This paper presents analyses and estimation of optimal control strategies of the parallel Hybrid Electric Vehicles (HEV) from the perspective of fuel economy and maximum energy regeneration during an active braking process. In the paper, there are four main control strategies of Continuously Variable Transmission (CVT) during a regenerative braking process depicted and discussed in detail. The four strategies are: 1) Control strategy of maximal use of regenerative braking. 2) Control strategy of CVT during to support workload of electrical motor according to maximal efficiency characteristics. 3) Control strategy of the CVT for maximal regenerative of energy of braking process per braking distance unit or braking time unit. 4) Discrete control strategy of the CVT with direct combinatorial applications of genetic algorithms and elements of fuzzy logic in control unit of the HEV. In all depicted control strategies, data of the HEV's drive system components, such as, electric motor, internal combustion engine, energy storage, transmission-CVT, are obtained from database of the software package ADVISOR ® of National Renewable Energy Laboratory (NREL).Index Terms -hybrid vehicle, optimal control strategies, fuzzy logic, genetic algorithms, regenerative process.

Small capacity and passively cooled battery packs are widely used in mild hybrid electric vehicles (MHEV). In this regard, continuous usage of electric traction could cause thermal runaway of the battery, reducing its life and increasing the risk of fire incidence. Hence, thermal limitations on the battery could be implemented in a supervisory controller to avoid such risks. A vast literature on the topic shows that the problem of battery thermal runaway is solved by applying active cooling or by implementing penalty factors on electric energy utilization for large capacity battery packs. However, they do not address the problem in the case of passive cooled, small capacity battery packs. In this paper, an experimentally validated electro-thermal model of the battery pack is integrated with the hybrid electric vehicle simulator. A supervisory controller using the equivalent consumption minimization strategy with, and without, consideration of thermal limitations are discussed. The results of a simulation of an MHEV with a 0.9 kWh battery pack showed that the thermal limitations of the battery pack caused a 2–3% fuel consumption increase compared to the case without such limitations; however, the limitations led to battery temperatures as high as 180 °C. The same simulation showed that the adoption of a 1.8 kWh battery pack led to a fuel consumption reduction of 8–13% without thermal implications.

In the general context of vehicles' fuel consumption and emissions reduction, the minimization of the aerodynamic drag can offer not negligible benefits regarding the environmental issues. The adjustment of the vehicle height is one of the possible ways to provide a reduction of the resistances to vehicle motion, in addition to consequent aspects regarding the increased versatility of the vehicle. The aim of this paper is to present in a systematic way to the state of the art of height adjustment systems for passenger vehicles, summarizing the main modes of operations, working principles and architectures. Particular attention is then given to electromechanical systems, which represent the next trends for future vehicles due to their high reliability and relatively low costs. A design methodology for electromechanical height adjustment systems with the purpose of optimizing their performance is presented. Such procedure is able to reach the most efficient working point even in presence of constraints of different nature. Prototypes have been designed, produced and tested to demonstrate the potentialities of electromechanical height adjustment systems. Furthermore, potential benefits and drawbacks of using such systems are highlighted.

This paper presents a comparison between a Fuzzy Logic and an Equivalent Consumption Minimization Strategy for the energy management of a Hybrid Electric Vehicle in P2 configuration, i.e. with the secondary energy converter located downstream the clutch. The design of the two methods is conducted aiming to minimize the fuel consumption. Although the adopted strategies are not charge sustaining, an additional goal of the techniques is to obtain a net energy extracted from the battery over a driving cycle that is not far from zero. The presented simulation results are obtained in the case of two homologation driving cycles, namely NEDC and WLTP. The objective of the study is to demonstrate that a non-optimal rule-based method can achieve a performance that is equivalent to a model-based optimal analytical approach.