. Serrao, L., Rizzoni, G.: Optimal control of power split for a hybrid electric refuse vehicle. In: American Control Conference, pp. 4498–4503 (2008)

    Google Scholar 

  73. Pisu, P., Rizzoni, G.: A comparative study of supervisory control strategies for hybrid electric vehicles. IEEE Trans. Control Syst. Technol. 15, 506–518 (2007)

    Article  Google Scholar 

  74. Paganelli, G., Guerra, T.M., Delprat, S., Santin, J., Delhom, M., Combes, E.: Simulation and assessment of power control strategies for a parallel hybrid car. Proc. Inst. Mech. Eng. Part D J. Autom. Eng. 214, 705–717 (2000)

    Article  Google Scholar 

  75. Paganelli, G., Delprat, S., Guerra, T.M., Rimaux, J., Santin, J.: Equivalent consumption minimization strategy for parallel hybrid powertrains. In: IEEE 55th Vehicular Technology Conference, vol. 4, pp. 2076–2081 (2002)

    Google Scholar 

  76. Sezer, V., Gokasan, M., Bogosyan, S.: A novel ECMS and combined cost map approach for high-efficiency series hybrid electric vehicles. IEEE Trans. Veh. Technol. 60, 3557–3570 (2011)

    Article  Google Scholar 

  77. Shan, M.: Modeling and control strategy for series hydraulic hybrid vehicles. Doctor of Philosophy, The University of Toledo (2009)

    Google Scholar 

  78. Zhang, C., Vahidi, A., Pisu, P., Tennant, K.: Role of terrain preview in energy management of hybrid electric vehicles. IEEE Trans. Veh. Technol. 59, 1139–1147 (2010)

    Article  Google Scholar 

  79. Zhang, C., Vahidi, A.: Route preview in energy management of plug-in hybrid vehicles. IEEE Trans. Control Syst. Technol. 20, 546–553 (2012)

    Article  Google Scholar 

  80. Tulpule, P., Marano, V., Rizzoni, G.: Effects of different PHEV control strategies on vehicle performance. In: American Control Conference, pp. 3950–3955 (2009)

    Google Scholar 

  81. Musardo, C., Rizzoni, G., Staccia, B.: A-ECMS: an adaptive algorithm for hybrid electric vehicle energy management. Eur. J. Control, 509–524 (2005)

    Article  MathSciNet  Google Scholar 

  82. He, Y., Chowdhury, M., Pisu, P., Ma, Y.: An energy optimization strategy for power-split drivetrain plug-in hybrid electric vehicles. Transp. Res. Part C Emerg. Technol. 22, 29–41 (2012)

    Article  Google Scholar 

  83. Wollaeger, J., Rizzoni, G.: ITS in energy management systems of PHEV’s. Master of Science, Ohio State University (2012)

    Google Scholar 

  84. Stockar,S., Marano, V., Rizzoni, G., Guzzella, L.: Optimal control for plug-in hybrid electric vehicle applications. In: American Control Conference, pp. 5024–5030 (2010)

    Google Scholar 

  85. Stockar, S., Marano, V., Canova, M., Rizzoni, G., Guzzella, L.: Energy-optimal control of plug-in hybrid electric vehicles for real-world driving cycles. IEEE Trans. Veh. Technol. 60, 2949–2962 (2011)

    Article  Google Scholar 

  86. Global status report on road safety: time for action. World Health Organization (2009)

    Google Scholar 

  87. Xiao, L., Gao, F.: A comprehensive review of the development of adaptive cruise control systems. Veh. Syst. Dyn. 48, 1167–1192 (2010)

    Article  Google Scholar 

  88. Bengtsson, J.: Adaptive cruise control and driver modeling. No. November, Department of Automatic Control, Lund Institute of Technology (2001)

    Google Scholar 

  89. Lu, X., Hedrick, K., Drew, M.: ACC/CACC—control design, stability and robust performance. In: American Control Conference, pp. 4327–4332 (2002)

    Google Scholar 

  90. Liang, C., Peng, H.: Optimal adaptive cruise control with guaranteed string stability. Veh. Syst. Dyn. 32, 37–41 (1999)

    Article  Google Scholar 

  91. Corona, D., Schutter, B.D.: Comparison of a linear and a hybrid adaptive cruise controller for a SMART. In: 46th IEEE Conference on Decision and Control, pp. 4779–4784 (2007)

    Google Scholar 

  92. Ferrara, A., Vecchio, C.: Second order sliding mode control of vehicles with distributed collision avoidance capabilities, 19, 471–477 (2009)

    Google Scholar 

  93. Moon, S., Moon, I., Yi, K.: Design, tuning, and evaluation of a full-range adaptive cruise control system with collision avoidance. Control Eng. Pract. 17, 442–455 (2009)

    Article  Google Scholar 

  94. Huang, W.: Design and evaluation of a 3D road geometry based heavy truck fuel optimization system. Doctor of Philosophy, Auburn University (2010)

    Google Scholar 

  95. Hellstrom, E., Ivarsson, M., Aslund, J., Nielsen, L.: Look-ahead control for heavy trucks to minimize trip time and fuel consumption. Control Eng. Pract. 17, 245–254 (2009)

    Article  Google Scholar 

  96. Zhuan, X., Xia, X.: Speed regulation with measured output feedback in the control of heavy haul trains. Automatica 44, 242–247 (2008)

    Article  MathSciNet  Google Scholar 

  97. Luo, L., Liu, H., Li, P., Wang, H.: Model predictive control for adaptive cruise control with multi-objectives: comfort, fuel-economy, safety and car-following. J. Z. Univ. Sci. A 11, 191–201 (2010)

    Article  Google Scholar 

  98. Asadi, B., Vahidi, A.: Predictive cruise control: utilizing upcoming traffic signal information for improving fuel economy and reducing trip time. IEEE Trans. Control Syst. Technol. 19, 707–714 (2011)

    Article  Google Scholar 

  99. Shakouri, P., Ordys, A.: Nonlinear model predictive control approach in design of adaptive cruise control with automated switching to cruise control. Control Eng. Pract. 26, 160–177 (2014)

    Article  Google Scholar 

  100. Li, S., Li, K., Rajamani, R., Wang, J.: Model predictive multi-objective vehicular adaptive cruise control. IEEE Trans. Control Syst. Technol. 19, 556–566 (2011)

    Article  Google Scholar 

  101. Kamal, M., Mukai, M., Murata, J., Kawabe, T.: Ecological vehicle control on roads with up-down slopes. IEEE Trans. Intell. Transp. Syst. 12, 783–794 (2011)

    Article  Google Scholar 

  102. Wang, M., Daamen, W., Hoogendoorn, S., van Arem, B.: Driver assistance systems modeling by model predictive control. In: 15th International IEEE Conference on Intelligent Transportation Systems, pp. 1543–1548 (2012)

    Google Scholar 

  103. Groot, N., Schutter, B.D., Hellendoorn, H.: Integrated model predictive traffic and emission control using a piecewise-affine approach. IEEE Trans. Intell. Transp. Syst. 14, 587–598 (2013)

    Article  Google Scholar 

  104. Groot, N., Schutter, B.D., Xi, Y., Hellendoorn, H.: Integrated urban traffic control for the reduction of travel delays and emissions. IEEE Trans. Intell. Transp. Syst. 14, 1609–1619 (2013)

    Article  Google Scholar 

  105. Kamal, M., Imura, J., Hayakawa, T., Ohata, A., Aihara, K.: Smart driving of a vehicle using model predictive control for improving traffic flow. IEEE Trans. Intell. Transp. Syst. 15, 878–888 (2014)

    Article  Google Scholar 

  106. Kamal, M., Mukai, M., Murata, J., Kawabe, T.: Model predictive control of vehicles on urban roads for improved fuel economy. IEEE Trans. Control Syst. Technol. 21, 831–841 (2013)

    Article  Google Scholar 

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Taghavipour, A., Vajedi, M., Azad, N.L. (2019). Related Work. In: Intelligent Control of Connected Plug-in Hybrid Electric Vehicles. Advances in Industrial Control. Springer, Cham. https://doi.org/10.1007/978-3-030-00314-2_2

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