Real-time control strategies for hybrid vehicles issued from optimization algorithm

International audienceThis paper focuses on a mild-hybrid city car (Smart), equipped with a starter-alternator, where the kinetic energy in the braking phases can be recovered to be stored in a supercapacitor, and re-used later via the electric motor. The additional traction power allows to downsize the engine and still fulfill the power requirements. Moreover, the engine can be turned off in idle phases. The optimal control problem of the energy management between the two power sources is solved for given driving cycles by a classical dynamic programming method. From dynamic models of the electric motor and supercapacitor a quasistatic model of the whole system is derived and used in the optimization. The real time control law to be implemented on the vehicle is derived from the resulting optimal control strategies

Optimal energy management of a mild-hybrid vehicle

International audienceThe paper presents the development of a supervisory controller for a mild-hybrid vehicle, a hybrid natural gas SMART, equipped with a starter alternator and supercapacitor manufactured by Valeo. This electric additional power can be used to stop and start quickly the engine and also to power the vehicle alongside with the engine. The electric motor can also be used to recharge the supercapacitor. After a description of the models developed for the electric motor dynamics, a dynamic programming algorithm is applied for the optimization of power split, based on these models. The resulting optimal power split is compared to a real-time control law. Among the available control laws, the choice of the Equivalent Consumption Minimization Strategy (ECMS) allows to keep the same models that have been used for dynamic programming algorithm. Moreover, some road tests show the resulting behavior of the powertrain, in terms of supercapacitor voltage, motor and engine torque and speed

Design Optimization and Optimal Control for Hybrid Vehicles

International audienceGrowing environmental and global crude oil supplies concerns are stimulating research on new vehicle technologies. Hybrid-electric vehicles appear to be one of the most promising technologies for reducing fuel consumption and pollutant emissions. Different types of hybrid-electric powertrains exist: from the mild-hybrid vehicle, equipped with a small electric motor, to the combined hybrid like the Toyota prius. This paper presents a parametric study focused on variations of the size of the powertrain components , and optimization of the power split between the engine and electric motor with respect to fuel consumption. To perform this optimization on a prescribed driving cycle (for instance, the New European Driving Cycle), a dynamic programming algorithm based on a reduced model is implemented. This simplified model allows a fast optimization with a fine parameterization of the controller: it furnishes the optimal power repartition at each time step regarding fuel consumption under constraints on the battery state of charge. The obtained results may be used to determine the best components of a given powertrain, for a prescribed vehicle cycle. The optimal split obtained thanks to dynamic programming algorithm can not be used directly on a vehicle as a real time control law, as the future can not be known in advance in normal driving conditions. To overcome this difficulty, we implement, as a real-time strategy, the Equivalent Consumption Minimization Strategy (ECMS): the battery being considered as an auxiliary reversible fuel reservoir, an instantaneous minimization of ECMS is performed. This control law is inferred from Pontryagin's Minimum Principle, where the Lagrange multiplier can be deduced from previous optimization results on given driving cycles. Offline optimization results and real-time control laws are compared for a realistic hybrid vehicle application. 2

Memory for symmetry and perceptual binding in patients with schizophrenia

The present study investigated the use of perceptual binding processes in schizophrenic (SC) patients and matched healthy controls, by examining their performance on the recall of symmetrical (vertical, horizontal and diagonal) and asymmetrical patterns varying in length between 2 and 9 items. The results showed that, although SC patients were less accurate than controls in all conditions, both groups recalled symmetrical patterns better than asymmetrical ones. The impairment of SC patients was magnified with supra-span symmetrical arrays, and they were more likely to reproduce symmetrical patterns as asymmetrical, particularly at medium and high length levels. Hierarchical regression analyses further indicated that the between-group differences in the recall of supra-span vertical and horizontal arrays, which require a greater involvement of visual pattern processes, remained significant after removing the variance associated with performance on asymmetrical patterns, which primarily reflects intrafigural spatial processes. It is proposed that schizophrenia may be associated with a specific deficit in the formation and retrieval of the global visual images of studied patterns and in the use of the on-line information about the type of symmetry being tested to guide retrieval processes. © 2013 Elsevier B.V