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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Homogenous Charge Compression Ignition (HCCI) engines hold promise of high fuel efficiency and low emission levels for future green vehicles. But in contrast to gasoline and diesel engines, HCCI engines suffer from lack of having direct means to initiate combustion. A combustion timing controller with robust tracking performance is the key requirement to leverage HCCI application in production vehicles. In this paper, a two-state control-oriented model is developed to predict HCCI combustion timing for a range of engine operation. The experimental validation of the model confirms the accuracy of the model for HCCI control applications. An optimal integral state feedback controller is designed to control the combustion timing by modulating the ratio of two fuels. Optimization methods are used in order to determine the controller’s parameters. The results demonstrate the designed controller can reach optimal combustion timing within about two engine cycles, while showing good robustness to physical disturbances.

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In this paper, a complete model of an electro hydraulic driven dry clutch along with its performance evaluation has elucidated. Through precision modeling, a complete nonlinear physical and full order sketch of clutch has drawn. Ultimate nonlinearities existent in the system prohibits it from being controlled by conventional linear control algorithms and to compensate the behavior of the system mainly during gearshift procedure, a nonlinear control program has been developed and tested. A unique approach to estimating clamp force has been adopted which makes the system comparable to a real world and full-physical one. Based on this type of modeling, the control approach is a true and feasible, ready-to-implement program which is based only on reality. The clutch model has been validated against experiments and great agreement has been attained since, every fine point has been taken into account and nothing is out of representation unless it is not crucial to system performance. The nonlinear control program does the control task very well and administrates the system in the desired trajectory.

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Non-linear characteristic of tire forces is the main cause of vehicle lateral dynamics instability, while direct yaw moment control is an effective method to recover the vehicle stability. In this paper, an optimal linear quadratic regulator (LQR) controller for roll-yaw dynamics to articulated heavy vehicles is developed. For this purpose, the equations of motion obtained by the MATLAB software are coded and then a control law is introduced by minimizing the local differences between the predicted and the desired responses. The influence of some parameters such as the anti roll bar, change the parameters of the suspension system and track wide in articulated heavy vehicles stability has been studied. The simulation results show that the vehicle stability can be remarkably improved when the optimal linear controller is applied

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The suspension system of a vehicle is one of the most important parts which is involved in the process of vehicle designing. When a vehicle suspension system is designed, the evaluation of its performance against the road disturbances such as shocks and bumps are very important. The most commonly used systems consist of four hydraulic Jacks with mobility in vertical line with low speed and low exactitude. This paper offers a new mechanism for inspecting the suspension system of a vehicle using a parallel robot called Stewart. This robot is a special kind of parallel robots with capability of movements in different directions with high speed, accuracy and repeatability. In this paper the suspension system is evaluated on a quarter model of a simulated vehicle with control and guidance of Stewart robot using PID controller. The Stewart robot simulates the isolated and uneven bumps on a flat road in order to evaluate the given suspension system, and to investigate some criteria such as comforting of the passengers and remaining of the vehicle on the road. The results of the simulations show that the proposed method has a high accuracy, applicability and flexibility as well as simplicity, compared to currently used mechanisms.

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In this study, stability control of a three-wheeled vehicle with two wheels on the front axle, a three-wheeled vehicle with two wheels on the rear axle, and a standard four-wheeled vehicle are compared. For vehicle dynamics control systems, the direct yaw moment control is considered as a suitable way of controlling the lateral motion of a vehicle during a severe driving maneuver. In accordance to the present available technology, the performance of vehicle dynamics control actuation systems is based on the individual control of each wheel braking force known as the differential braking. Also, in order to design the vehicle dynamics control system the linear optimal control theory is used. Then, to investigate the effectiveness of the proposed linear optimal control system, computer simulations are carried out by using nonlinear twelvedegree- of-freedom models for three-wheeled cars and a fourteen-degree-of-freedom model for a fourwheeled car. Simulation results of lane change and J-turn maneuvers are shown with and without control system. It is shown that for lateral stability, the three wheeled vehicle with single front wheel is more stable than the four wheeled vehicle, which is in turn more stable than the three wheeled vehicle with single rear wheel. Considering turning radius which is a kinematic property shows that the front single three-wheeled car is more under steer than the other cars.

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In this paper, the enhancement of vehicle stability and handling is investigated by control of the active geometry suspension system (AGS). This system could be changed through control of suspension mounting point’s position in the perpendicular direction to wishbone therefore the dynamic is alternative and characteristics need to change. For this purpose, suitable controller needs to change mounting point’s position in limit area. Adaptive fuzzy control able to adjust stability and handling characteristics in all conditions. Also, simple controller such as proportional-integral-derivative (PID) versus adaptive fuzzy have been used that submit intelligent controllers. The three of freedom model (3DOF) in vehicle handling is validated with MATLAB and CarSim software. The results show that the steady state response of the adaptive fuzzy controller has been closed to desired yaw and roll angle has been enhanced about %20. In cases of lateral velocity and side slip angle have the same condition that it shows the stability has been improved. The control effort of PID needs to change very high that this response is not good physically, while control effort in adaptive fuzzy is less than 50 mm.

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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 spark ignition (SI) engines, the accurate control of air fuel ratio (AFR) in the stoichiometric value is required to reduce emission and fuel consumption. The wide operating range, the inherent nonlinearities and the modeling uncertainties of the engine system are the main difficulties arising in the design of AFR controller. In this paper, an optimization-based nonlinear control law is analytically developed for the injected fuel mass flow using the prediction of air fuel ratio response from a mean value engine model. The controller accuracy is more increased without chattering by appending the integral feedback technique to the design method. The simulation studies are carried out by applying severe changes in the throttle body angle to evaluate the performance of the proposed controller with and without integral feedback. The results show that the proposed controller is more effective than the conventional sliding mode controller in regulating the AFR without chattering.

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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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Direct Yaw moment Control systems (DYC) can maintain the vehicle in the driver’s desired path by distributing the asymmetric longitudinal forces and the generation of the Control Yaw Moment (CYM). In order to achieve the superior control performance, intelligent usage of lateral forces is also required. The lateral wheel forces have an indirect effect on the CYM and based upon their directions, increase or decrease the amount of CYM magnitude. In this paper, a systematic and applicable algorithm is proposed to use the lateral force in the process of Yaw controlling optimally. The control systems are designed based on the proposed algorithm. This system includes Yaw rate controller and wheel slip controllers which are installed separately for each wheel. Both of the mentioned control systems are designed on the basis of the Fuzzy logic. Finally, the capabilities of the proposed control systems are evaluated in a four wheel drive vehicle, for which, the traction of each wheel can be controlled individually. It is shown that considering the lateral force effect offers significant improvement of the desired yaw rate tracking

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In this paper, a numerical study is performed to provide the combustion and emission characteristics resulting from fuel-reactivity controlled compression ignition (RCCI) combustion mode in a heavy-duty, single-cylinder diesel engine with gasoline and diesel fuels. In RCCI strategy in-cylinder fuel blending is used to develop fuel reactivity gradients in the combustion chamber that result in a broad combustion event and reduced pressure rise rates (PRR). RCCI has been demonstrated to yield low NOx and soot with high thermal efficiency in light and heavy-duty engines. KIVA-CHEMKIN code with a reduced primary reference fuel (PRF) mechanism are implemented to study injection timings of high reactivity fuel (i.e., diesel) and low reactivity fuel percentages (i.e., gasoline) at a constant engine speed of 1300 rpm and medium load of 9 bar indicated mean effective pressure (IMEP). Significant reduction in nitrogen oxide (NOx), while 49% gross indicated efficiency (GIE) were achieved successfully through the RCCI combustion mode. The parametric study of the RCCI combustion mode revealed that the peak cylinder pressure rise rate (PPRR) of the RCCI combustion mode could be controlled by several physical parameters – PRF number, and start of injection (SOI) timing of directly injected fuel.

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In recent years, need to increase the convenience of trips in railway vehicles causes that train operators and manufacturers focus on reducing the noise level which is sensed by passengers. In this paper, first the state of modeling acoustic noise in cab train is discussed and natural frequencies and acoustic mode shapes are derived and then formulation of acoustic pressure in the cab will be obtained. By utilizing field testing, the noise produced by diesel engine in the cabin of Pardistranset train (source of undesirable noise), has been measured and is used in simulating. In order to reduce the acoustic pressure, a secondary noise source is used which its Stimulation signal is obtained by phased PID controller. Then, active noise control will be investigated in two cases of single-channel and multi-channel. The result of actuating the controller shows that in central frequencies of one octave band, there is a reduction in the sound pressure level, loudness, and sound loudness level.

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Robust control design of vehicles addresses the effect of uncertainties on the vehicle’s performance. In present study, the robust optimal multi-objective controller design on a non-linear full vehicle dynamic model with 8-degrees of freedom having parameter with probabilistic uncertainty considering two simultaneous conflicting objective functions has been made to prevent the rollover. The objective functions that have been simultaneously considered in this work are, namely, mean of control effort (MCE) and variance of control effort (VCE).The nonlinear control scheme based on sliding mode has been investigated so that applied braking torques on the four wheels are adopted as actuators. It is tried to achieve optimum and robust design against uncertainties existing in reality with including probabilistic analysis through a Monte Carlo simulation (MCS) approach in multi-objective optimization using the genetic algorithms. Finally, the comparison between the results of deterministic and probabilistic design has been presented. The comparison of the obtained robust results with those of deterministic approach shows the superiority robustness of probabilistic method.

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Nowadays, the use of small vehicles is spreading among urban areas and one sort of these vehicles are three-wheeled vehicles (TWVs) which can be competitive with four-wheeled urban vehicles (FWVs) in aspects such as smallness, simple manufacturing, and low tire rolling resistance, fuel consumption and so on. The most critical instability associated with TWVs is the roll over. In this paper a tilt control mechanism has been modeled which can reduce the danger of roll over by leaning the vehicle towards the turning center in order to decrease the amount of lateral load transfer (LLT), and by doing so, system combines the dynamical abilities of a passenger car with a motorcycle. A 3 degree of freedom vehicle model is simulated at constant speed in MATLAB-Simulink environment and a fuzzy algorithm is developed to control such a non-linear system with appropriate tilting torque. Results are interpreted in presence and absence of controller with different longitudinal speeds and steering inputs the results are also compared to behavior of a similar FWV and this is concluded that the tilt control system could countervail deficiencies of the TWV compared to the FWV.

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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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Due to the increasing demand for traveling in public transportation systems and increasing traffic of vehicles, nowadays vehicles are getting to be intelligent to increase safety, reduce the probability of accident and also financial costs. Therefore, today, most vehicles are equipped with multiple safety control and vehicle navigation systems. In the process of developing such systems, simulation has become a cost-effective chance for the fast evolution of computational modeling techniques. The most popular microscopic traffic flow model is car following models which are increasingly being used by transportation experts to evaluate new Intelligent Transportation System (ITS) applications. The control of car following is essential to its safety and its operational efficiency. This paper presents a car-following control system that was developed using a fuzzy model predictive control (FMPC). This system was used to simulate and predict the future behavior of a Driver-Vehicle-Unit (DVU) and was developed based on a new idea to calculate and estimate the instantaneous reaction of a DVU. At the end, for experimental evaluation, the FMPC system was used along with a human driver in a driving simulator. The results showed that the FMPC has better performance in keeping the safe distance in comparison with real data of human drivers behaviors. The proposed model can be recruited in driver assistant devices, safe distance keeping observers, collision prevention systems and other ITS applications.

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In this article, vehicle cornering stability and brake stabilization via bifurcation analysis has been investigated. In order to extract the governing equations of motion, a nonlinear four-wheeled vehicle model with two degrees of freedom has been developed. Using the continuation software package MatCont a stability analysis based on phase plane analysis and bifurcation of equilibrium is performed and an optimal controller has been proposed. Finally, simulation has been done in Matlab-Simulink software considering a sine with dwell steering angle input, and the effectiveness of the proposed controller on the aforementioned model has been validated with Carsim model.

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In this paper, a two-surfaces sliding mode controller (TSSMC) is proposed for the voltage tracking control of a two input DC-DC converter in application of electric vehicles (EVs). The imperialist competitive algorithm (ICA) is used for tuning TSSMC parameters. The proposed controller significantly improves the transient response and disturbance rejection of the two input converters while preserving the closed-loop stability. The combination of the proposed controller and ICA, realizes a fast transient response over a wide transient load changes and input voltage disturbances. For modeling the equations governing the system, state-space average modeling technique is used. In order to analyzing the results, the two input converter equipped with the proposed controller, was modeled in MATLAB/SIMULINK environment. Simulation results are reported to validate the theoretical predictions and to confirm the superior performance of the proposed nonlinear controller when it is compared with a conventional pure SMC.