Automotive Science and Engineering

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In this paper, multi-objective uniform-diversity genetic algorithm (MUGA) with a diversity preserving mechanism called the ε-elimination algorithm is used for Pareto optimization of 5-degree of freedom vehicle vibration model considering the five conflicting functions simultaneously. The important conflicting objective functions that have been considered in this work are, namely, vertical acceleration of seat, vertical velocity of forward tire, vertical velocity of rear tire, relative displacement between sprung mass and forward tire and relative displacement between sprung mass and rear tire. Further, different pairs of these objective functions have also been selected for 2-objective optimization processes. The comparison of the obtained results with those in literature demonstrates the superiority of the results of this work. It is shown that the results of 5-objective optimization include those of 2-objective optimization and, therefore, provide more choices for optimal design of vehicle vibration model.

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In cruise control systems, the performance of the controller is important. Hence, in order to have accurate results, the nonlinear behavior of a vehicle model should also be considered. In this article, a vehicle with a nonlinear model is controlled by using a nonlinear method. The nonlinear term of the model is the generated torque of engine, which is a polynomial equation. In addition, feedback linearization is used as a nonlinear method in order to design two parallel controllers to control the movement of the vehicle. These two parallel controllers are used to control braking and gas pedals which are in charge of the angular velocity of the wheels. To check the performances of controllers, first, each controller is used separately. Finally, two parallel controllers are used to track the reference signal. Comparison between results shows that the designed controller is able to reduce the convergence time of about 10 seconds. This improvement is near 35% in comparison with near studies. In addition, it can reduce the error between the velocity of the vehicle and the values of the reference signal that results in more safety for passengers.

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In this paper, a new version of multi-objective differential evolution with dynamically adaptable mutation factor is used for Pareto optimization of a 5-degree of freedom vehicle vibration model excited by non-stationary random road profile. In this way, non-dominated sorting algorithm and crowding distance criterion have been combined to differential evolution with fuzzified mutation in order to achieve multi-objective meta-heuristic algorithm. To dynamically tune the mutation factor, two parameters, named, number of generation and population diversity are considered as inputs and, one parameter, named, the mutation factor as output of the fuzzy logic inference system. Conflicting objective functions that have been observed to be optimally designed simultaneously are, namely, vertical seat acceleration, vertical forward tire velocity, vertical rear tire velocity, relative displacement between sprung mass and forward tire and relative displacement between sprung mass and rear tire. Furthermore, different pairs of these objective functions have also been chosen for bi-objective optimization processes. The comparison of the obtained results with those in the literature unveils the superiority of the results of this work. It is displayed that the results of 5-objective optimization subsume those of bi-objective optimization and, consequently, this achievement can offer more optimal choices to designers.

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In order to improve the safety and longitudinal stability of a vehicle equipped with standard ABS system, this paper, analyzes the basic principles of vehicles stability and proposes a control strategy based on fuzzy adaptive control which will adjust PID gain parameters, using genetic algorithm. A linear three-degree-of-freedom (DOF) vehicle model was set up in Simulink and the stability test was conducted utilizing jointly a joint established simulation platform with CarSim.
   For controlling the brake length, traditional controllers have difficulty in guaranteeing performance and stability over a wide range of parameter changes and disturbances. Therefore, a 2 level controller by providing a modified Sliding Mode Control (SMC) will be used. Using this approach the flexibility increased and brake length and rotor temperatures decreases significantly. This results improvement of the vehicle’s stability and brakes fatigue lifespan.

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The control of Antilock Braking Systems (ABS) is a difficult problem, because of their nonlinearities and uncertainties appearing in their dynamics and parameters. To overcome these issues, this paper proposes a new adaptive controller for the next generation of ABS. After considering a complex vehicle dynamic, a triple adaptive fuzzy control system is presented. Important parameters of the vehicle dynamic include two separated brake torques for front ands rear wheels, as well as longitudinal weight transfer which is caused by the acceleration or deceleration. Because of the nonlinearity of the vehicle dynamic model, three fuzzy-estimators have been suggested to eliminate nonlinear terms of the front and rear wheels’ dynamic. Since the vehicle model parameters change due to variations of road conditions, an adaptive law of the controller is derived based on Lyapunov theory to adapt the fuzzy-estimators and stabilize the entire system. The performance of the proposed controller is evaluated by some simulations on the ABS system. The results demonstrate the effectiveness of the proposed method for ABS under different road conditions.

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Rollover of sport utility vehicles is a critical challenge for dynamic stability of the vehicle. Due to the high rate of fatalities resulted from the rollover, in order to reduces the injuries, the design of active vehicle controllers has received significant attention among the researchers and car companies. In this article, a multi-criteria optimum method is discussed in order to design a dynamics stabilizing controller via differential braking with an optimum braking torque distribution. To this end, the nonlinear control method on the basis of the sliding mode techniques has been implemented that provides ride comfort, improve safety performance, and maintain maneuverability. To address the trade-off between the conflicting requirements of vehicle dynamic control in terms of maneuverability and rollover prevention capability, we formulate an artificial intelligence-based multi-criteria genetic algorithms. The simulation verification analysis indicates that the utilized optimum distribution braking torques result in the desired enhancement in roll stability of the vehicle.

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A new safe optimal consensus procedure is presented to guarantee the asymptotic and string stability as well as crash avoidance of large-scale non-identical traffic flow. Since time delay is an inherent characteristic of physical actuators and sensors, measurement delay and lags are involved in the upper level control structure. A third-order linear model is employed to define the 1-D motion of each automated vehicle (AV) and the constant time headway plan is employed to regulate the inter-AV distance. It is assumed that the network structure is decentralized look ahead (DLA) and each AV has access to relative position and velocity regarding with the front AV. A linear control law is introduced for each AV and by performing the stability analysis in frequency domain, the necessary conditions guaranteeing string stability and crash avoidance for large-scale traffic flow are derived. Afterwards, to calculate the optimal control parameters guaranteeing the best performance, an objective function combining all mentioned conditions as well as maximum overshoot, settling time and stability margin is introduced. The genetic algorithm (GA) technique is employed to optimize the presented objective function and obtain the optimal control parameters. Various numerical results are proposed to demonstrate the efficiency of this method.

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This paper considers the asymptotic zero tracking error as well as string stability of large-scale automated vehicle convoys (LAVC). Both centralized and decentralized bi-directional network topologies are investigated. A double integrator dynamical equation is defined to describe the 1-D dynamics of automated vehicles (AV). A centralized / decentralized controller which employs the relative displacement and velocity compared with the backward and forward AVs is defined for all following AVs. Since the dynamical equation of LAVC is hard to be analyzed for internal stability, a PDE-based approach is introduced to decouple and reduce the closed-loop dynamical equation.  According to this approach, we will be able to decouple the dynamical equation of all AVs individually based on the error dynamics. After simplifying the dynamical equation of LAVC, the conditions satisfying the internal stability of centralized and decentralized networks are obtained. After that, algebraic analyses in frequency domain will able us to find the constraints on control gains guaranteeing the string stability. Simulation and experimental results are available to describe the merits of this algorithm.

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This paper experimentally investigates the trafficability of a small tracked vehicle on a slope. An increase in the angle of slope inclination may divert the vehicle from its path. In other words, the deviation of the vehicle is due to a sudden increase in the yaw angle. Also, the tip-over occurs at a specific slope angle. The locomotion of the small tracked vehicle on soils with different terramechanics (such as cohesion, internal friction angle, cohesive modulus, and friction modulus) is also simulated to evaluate its slope-traversing performance. Moreover, the impact of velocity and soil type on traversing a slope is measured. The proposed yaw angle control system is modeled for controlling the yaw angle of the tracked vehicle. This controller is designed through co-simulation. It keeps the tracked vehicle at zero yaw angle to achieve straight locomotion on slopes. It is compared to the PI, PID, and fuzzy controllers. The response of this controller is faster than PI and PID controllers. A Comparison between fuzzy and proposed yaw angle controller yields almost similar responses. The mechanism of the proposed yaw angle controller is also easier to understand. The precision of the controller's performance is measured by simulating over different terrains.

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In this paper, firstly chaotic behavior of the lateral dynamics of vehicle is investigated by the use of numerical tools including Lyapunov exponent and bifurcation diagrams. To this end rout to chaos along with period doubling and quasi-periodic responses are demonstrated in terms of bifurcation diagrams. After chaos analysis, a novel controller commensurate with the chaotic characteristics of the system, in conformity with Poincaré map is represented to suppress the chaotic behavior of lateral movement. The Poincaré map of the system is derived by means of a neuro fuzzy network. A robust Fuzzy system on the basis of nonlinear Ott-Grebogi-Yorke (OGY) method forms the control system. Closed-loop results of the system shows effectiveness of the chaos controller in extreme conditions.

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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.

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Today, a large part of a vehicle's performance depends on its suspension. These expectations are addressed in this paper, including ride comfort, road-holding, and lateral stability. Due to the high statistics of lateral overturning, preventing lateral overturning and providing lateral stability of the vehicle is one of the most important goals of this paper. In this paper, a new type of suspension based on the Series Active Variable-Geometry is used by designing a simple Sliding Mode Controller (SMC) to improve vehicle dynamics. On the contrary previous studies in this field, asymmetric distribution of control command has been used to increase the usefulness of suspension in standard road roughness and during longitudinal and transverse maneuvers. In this paper, by simulating crosswind and double lane change maneuvers, several ideas have been used to command the suspension links, and a 25% to 30% improvement in vehicle dynamic performance parameters has been achieved.

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Recently, number of Hybrid Electric Vehicles (HEV) is on the rise due to concerns over environmental issues. By combining fuel and electricity as two sources of power, this type of vehicle is capable of bettering fuel economy and lowering emission. In this work, fuel and electrical energy consumption of a parallel hybrid electric vehicle are investigated through TEH-CAR urban drive cycle. For this purpose, a forward looking model is developed in AVL CRUISE M. To ensure adequacy of the model and take engine gas path components’ dynamic interaction into account, a crank based model with individual cylinders is utilized. Furthermore, a throttle filter is presented to slow down engine’s response and also, allow the electric motor to have the larger share of delivering power in transients. Finally, genetic algorithm is used to find optimal values for throttle filter parameter and electric motor load ratio, in order to have minimal overall fuel and electrical energy consumption. The optimization results show 1.2% of fuel and 20.2% of total energy consumption reduction in comparison with conventional torque assist.

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The adaptive size-independent consensus problem of uni-directional (UD) and bi-directional (BD) decentralized large-scale vehicle convoys with uncertain dynamics has been investigated in this research work. The constant distance plan (CDP) is employed to adjust the distances between successive vehicles. We assume that only relative displacement information between adjacent vehicles is accessible (partial measurement) and other information such as relative velocity and acceleration are not provided. The stability of the convoy can be performed by the analysis of each couple of consecutive vehicles. The main objective is to design an adaptive size-independent control protocol maintaining internal and string stability based on CDP with only partial measurement. Appropriate adaptive rules are derived to estimate the uncertain dynamics by utilizing only relative displacement. It will be proved that the presented adaptive protocol assures both internal stability (asymptotic stability of closed-loop convoy) and string stability (tracking error attenuation) of large-scale decentralized UD and BD convoys under the CDP. Simulations demonstrate the efficiency of the presented control framework.

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Electric vehicles are attaining significant attention recently and the current legislation is forcing the automotive industry to electrify the productions. Regardless of electric energy accumulation technology, drive technology is one of the vital components of EVs. The motor drive technology has been mainly developed based on the application which required position/velocity control. In automotive application, however, torque control is an important aspect since the drivers have already used to drive the vehicle based on torque control approach in traditional powertrain system. In this article, a model-based approach is employed to develop a controller which can guarantee the precise control of the induction motors torque for a micro electric vehicle (EV) application regardless of operating conditions. The implementation of the control drive was conducted in MATLAB/Simulink environment, followed by Model In the Loop simulation and testing at various test conditions to confirm the robustness of the developed drive. Direct Torque Control (DTC) with optimum voltage vector selection method is employed to control the motor torque that requires fewer power electronics to process its operation and hence lowers the cost of implementation. The result shows the practicality of the designed control system and its ability to track reference torque commands. Vitally, the controlled approach shows fair abilities to control IMs to produce torque at both the motoring and regenerative modes which is a highly important requirement in electrical propulsion powertrains. Furthermore, the controller’s response time was within the industrial standard range which confirms its suitability for industrial implementation at low cost.

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In this paper, the consensus of second-order nonlinear self-driving vehicle convoys (SDVCs) is studied. We assume that each self-driving vehicle (SDV) communicates only with one front and one rear SDVs. Each SDV’s nonlinear dynamics consisting of the rolling resistance and the air drag force is a function of SDV’s speed and is investigated in SDVC’s modeling and consensus design. Since the speed is bounded, all vehicles’ nonlinearities are also bounded. Due to engine saturation of each SDV, the control input is limited. We involve this limitation by introducing the arctan(.) function to control protocol. The inter-SDV’s distances are assumed to be constant during motion. The distance tracking error associated with each SDV is defined as distance between it and the leading SDV. The error dynamics of the proposed SDVC is derived after applying the consensus law to each SDV. To prove the internal stability, the Lyapunov theorem is employed. We will prove that under this consensus algorithm, the SDVC will be internal stable. To validate the effectiveness of this method, a SDVC comprising a leading and 6 following SDVs will be studied. It will be verified that under the proposed consensus law, all the SDVs reach a unique consensus.