Showing 3 results for Hybrid Vehicle
Sohrab Pakdelbonab, Afshin Kazerooni, Gholamhassan Payganeh, Mohsen Esfahanian,
Volume 11, Issue 1 (3-2021)
Abstract
Global restrictions on the use of fossil fuels in the transportation sector and the commitment to rapid response to the climate change have created a strong incentive to develop fuel-efficient and low-emission vehicle systems. Hydraulic hybrid power train technology is one of the temporary solutions introduced to optimize internal combustion engine (ICE) operation and regenerate braking energy. The hydraulic hybrid power train system (HHPS) has a higher power density than the electric one. So, it is used in heavy vehicles, agricultural and construction machinery that need a high-power density to accelerate or recover the braking energy. In some trucks, such as refuses collection trucks, fire trucks and delivery trucks, a high percentage of the ICE energy is consumed by the auxiliary systems. In this type of trucks, the hydraulic hybrid power train systems are not very efficient. This paper introduces a hydraulic hybrid auxiliary system (HHAS) concept to manage the energy consumed by the auxiliary system in refuse collection trucks. In the first part of the paper, the configurations and operating modes of series, parallel and hydro-mechanical HHPS are discussed and compared with the HHAS concept. In the following, the conventional refuse collection truck model and refuse truck equipped with HHAS model was developed in MATLAB/SINMULINK and simulated in Tehran refuse collection truck driving cycle. The simulation results show that by using the HHAS concept, the fuel consumption is reduced by 15 percent.
Abolfazl Ghanbari Barzian, Mohammad Saadat, Hossein Saeedi Masine,
Volume 12, Issue 1 (3-2022)
Abstract
Environmental pollution and reduction of fossil fuel resources can be considered as the most important challenges for human society in the recent years. The results of previous studies show that the main consumer of fossil fuels and, consequently, most of the air pollutants, is related to the transportation industry and especially cars. The increasing growth of vehicles, the increase in traffic and the decrease in the average speed of inner-city vehicles have led to a sharp increase in fuel consumption. To address this problem, automakers have proposed the development and commercialization of hybrid vehicles as an alternative to internal combustion vehicles. In this paper, the design of an energy management system in a fuel-cell hybrid vehicle based on the look-ahead fuzzy control is considered. The preparation of fuzzy rules and the design of membership functions is based on the fuel efficiency curve of the fuel-cell. In look-ahead fuzzy control, the ahead conditions of the vehicle are the basis for decision in terms of slope and speed limit due to path curves as well as battery charge level. The fuzzy controller will determine the on or off status of the fuel-cell, as well as the power required. The motion of the fuel-cell hybrid vehicle on a real road is simulated and the performance of the proposed look-ahead controller is compared with the base controller (thermostatic method). The simulation results show that using the proposed approach can reduce the fuel consumption of the fuel-cell hybrid vehicle as well as travel time.
Prof Morteza Montazeri, Mr Mohammad Amin Zakizadeh, Mr Afshin Mostashiri,
Volume 15, Issue 4 (12-2025)
Abstract
The rising demand for sustainable transportation has intensified research on Fuel Cell Hybrid Electric Vehicles (FCHEVs). Integrating fuel cells with lithium-ion batteries provides a pathway to enhance energy efficiency and driving performance, but ensuring the durability of both components under real operating conditions remains a critical challenge. This work proposes an integrated framework to improve FCHEV performance and lifetime through combined modeling, degradation analysis, and optimized energy management. Dynamic vehicle simulations were conducted using the ADVISOR platform under both the Urban Dynamometer Driving Schedule (UDDS) and a real-world cycle based on Tehran traffic data. Degradation models were implemented to capture platinum dissolution in the Proton Exchange Membrane Fuel Cell (PEMFC) and capacity loss in the lithium-ion battery, incorporating the effects of state of charge, temperature, and current rate. An energy management strategy was developed using a Fuzzy Logic Controller (FLC) for fuel cell–battery power distribution, which was further refined with a Genetic Algorithm (GA). The optimization objectives included reducing hydrogen consumption and extending component lifetimes. The GA-optimized FLC extended PEMFC lifetime by 50.6% Tehran and 12.9% UDDS and reduced battery capacity fade by 10% and 4.9%, respectively. While direct hydrogen consumption increased in Tehran due to more aggressive regenerative-energy routing to the battery, the Equivalent Fuel Consumption (EFC) decreased from 971.32 → 937.21 g/100 km (Tehran) and 794.41 → 782.24 g/100 km (UDDS), reflecting a net efficiency gain once SOC restoration is accounted for.
