Control strategies for parallel hybrid vehicles

Optimisation-based control for electrified vehicles: challenges and opportunities

“…The heuristic supervisory control is often based on the load-levelling concept (Jalil, Kheir, & Salman, 1997;Rahman, Butler, & Ehsani, 2000), namely operating the engine at its efficient region while using the battery for leverage. Other rule-based PMS use heuristic rules, fuzzy logic or neural networks (He, Parten, & Maxwell, 2005;Salman, Schouten, & Kheir, 2000) for estimation and control implementation. While those strategies are simple and computationally efficient, their design totally relies on the engineering judgment and experience of the designers.…”

A control benchmark on the energy management of a plug-in hybrid electric vehicle

“…Energy management of hybrid electric vehicles (HEV) is nowadays a more-than-ten-years-old field of research in control engineering (Baumann, Rizzoni, & Washington, 1998;Brahma, Guezennec, & Rizzoni, 2000;Hofman, Ebbesen, & Guzzella, 2012;Kleimaier & Schroder, 2002;Koot et al, 2005;Lin, Kang, Grizzle, & Peng, 2001;Paganelli et al, 2000;Salman, Schouten, & Kheir, 2000;Sciarretta, Back, & Guzzella, 2004;. Indeed, energy management is a control task since it consists in determining the setpoints (mostly, torque) to the various power converters (internal combustion engine, electric machines with their power electronics, mechanical transmission devices, electrical power converters, etc.)…”

“…In particular, charge-sustaining or autonomous HEV implies that the battery State Of Charge (SOC) at the end of a vehicle mission is required to be as close as possible to its initial value. A mathematical formulation of such a control problem has been posed in terms of optimal control (Ambühl et al, 2007;Hofman, Steinbuch, Serrarens, & van Druten, 2008;Kim, Cha, & Peng, 2011;Serrao, Onori, & Rizzoni, 2009;van Berkel, Hofman, Vroemen, & Steinbuch, 2012) and numerous practical implementations for various architectures such as parallel (Lin et al, 2001;Musardo & Rizzoni, 2005;Pisu & Rizzoni, 2007;Salman et al, 2000;Sciarretta et al, 2004;Sivertsson, Sundström, & Eriksson, 2011), series (Anatone, Cipollone, Donati, & Sciarretta, 2005;Pisu & Rizzoni, 2005), and combined HEV (Borhan & Vahidi, 2010;Cipollone & Sciarretta, 2006;Hofman et al, 2008;Liu & Peng, 2006) have been presented.…”

Energy Management and Drivability Control Problems for Hybrid Electric Vehicles

“…The global minimization problem represented in (1) and the local minimization shown in (2) are not strictly equivalent. However, local minimization results in a formulation amenable to real-time control, while the use of the equivalent fuel flow rate indirectly accounts for the non-local nature of the problem.…”

“…In particular, they can be classified in three groups: dynamic programming approaches as in [1], intelligent control techniques such as rule based, fuzzy logic [2] and neural networks [3], and methods based on the conversion of the electric power into equivalent fuel consumption [4], [5]. Unfortunately, these approaches have some major drawbacks like the necessity to know the driving cycle a priori and the difficulty in finding an analytical expression for the controller [1]- [3].…”