Automotive Science and Engineering

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In this paper, an adaptive rule based controller for an anti-lock regenerative braking system (ARBS) of a series hybrid electric bus (SHEB) has been proposed. The proposed controller integrates the regenerative braking and wheel anti-lock functions by controlling the electric motor of the hybrid vehicle, without using any conventional mechanical anti-lock braking system. The performance of the proposed system is evaluated by a comprehensive vehicle dynamics model in MATLAB/Simulink. Using the designed ARBS, the braking and regenerative performances of SHEB have significantly improved in slippery roads while the slip ratios are kept between 0.15 and 0.20.

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Material properties and geometry are two important design parameters which their effects should be considered in a crashworthiness analysis. In this paper, the axial impact of metallic and hybrid energy absorbing thin-walled tubes with poly-gonal cross-section is simulated using LS-DYNA software. The combined effects of changing the geometry and material properties on the mass specific energy absorption (MSEA) as well as the mean and maximum crush forces are investigated. To compare the results, all metallic tubes have identical thickness, length, and circumference. The hybrid tubes are made of the same metallic tubes which are reinforced with special composite overlays. These materials are intentionally selected in such a way that the effects of yield strength and Young’s modulus can be separately investigated. The results show that, in contrast with the current belief, there are some metallic and hybrid tubes with non- circular cross-section shapes, which have better mass specific energy absorption capabilities than the circular ones during the impact.

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Hybrid Electric Vehicles (HEVs) are driven by two energy convertors, i.e., an Internal Combustion (IC) engine and an electric machine. To make powertrain of HEV as efficient as possible, proper management of the energy elements is essential. This task is completed by HEV controller, which splits power between the IC engine and Electric Motor (EM). In this paper, a Genetic-Fuzzy control strategy is employed to control the powertrain. Genetic-Fuzzy algorithm is a method in which parameters of a Fuzzy Logic Controller (FLC) are tuned by Genetic algorithm. The main target of control is to minimize two competing objectives, consisting of energy cost and emissions, simultaneously. In addition, a new method to consider variations of Battery State of Charge (SOC) in the optimization algorithm is proposed. The controller performances are verified over Urban Dinamometer Driving Cycle (UDDS) and New Europian Driving Cycle (NEDC). The results demonstrate the effectiveness of the proposed method in reducing energy cost and emissions without sacrificing vehicle performance.

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In the present study, a model of a large Lithium Polymer (Li-Po) battery for use in the simulation of Hybrid Electric Vehicles (HEVs) is developed. To attain this goal, an Equivalent Circuit (EC) consisting of a series resistor and two RC parallel networks is considered. The accuracy and the response time of the model for use in an HEV simulator are studied. The battery parameters identification and model validation tests are performed in low current with a good accuracy. Similar test process is implemented in high current for another cell and the simulation is verified with experimental results. The validation tests confirm the accuracy of the model for use in HEV simulator. Finally, the battery model is used to model a Vehicle, Fuel and Environment Research Institute (VFERI) hybrid electric city bus using ADVISOR software and its compatibility with other components of the vehicle simulator are demonstrated in a drive cycle test.

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In this paper, the development and optimization of Power Distribution Control Strategy (PDCS) have been performed for a Hybrid Energy Storage Systems (HESS) of a Series Hybrid Electric Bus (SHEB). A common PDCS is based on the use of Ultra-Capacitor (UC) pack. A new simple PDCS is developed as a battery based one. For the battery based PDCS, four parameters are introduced for tuning the PDCS performance. The Design of Experiment (DoE) method is utilized to optimize the parameters of the battery based PDCS for the driving cycles and the vehicle controllers. The results show the optimized battery based PDCS performance for some cases are better than the UC based PDCS performance. Vice versa, for some cases the performance of the UC based PDCS is better than the battery based PDCS. Finally, the costs rising from the HESS (about 66%) is reasonable when considering the over double increase in the battery life-time when using an appropriate PDCS.

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In the present paper, the idea of braking energy regeneration and reusing that energy during acceleration for a refuse truck is comprehended. According to their driving cycle, the refuse trucks have a good potential for braking energy regeneration. On the other hand, hydraulic hybrid is a powertrain with high power density which is appropriate for energy regeneration. In the primary stage of this issue, the hydraulic hybrid propulsion system is designed with intention of regenerating the maximum possible kinetic energy during the refuse truck braking mode. At this stage, a non-fuzzy rule-based control strategy is applied to manage the energy flow in the hybrid powertrain. After that, the powertrain of the Axor 1828 truck and the elements of the hydraulic powertrain are modeled in MATLAB/Simulink. The modeling is performed considering the efficiencies of the powertrain elements. In the last part of the paper, a fuzzy control strategy is designed and modeled to improve the fuel consumption of the truck with hybrid powertrain. In order to see the usefulness of the designed hybrid powertrain, several simulations are organized on the vehicle model in Simulink. The driving cycle for refuse truck in Tehran is used for performing the simulations. The results state indicated that using the hydraulic hybrid powertrain decreased the fuel consumption of the refuse truck by 7 percent. In addition, this amount of reduction was improved by implementing the fuzzy control strategy. The decrease in fuel consumption was due to the regenerating of the braking energy up to 50 percent.

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Many studies have been done on hybrid vehicles in the past few years. The full hybrid vehicles need a large number of batteries creating up to 300 (V) to meet the required voltage of electric motor. The size and weight of the batteries cause some problems. This research investigates the mild hybrid vehicle. This vehicle includes a small electric motor and a high power internal combustion engine. In most cases the car’s driving force is created by an internal combustion part. A small electric motor, which can operate as engine starter, generator and traction motor, is located between the engine and an automatically shifted multi-gear transmission (gearbox). The clutch is used to disconnect the gearbox from the engine when needed such as during gear shifting and low vehicle speed. The power rating of the electric motor may be in the range of about 15% of the IC engine power rating. The electric motor can be smoothly controlled to operate at any speed and torque, thus, isolation between the electric motor and transmission is not necessary. The present study evaluates the properties of the mild hybrid vehicle, its structure and performance and proposes an energy control model for its optimum operation.

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Research on vehicle longitudinal control with a stop and go system is presently one of the most important topics in the field of intelligent transportation systems. The purpose of stop and go systems is to assist drivers for repeatedly accelerate and stop their vehicles in traffic jams. This system can improve the driving comfort, safety and reduce the danger of collisions and fuel consumption. Although there have been many attempts to model stop and go maneuver via traffic models, but predicting the future vehicle's acceleration in steps ahead has not been studied much in this models. The main contribution of this paper is in designing integrated genetic algorithm-artificial neural network (GA-ANN) which is a soft computing method to simulate and predict the future acceleration of the stop and go maneuver for different steps ahead based on US federal highway administration’s NGSIM dataset in real traffic flow. The results of this study are compared with two methods, back propagation based artificial neural network model (BP-ANN) and standard time series forecasting approach called ARX model. The mean absolute percentage error (MAPE), root mean square error (RMSE) and coefficient of determination or R-squared (R2) are utilized as three criteria for evaluating predictions accuracy. The results showed the effectiveness of the proposed approach for prediction of driving acceleration time series. The proposed model can be employed in intelligent transportation systems (ITS), collision prevention systems (CPS) and driver assistant systems (DAS) such as adaptive cruise control (ACC) and etc. The outcomes of this study can be used for the automotive industries who have been seeking accurate and inexpensive tools capable of predicting vehicle speeds up to a given point ahead of time, known as prediction horizon, which can be used for designing efficient predictive controllers based on human behaviors.

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The Energy Storage System (ESS) is an expensive component of an E-bike. The idea of Hybrid Energy Storage System (HESS), a combination between battery and Ultra-Capacitor (UC), can moderate the cost of E-bike ESS. In this paper, a cost function is developed to use for optimal sizing of a HESS. This cost function is consisted of the HESS (battery, UC and DC/DC converter) cost and the cost of battery replacements during 10 years. The battery lifetime and riding pattern limit the life span of ESS. The “Portuguese standard NP EN 1986-1” riding pattern is used in this research. The Genetic Algorithm (GA) is used to solve the optimization problem. The results show that the cost and weight of HESS are clearly better than optimally sized battery ESS.

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This paper investigates the effect of temperature on a hybrid energy storage system with various energy management systems. The hybrid energy storage system consists of a fuel cell, ultracapacitor and battery with associated DC/DC and DC/AC converters. The energy management strategies employed are the state machine control strategy, fuzzy frequency/logic decoupling strategy, minimization strategy of equivalent consumption (ECMS) and external energy maximization strategy (EEMS). Initially, a module of 3.3v 2.3Ah LiPo4 batteries consisting of 15 cells in series and 15 rows in parallel are studied without considering the temperature effect. In the next step, the studies are repeated considering the temperature variation effects. The current and SOC associated with the battery, the hydrogen consumption, and battery life are studied for each strategy. The results suggest that the errors associated with the battery life estimation, as well as the battery current are significant with and without considering the temperature effects with the values of 30% and 20%, respectively.

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Hardware implementation of the Plug-in hybrid electric vehicles (PHEVs) control strategy is an important stage of the development of the vehicle electric control unit (ECU). This paper introduces Model-Based Design (MBD) approach for implementation of PHEV energy management. Based on this approach, implementation of the control algorithm on an electronic hardware is performed using automatic code generation. The advantages of the MBD in comparison with the traditional methods are the capability of eliminating the manual coding complexities as well as compiling problems and reducing the test duration. In this study, hardware implementation of a PHEV rule-based control strategy is accomplished using MBD method. Also, in order to increase the accuracy of the results of the implementation, the data packing method is used. In this method, by controlling the primer and end data of the data packet transferred between the electronic board and the computer system, the noisy data is prevented from entering. In addition, to verify the performance of the implemented control strategy, hardware-in-the-loop (HIL) simulation is used with the two frequency rates. The results show the effectiveness of the proposed approach in correct and rapid implantation procedure.

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As an effective means of displacing fossil fuel consumption and reducing greenhouse gas emissions, plug-in electric vehicles (PEVs) and plug-in hybrid electric vehicles (PHEVs) have attracted more and more attentions. From the power grid perspective, PHEVs and PEVs equipped with batteries can also be used as energy storage facilities, due to the fact that, these vehicles are parked most of the time. Since, the temperature has a strong influence on the battery life-time and also the inherent characteristics of PHEV/PEV energy storage systems limit their use as appropriate resources for energy tuning, this paper, at first, presents a detailed model for energy storage systems of PEVs considering the cooling system and set temperature, and then, it proposes a reliable energy management method for scheduling of PEVs in the multi-microgrid (MMG) systems for both faulted and normal operations using parametric multi-objective function. The simulation results indicate that, considering proper energy management of energy storage systems of PEVs has significant influence on energy scheduling of MMG systems. For this investigation, all data analysis and simulations were done and implemented in MATLAB/Simulink environment.

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In this paper an idea for hybridization of conventional vehicles has proposed. The case study performed on one of the common vehicles on country roads i.e. Samand. This vehicle has high production volume but low fuel performance therefore hybridization of it could be attractive for its manufacture. This paper aims that the hybridization idea and its structure to need minimum mechanical modifications. In consequence attractiveness of this idea for industry could be high. A cost optimization has been performed for sizing of additional components such as electric motors and battery modules and the simulation results has been adopted to verify the proposed idea for case study with hybrid simulation of GT-Suit and MATLAB softwares.      

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To reduce the harmful effects of fuel based engines new technologies in automotive industries have introduced. Combination of novel ball continuously variable transmission and hybrid technologies with the advantages of optimum controlling of power sources in the vehicle are the main topic of this paper by preparing a model of transmission using GT-Suite software. In order to determine the operation and responses of the proposed transmission, different operational modes, along with different inputs in term of speed, torque and ratio are presented. This research successfully demonstrates a new type of transmission which is developed to enjoy the benefits of combining technologies in vehicle drivetrain that features high torque capacity and desirable drivability. Main achievement of this paper is to show the operational modes of this system as well as ability to mode alteration during vehicle operation. Various steady and transient modes are studied in this paper using multi body modeling and it shows HBCVT can eliminate most limitation of parallel hybrid systems.

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In this article, the procedure of series hybridizing is fulfilled on the O457 city bus that is produced in Irankhodro Diesel Company. For simulation validation the bus with base diesel engine is simulated in European and Tehran compound urban–highway driving cycle and fuel consumption results compared. First the ECE_EUDC_LOW driving cycle  simulation results compared with the results of the advisor software that was some difference between two software results. For deep validation bus with base engine was simulated in Tehran driving cycle and fuel consumption calculated 53.26 Lit/100Km that was near actual value that is 59.48 Lit/100Km. After verification, a bus with series hybrid electric-diesel powertrain was designed and simulated in the European and Tehran driving cycle. Simulation results and experimental data’s shown that the series hybrid electric-diesel bus fuel consumption reduction in ‌the ECE_EUDC_LOW driving cycle, is 30% and in Tehran driving cycle is 39% less in comparison to base power train that is base diesel engine.

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This paper introduces a novel powertrain system composed of a liquid ammonia internal combustion engine, a dissociation and separation unit, and a PEM fuel cell system developed for vehicular applications. Using a carbon-free fuel for the ICE and producing hydrogen on board for PEMFC use significantly enhance this novel systemchr('39')s environmental effects. The thermodynamic analyses are conducted using EES and MATLAB software. The results show that while this hybrid powertrain system produces 120 kW output power, energy and exergy efficiencies are 45.2% and 43.1%, respectively. The overall exergy destruction rate of the system becomes 237.4 kW.The fuel consumption, engine speed, and battery state of charge (SoC) analyses are calculated using three driving cycles. These vehicles consume 7.9, 5.7, and 7.7 liters of liquid ammonia per 100 km in FTP-75, NEDC, and HWFET driving cycles, respectively. The battery state of charge differentiation in these three cycles shows the practicality of this novel powertrain system specially in inner-city driving cycles as the battery does not confront any intense decline of SOC to the minimum level. HWFET results show the great dependence of the vehicle on ICE and low PEM fuel cell function, which results in releasing decomposed hydrogen to the environment.

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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.

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In this study, a new micro gas turbine engine is presented. The effect of inlet air cooling on the performance of the micro gas turbine engine by changing the parameters such as the temperature difference between the inlet air temperature (IAT) based on ISA (International Society of Automation) standard and turbine inlet temperature (TIT) has been investigated. then, an Optimization is done base on the Genetic Algorithm with two separate objectives, SNOx minimization, and Thermal efficiency maximization, separately. The thermal efficiency and specific consumption of the optimized cycle based on the thermal efficiency are compared with the XU7/L3 internal combustion engine to produce the output power of 64.57 KW. Results show by adding a cooling system to the micro gas turbines to cool the inlet air with the coefficient performance of 2 and 4 increased the thermal efficiency by about 11.37% rather than base mrio gas turbine engine Eventually, the proposed micro gas turbine engine is more efficient than the XU7/L3 internal combustion engine. so It can be understood that micro  GT is one of the best substitutes for the internal combustion engine in the new vehicle age just by adding the cooling system.

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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.