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Abstract This study aims to take the first step in bridging the gap between vehicle dynamics systems and autonomous control strategies research. More specifically, a nested method is employed to evaluate the collision avoidance ability of autonomous vehicles in the primary design stage theoretically based on both dynamics and control parameters. An integrated model is derived from a half car mathematical model in the lateral direction, consisting of two degrees of freedom, lateral deviation and yaw angle, with a traction mathematical model in the longitudinal direction, consisting of two degrees of freedom, the longitudinal velocity and rolling velocity of the wheel. The integrated model uses a mathematical power train model to generate the torque on the wheel and connects the two systems via the magic formula tyre model to represent the tyre non-linearity during augmented longitudinal and lateral dynamic attitudes.

Abstract With increasing demands for higher performance along with lower vehicle emissions, lightweight vehicle system construction is key to meet such demands. Suspension and transmission assemblies being the key areas for weight-reduction, we have designed a revolutionary new type of suspension system which combines the suspension links with the powertrain assembly and thus completely eliminates one suspension member. Less weight means lower fuel-consumption with improved passenger-comfort and road-holding due to reduction in unsprung mass. Elimination of a suspension link reduces the overall cost of material, machining & fabrication making our design cost-effective than existing setups. This paper deals with the design and implementation of of our concept. A working prototype is also constructed and tested which completely validates our design.

Abstract A kinematic modeling framework was established to predict status (position, displacement, velocity, acceleration, and shape) of a towing vehicle system with different driver inputs. This framework consists of three components: (1) a state space model to decide position and velocity for the vehicle system based on Newton’s second law; (2) an angular acceleration transferring model, which leads to a hypothesis that the each towed unit follows the same path as the towing vehicle; and (3) a polygon model to draw instantaneous polygons to envelop the entire system at any time point.

Abstract The brake discs are subjected to thermal load due to sliding by the brake pad and fluctuating loads because of the braking load. This combined loading problem requires simulation using coupled thermo-mechanical analysis for design evaluation. This work presents a combined thermal and mechanical finite element analysis (FEA) and evolutionary optimization-based novel approach for estimating the optimal design parameters of the ventilated brake disc. Five parameters controlling the design: inboard plate thickness, outboard plate thickness, vane height, effective offset, and center hole radius were considered, and simulation runs were planned. A total of 27 brake disc designs with design parameters as recommended by the Taguchi method (L27) were modeled using SolidWorks, and the FEA simulation runs were carried out using the ANSYS thermal and structural analysis tool.

Abstract In this article performance of the innovative Crank-Lever Electromagnetic Damper (CLEMD) for an off-road vehicle suspension system is analyzed. To determine the characteristic behavior of the CLEMD, the damping force it provides on the suspension system is varied by changing the values of the damping coefficient in the simulations. Various parameters considered in the analyses include power regenerated, voltage, current, comfort, road-holding, etc. The behavior of all the parameters of the CLEMD is observed for an off-road vehicle by carrying out simulations on country roads since the off-road vehicles are subjected to higher road irregularities and hence provide an opportunity to regenerate a higher amount of power. A two-dimensional (2-D) model of a vehicle developed in SimMechanics is interfaced with a Simulink model of CLEMDs for the analyses.

Abstract Obstacle avoidance is an important function in self-driving vehicle control. When the vehicle move from any arbitrary start positions to any target positions in environment, a proper path must avoid both static obstacles and moving obstacles of arbitrary shape. There are many possible scenarios, manually tackling all possible cases will likely yield a too simplistic policy. In this paper reinforcement learning is applied to the problem to form effective strategies. There are two major challenges that make self-driving vehicle different from other robotic tasks. Firstly, in order to control the vehicle precisely, the action space must be continuous which can’t be dealt with by traditional Q-learning. Secondly, self-driving vehicle must satisfy various constraints including vehicle dynamics constraints and traffic rules constraints. Three contributions are made in this paper.

Abstract The development, analysis, and optimization of battery electric class-7 heavy-duty trucks equipped with multi-speed transmissions are discussed in this paper. The designs of five new traction motors-fractional-slot, concentrated winding machines-are proposed for use in heavy-duty electric trucks. The procedure for gear-ratio range selection is outlined and ranges of gear ratios for three-to six-speed transmission powertrains are calculated for each of the proposed electric traction motors. The simulation and gear-ratio optimization tasks for class-7 battery electric trucks are formulated. The energy consumption of the e-truck with the twenty possible powertrain combinations is minimized over the four driving cycles and the most efficient powertrain layouts that meet the performance criteria are recommended.

Abstract Aiming to improve the handling performance of heavy tractor semi-trailer during turning or changing lanes at high speed, a hierarchical structure controller is proposed and a hardware-in-the-loop (HIL) test bench of the electronic pneumatic braking system is developed to validate the proposed controller. In the upper controller, a Kalman filter observer based on the heavy tractor semi-trailer dynamic model is used to estimate the yaw rates and sideslip angles of the tractor and trailer. Simultaneously, a sliding mode direct yaw moment controller is developed, which takes the estimated yaw rates and sideslip angles and the reference values calculated by the three-degrees-of-freedom dynamic model of the heavy tractor semi-trailer as the control inputs. In the lower controller, the additional yaw moments of tractor and trailer are transformed into corresponding wheel braking forces according to the current steering characteristics.

Abstract In motorcycles, when they are traveling at medium to high speed, the roll stability is usually maintained by the restoration force generated by self-steering effect. However, when the vehicle is stationary or traveling in low speed, sufficient restoring force does not occur because some of the forces, such as centrifugal force, become small. In our study, we aimed at prototyping a motorcycle having a roll stability realized by a steering control when the vehicle is stationary or traveling in low speed. When we considered a mathematical control model to be applied, general models of four-degree-of-freedom had a critical inconvenience that the formulae include nonlinear second derivatives making them excessively complicated for deriving a practically applicable control method. Accordingly, we originally constructed a new control model which has equivalent two point masses (upper and lower from the vehicle’s center of gravity).

Abstract In this article, compared with traditional Remote Parameter Control (RPC), the iterative process is improved based on linear transfer function (TF) estimation of the nonlinear dynamic system. In the improved RPC, the iteration coefficient is designed according to the convergence condition of the nonlinear iterative process, so that the convergence level, convergence speed, and iteration stability could be improved. The difference between the traditional and the improved RPC iterative process is discussed, the RPC iterative process of the nonlinear system is analyzed, and channel decoupling for Multi-Input Multi-Output (MIMO) system based on eigen-decomposition of the system TF and linear TF estimation is introduced. It assumes that the eigenvector matrix of the system TF remains the same, and the linear TF in the iterative process is estimated and updated, which is used for iterative calculation.

Abstract The Naval Nose Landing Gear (NLG) structural assembly consists of components with complex structural geometry and critical functionalities. The landing gear components are subjected to high static and dynamic loads, so they must be appropriately designed, dimensioned, and made by materials with mechanical characteristics that meet high strength, stiffness, and less weight requirements. This article contributes to the shape, size, and material optimization for the NLG of a supersonic naval aircraft for the estimated static loads. The estimated modal frequency values of the NLG assembly using Finite Element Analysis (FEA) software were compared with available Ground Vibration Test data of an aircraft to literally prove the accuracy and suitability of finite element (FE) model that can be used for any further analysis.

Abstract From the fact that a propulsor consumes less power for a given thrust if the inlet air is slower, simulations are conducted for a propulsor imposed behind an airfoil as ideal boundary layer ingestion (BLI) propulsor to stand on the benefits of this configuration from the point of view of power and efficiency and to get a closer look on the mutual interaction between them. This interaction is quantified by the impact on three main sets of parameters, namely, power consumption, boundary layer properties, and airfoil performance. The position and size of the propulsor have great influence on the flow around the airfoil. Parametric studies are carried out to understand their influence. BLI propulsor directly affects the power saving and all of the pressure-dependent parameters, including lift and drag. For the present case, power saving reached 14.4% compared to the propeller working in freestream.

Abstract Jet engine hot parts (e.g., jet nozzle) are a crucial source of aircraft’s infrared (IR) signature from the rearview, in 1.9-2.9 μm and 3-5 μm bands. The exhaust nozzle design used in a jet aircraft affects its performance and IR signature (which is also affected just by performance) from the engine layout. For supersonic aircraft (typically for M ∞ > 1.5), a converging-diverging (C-D) nozzle is preferred over a convergent nozzle for optimum performance. The diverging section of the C-D nozzle has a full range of visibility from the rearview; hence, it was not considered a prudent choice for low IR observability. This theoretical study compares the IR signature of the C-D nozzle with that of the convergent nozzle from the rearview in 1.9-2.9 μm and 3-5 μm bands for the same thrust.

Abstract This research developed methods for a virtual operator model (VOM) to learn the optimal control inputs for operation of a virtual excavator. Virtual design, used to model, simulate, and test new features, has often been limited by the fidelity of the virtual model of human operators. Human operator learns, over time, the capability, limits, and control characteristics of new vehicles to develop the best strategy to maximize the efficiency of operation. However, VOMs are developed with fixed strategies and for specific vehicle models (VMs) and require time-consuming re-tuning of the VOM for each new vehicle design. Thus, there typically is no capability to optimize strategies, taking account of variation in vehicle capabilities and limitations. A VOM learning capability was developed to optimize control inputs for the swing-to-pile task of a trenching operation. Different control strategies consisted of varied combinations of speed control, position control, and coast.

Abstract A number of semi-deterministic and stochastic formulations of multi-degree of freedom, frequency domain load models for heavy truck chassis are proposed and evaluated. The semi-deterministic models aim at reproducing the damage of a specific vehicle, while the stochastic ones aim to describe a collection of vehicle loads. The stochastic models are divided into two groups: Monte Carlo based and models based on single spectrum matrices. In both cases, the objective is to provide a load model that may be used to produce a design with a certain probability of survival. The goodness of the models is evaluated through a comparison of their damage outcomes with the corresponding damages of a set of time domain loads. This original time domain load set consists of chassis accelerations collected from seven physical trucks.

Abstract Vehicle rolling resistance and weight are two of the factors that affect fuel economy. The vehicle tire rolling resistance has a more significant influence than aerodynamics drags on fuel economy at lower vehicle speeds, particularly true for medium- and heavy-duty trucks. Less vehicle weight reduces inertia loads, uphill grade resistance, and rolling resistance. The influence of weight on the fuel economy can be considerable particularly in light- to medium-duty truck classes because the weight makes up a larger portion of gross vehicle weight. This article presents an empirical investigation and a numerical analysis of the influences of rolling resistance and weight on the fuel economy of medium-duty trucks. The experimental tests include various tires and payloads applied on a total of 21vehicle configurations over three road profiles. These tests are used to assess the sensitivity of rolling resistance and weight to the vehicle fuel economy.

Abstract In this study, an attempt is made to deduce the number of teeth in the driven sprocket of a Formula SAE (FSAE) car using Optimum Lap software based on track run simulation of the car, which comes out to be 51 teeth. The sprocket material was selected as Aluminum Alloy AL-7075 T6 because of its strength-to-weight ratio. In addition to it, the generative design strategy by Fusion-360 was utilized to automatically engender the slotted sprocket design on the ground of stress induced on it during operation. Furthermore, the design was verified virtually carrying out static structural and fatigue analysis under the worst-case scenario in CAE software. The overall weight reduction achieved was around 45%. Furthermore, the center-to-center distance between the sprockets and the number of chain links required were also calculated on the basis of space constraints and the wrap angle of the sprocket.

Abstract This article presents the application of the Life Cycle Sustainability Assessment (LCSA) methodology for integrating environmental, economic, and social assessment results by the direct application of Fuzzy-Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The aim of this work is to test the applicability of LCSA methodology as a potential tool to support the design phase, providing solutions tailored to its application in the automotive sector. To validate the proposed procedure, two alternative design solutions for a car dashboard are used as case study. In response to the need of methods and tools for evaluating and comparing sustainability of alternative design solutions, LCSA is seen as one of the most promising method, but which needs further testing with real cases to solve some methodological challenges.

Abstract Maximum lifetime and minimum manufacturing cost for new products are the primary goals of companies for competitiveness. These two objectives are contradictory and the geometric dimensions of the products directly control them. In addition, the earlier design errors of new products are predicted, the easier and more inexpensive their rectification becomes. To achieve these objectives, we propose in this article a novel model that makes it possible to solve the problem of optimizing the lifespan and the manufacturing cost of new products during the phase of their design. The prediction of the life of the products is carried out by an energy damage method implemented on the finite element (FE) calculation by using the ABAQUS software. The manufacturing cost prediction is carried out by applying the ABC cost estimation analytical method. In addition, the optimization problem is solved by the method of genetic algorithms.

Abstract The preliminary gas turbine combustor design process uses a huge amount of empirical correlations to achieve more optimized designs. Combustion efficiency, in relation to the basic dimensions of the combustor, is one of the most critical performance parameters. In this study, semi-empirical correlations for combustion efficiencies are examined and correlation coefficients have been revised using an experimental air-blasted tubular combustor that uses JP8 kerosene aviation fuel. Besides, droplet diameter and effective evaporation constant parameters have been investigated for different operating conditions. In the study, it is observed that increased air velocity significantly improves the atomization process and decreases droplet diameters, while increasing the mass flow rate has a positive effect on the atomization—the relative air velocity in the air-blast atomizer increases and the fuel droplets become finer.