With ever increasing concern on oil prices and energy conservation, there is a fast growing interest in hybrid vehicles globally. Currently, all hybrid vehicles, including micro, mild and full hybrids, adopt internal combustion engines which are inefficient in general. The corresponding waste heat of exhaust gas constitutes up to 40% of the fuel consumption. So, it is a pressing need for researchers to develop viable energy-efficient technology to recover the waste energy of exhaust gas for hybrid vehicles. In this paper, an overview of thermoelectric waste-heat energy recovery for hybrid vehicles is presented, with emphasis on the system configuration, heat exchanger, thermoelectric material, power converter and maximum power point tracking.

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Plug-in Hybrid Electric Vehicles (PHEVs) offer a great opportunity to significantly reduce petroleum consumption. The fuel economy of PHEV is highly dependent on All-Electric-Range (AER) and control strategy. Previous studies have shown that in addition to parameters influencing Hybrid Electric Vehicles (HEVs), control strategies of PHEVs are also influenced by the trip distance. This additional parameter makes it even more difficult to manually tune the parameters that minimize fuel consumption. This study uses a pre-transmission parallel PHEV model developed with the Powertrain System Analysis Toolkit (PSAT). A non-derivative based algorithm called DIRECT (for DIvided RECTangles) is used to optimize the main control strategy parameters. The fuel economy and main performance criteria of the PHEVs are compared for the initial design and final optimal design. An optimal control solution resulting from an extensive search of the entire design space can provide physical insight into the PHEV operation.

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Auto rickshaws are small, three-wheeled vehicles which are used extensively in many Asian countries for transport of people and goods. The vehicles are small and narrow allowing for easy maneuverability in congested Asian metropolises. In India, auto rickshaws are commonly used as taxis, as they are very inexpensive to operate. Despite the apparent advantages in the vehicle design, auto rickshaws present a huge pollution problem in major Indian cities. This is due to the use of an inefficient engine, typically a 2 or 4 stroke, with almost no pollution control. This paper presents a transportation system based on auto rickshaws that operate in an environmentally friendly way. Existing vehicles are to be replaced by an all-electric counterpart redesigned in a manner which improves the efficiency of the vehicle. In addition, a recharging infrastructure is proposed which will allow for the batteries to be charged using mostly renewable energy sources such as solar power. Thus far, we have looked at the existing vehicle and the environment in which it operates, made a model of the vehicle in ADVISOR software, produced a prototype electric vehicle, and investigated recharging infrastructure requirements and designs. In particular, our proposed recharging infrastructure consists of a central recharging station which supplies distribution points with charged batteries. Since we aim to incorporate renewable energies in the infrastructure, we used HOMER software to design a feasible infrastructure system.

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The thermal issue of electric vehicles is an important criterion for the design of the motor and for choosing the adequate cooling system to assure propels electrical performance and reliability. The thermal behavior of motor depends on the heat sources and on the motor geometry. This paper presents the thermal analysis of permanent magnet synchronous motor (PMSM) for electric vehicles traction application. The thermal design technique used is the analytical lumped circuit. An analytical copper and iron loss model is presented also two cooling systems are applied to this model, cooling by air and water. A comparison is carried out so choosing the best solution. The equivalent circuit of the motor is implemented and simulated with MATLAB simulator. The results obtained show the effectiveness of the designed motor and its good satisfaction of the specification book.

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The purpose of this study is to describe the experiments of hydrogen generation from water molecules reacting with activated aluminum particles and the identification of its characteristics using an ARMA model on the assumption of the applications for a fuel-cell vehicle. Because 1 gram of the activated aluminum particles can generate about 1.1 liters of pure hydrogen, they have application possibility as the hydrogen resource of a fuel cell car. However, the details of hydrogen generation characteristics by this reaction are not well known. The reaction has non-linearity and time-varying due to the characteristics of the sample, the external environment and so on. Therefore, it is difficult to construct a mathematical model based on the physiochemical law of the reaction. Here, the dynamic characteristics of hydrogen generation are assumed to be described as a linear ARMA model using the reaction temperature and hydrogen generation. The parameters of ARMA model are identified by a constant trace adaptive algorithm using the measured data. The outputs of the ARMA model are well accorded with the measured data.

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Hybrid Electric Vehicles (HEV) are superior to conventional vehicles from the standpoint of environmental issues. Many factors involve in designing HEVs such as fuel consumption, emission and performance. A major challenge for development of hybrid vehicles is coordination of multiple energy sources and converters, and in case of a HEV, power flow control for both mechanical and electrical path. This necessitates the utilization of appropriate control or energy management strategy. Furthermore, the durability extension of some critical components in the drive train such as batteries tends to be one of the substantial factors considered in designing control strategies for HEVs as replacement costs is a deterring factor for consumers. This paper proposes an improved power follower control strategy for series hybrid electric vehicles based on protection of the vehicle's battery and prediction of the future vehicles' path. First, a fuzzy predictive algorithm is integrated into a conventional power follower management system such that the future path information of the vehicle is taken into account for generation of the control signals. Then, the energy management system is augmented with a new tool to increase the state of the health (SOH) of the power train battery. Furthermore, since Valve Regulated Lead Acid (VRLA) batteries are of great importance in HEV technology, a new method based is used to optimize the charging current for these batteries, in order to decrease charging time and improve battery lifetime. This approach, which results in the extension of the battery life, is called Predictive and Protective Algorithm (PPA). The simulation results verify the effectiveness of the proposed controllers.

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This paper mainly focuses on the energy management system of CJY6470 parallel hybrid electric vehicle (CJY6470PHEV) with the mild hybrid strategy. The energy controller is designed, and the optimum method of the throttle angle and vehicle gear shift, as well as the energy distributing strategy is presented, too. Moreover, the energy management system is simulated according to ECE-EUDC cycles. The results indicate that the energy can be distributed as expected in the system.

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This paper deals with the modelling of a nickel-based battery. The objective is to design a model usable in an electrical engineering laboratory. This study provides a State of Charge (SoC), current and temperature dependant experience-based model. The parameterization is really fast and simple; it does not require electrochemical knowledge. In this paper, the parameterization tests and their analyses are detailed. This model is experimentally validated.

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This paper shows that EV range-extender (RXT) with a trailer will provide better mileage than the plug-in hybrid (PHEV) when an appropriate system is used. A weekly driving pattern is assumed to be: 30 km (6 days a week), 100 km (1 day a week). The RXT system made for this evaluation is composed of a pure BEV and a trailer with an electric generator. Japan 10-15 mode is used for the calculation. The result shows that 35.4 kWh⁄weeks is obtained for RXT, while 36.5 kWh⁄week for PHEV. This would be the first evaluation of RXT based on the fuel economy.

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