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The most common and lethal weapons against military vehicles are the improvised explosive devices (IEDs). In an explosion, critical cabin’s penetrations and high accelerations can cause serious injuries and death of military personnel. This investigation uses single and multi-fidelity Bayesian optimization (BO) to design sandwich composite armors for blast mitigation. BO is an efficient methodology to solve optimization problems that involve black-box functions. The black-box function of this work is the finite element (FE) simulation of the armor subjected to blast. The main two components of BO are the surrogate model of the black-box function and the acquisition function that guides the optimization. In this investigation, the surrogate models are Gaussian Process (GP) regression models and the acquisition function is the multi-objective expected improvement (MEI) function. Information from low and high fidelity FE models is used to train the GP surrogates.

To study the generated axial force (GAF) of the drive shaft system more accurately and effectively, this paper introduces the interval uncertainty into the research focusing on the GAF. Firstly, an interval uncertainty model for calculating the GAF is proposed based on the Chebyshev polynomials and an analytical model of the GAF. The input torque, the articulation angle, the rotation angle of the drive shaft system, the pitch circle radius (PCR) of the tripod joint and the friction coefficient are regarded as interval variables. Secondly, the upper and lower bounds of the proposed GAF model under interval uncertainty parameters are calculated quickly with the vertex method. Then the interval uncertainty optimization of the GAF under uncertainty parameters is performed. The upper bound of the response interval of the GAF is taken as the optimization object.

Sliding mode control with a disturbance observer (SMC-DO) is proposed for suppressing the sprung mass vibration in a quarter-car with double-wishbone active suspension system (ASS), which contains the geometry structure of the upper and lower control arms. The governing equations of double-wishbone ASS are obtained by the balance-force analysis of the sprung mass in ASS. Considering uncertainties in damping, stiffness, and external disturbance acting on the sprung mass, we design a disturbance observer based on a sliding mode control (SMC) to estimate these uncertainties under the unknown road excitation. By the Lyapunov minimax approach, the uniform boundedness and the uniform ultimate boundedness of ASS with the proposed control are rigorously proved. Through co-simulation of ADAMS software and MATLAB/Simulink software, the sprung mass acceleration of ASS can be obtained with and without the proposed control.

During the operation of the ball joint, its service life and transmission efficiency are affected by the internal friction. Taking the ball joint as the research object, based on fractal theory, the friction between the steel ball and the raceway inside the ball joint of an automotive drive shaft system is studied in this paper. During the analysis, the friction between the steel ball and the arc raceway is regarded as the friction between a sphere and an arc raceway surface. In order to describe the friction state more accurately, this paper proposes a correction coefficient to modify the distribution function of contact asperities in the plane, and obtains the distribution function of contact asperities between the sphere and the arc raceway surface. The correction coefficient is related to the load, the size parameters and the material parameters of the steel ball and the raceway.

Excessive vibration and poor controllability occur in many mobile fluid power applications, with negative consequences as concerns operators' health and comfort as well as machine safety and productivity. This paper addresses the problem of reducing oscillations in fluid power machines presenting a novel control technique of general applicability. Strong nonlinearities of hydraulic systems and the unpredictable operating conditions of the specific application (e.g. uneven ground, varying loads, etc.) are the main challenges to the development of satisfactory general vibration damping methods. The state of the art methods are typically designed as a function of the specific application, and in many cases they introduce energy dissipation and/or system slowdown. This paper contributes to this research by introducing an energy efficient active damping method based on feedback signals from pressure sensors mounted on the flow control valve block.

Design of powertrain mounting bracket is always challenging in achieving good NVH characteristics, sound durability and simultaneously reduced weight. Structural optimization is an effective tool to obtain an optimum design. Depending on the design status, different schemes, i.e. size, topology and shape optimization, are applied. In this paper, a case study of application of structural optimization in the design of a mount bracket has been presented. Firstly, both test and FEA (Finite Element Analysis) results expose problems of the initial design. Therefore, it is necessary to redesign the bracket. With sufficient design freedom and time in topology optimization, design space and optimization parameters are defined. Die direction and other manufacturability considerations for the casting components are vital. Shape optimization is then conducted to further decrease the weight and refine local weakness.

The optimal design of hybrid-electric vehicle power systems poses a challenge to the system analyst, who is presented with a host of parameters to fine-tune, along with stringent performance criteria and multiple design objectives to meet. Herein, a methodology is presented to transform such a design task into a constrained multi-objective optimization problem, which is solved using a distributed evolutionary algorithm. A power system model representative of a series hybrid-electric vehicle is considered as a paradigm to support the illustration of the proposed methodology, with particular emphasis on the power system's time-domain performance.

The need for greater capacity in automotive transportation (in the midst of constrained resources) and the convergence of key technologies from multiple domains may eventually produce the emergence of a “swarm” concept of operations. The swarm, a collection of vehicles traveling at high speeds and in close proximity, will require management techniques to ensure safe, efficient, and reliable vehicle interactions. We propose a shared-autonomy approach in which the strengths of both human drivers and machines are employed in concert for this management. A fuzzy logic-based control implementation is combined with a genetic algorithm to select the shared-autonomy architecture and sensor capabilities that optimize swarm operations.

The characteristics of suspension elastic elements (i.e., spring, damper and anti-roll bar) are directly related to the handling and ride comfort performances, how to tune the characteristics of suspensions' elastic elements is always a big issue in developing the chassis of a vehicle. In this paper, a multi-body dynamics model of a passenger car within MSC.ADAMS® is integrated with iSight FD®, an optimization tool, to carry out a multi-objective optimization for improving the behavior of vehicle handling and ride comfort. The characteristics of suspension elastic elements (i.e., spring, damper and anti-roll bar) are considered as design variables. For handling, the objectives are defined by the measurements from multi-body dynamics simulation of typical double lane change according to ISO3888 standard. For ride comfort, the frequency-weighted RMS (Root Mean Square) value of vertical acceleration of the front seat rail according to ISO2631 standard is set as the objective.

This paper describes the numerical modeling of the hydraulic circuit of a self-moving boom lift. Boom lifts consist of several hydraulic actuators, each of them performs a specific movement. Hydraulic systems for lifting applications must ensure consistent performance no matter what the load and how many users are in operation at the same time. Common solutions comprise a fixed or a variable displacement pump with load-sensing control strategy. Instead, the hydraulic circuit studied in this paper includes a fixed displacement pump and an innovative (patented) proportional valve assembly. Each proportional valve (one for each user) permits a flow regulation for all typical load conditions and movement simultaneously. The study of the hydraulic system required a detailed modeling of some components such as: the overcenter valves, for the control of the assistive loads; the proportional valve, which keeps a constant flow independently of pressure drop across itself.

A methodology for modeling elastomeric mounts as nonlinear lumped parameter models is discussed. A key feature of this methodology is that it integrates dynamic test results under different conditions into the model. The first step is to model the mount as a linear model that is simple but reproduces accurately results from dynamic tests under small excitations. Frequency Response Functions (FRF) enables systematic calculation of the parameters for the model. Under more realistic excitation, the mount exhibits non-linearity, which is investigated in the next step. For nonlinear structures, a simple and intuitive method is to use time-domain force-displacement (F-x) curves. Experiments to obtain the F-x curves involve controlling the displacement excitation and measuring the induced forces. From the F-x curves, stiffness and damping parameters are obtained with an optimization technique.

This paper presents the continuation of the modeling work described in a companion paper “Modeling of Nonlinear Elastomeric Mounts. Part 1: Dynamic Testing and Parameter Identification” by the same authors. That paper discussed a dynamic test procedure and an optimization methodology to identify and model an elastomeric mount as a non-linear lumped parameter structure. This paper discusses a numerical modeling methodology to confirm or improve the agreement between the dynamic test results and the input-output relationship of the analytical model generated in the companion paper. In this paper, the model developed in the companion paper and the model parameters are input into a dynamic simulation model using a commercial simulation package. The model is then run to produce the numerical force-versus-displacement (F-x) curves of the mount. The numerical F-x curves are compared with the F-x curves obtained from the experiments.

In this paper, an aggregate system level modeling and analysis framework is proposed to facilitate the integration and design of advanced life support systems (ALSS). As in process design, the goal is to choose values for the degrees of freedom that achieve the best overall ALSS behavior without violating any system constraints. At the most fundamental level, this effort will identify the constraints and degrees of freedom associated with each subsystem and provide estimates of the system behavior and interactions involved in ALSS. This work is intended to be a starting point for developing insights into ALSS from a systems engineering point of view. At this level, simple aggregate static input/output mapping subsystem models from existing data and the NASA ALS BVAD document are used to debug the model and demonstrate feasibility.

An important function of life support systems developed for a long duration human mission to Mars is the ability to recycle water and air. The Bio-Regenerative Environmental Air Treatment for Health (BREATHe) is part of a multicomponent life support system and will simultaneously treat wastewater and air. The BREATHe system will consist of packed bed biofilm reactors. Model waste streams will be used for experiments conducted during the design phase of the BREATHe system. This paper summarizes expected characteristics of water and air waste steams that would be generated by a crew of six during a human mission to Mars. In addition to waste air and water generation rates, the chemical composition of each waste stream is defined. Specifically, chemical constituents expected to be present in hygiene wastewater, dishwater, laundry water, atmospheric condensate, and cabin air are presented.

Design optimization for functionality, and manufacturability was virtually impossible in the past. However, recent standardization of file storing formats resulted in seamless data transfer from one software package to another; thus, allowing integration of all facets of product design optimization. This paper describes a metalcasting design optimization process. It focuses on the design of cast parts according to functional requirements while optimizing shape with respect to structural integrity, while ascertaining that the part can be manufactured (cast) without defects.

With the need for improvement in the fuel economy along with reduction in emissions due to stringent regulations, powertrain hybridization has become the focal point of research for the automotive sector. Hydraulic hybrids have progressively gained acceptance due to their high power density and low component costs relative to their electric counterpart and many different architectures have been proposed and implemented on both on and off-highway applications. The most commonly used architecture is the series hybrid which offers great flexibility for implementation of power management strategies. But the direct connection of the high pressure accumulator to the system often results in operation of the hydraulic units in high pressure and low displacement mode. However, in this operating mode the hydraulic units are highly inefficient. Also, the accumulator renders the system highly compliant and makes the response of the transmission sluggish.

This work proposes a new method to design crashworthiness structures that made of functionally graded cellular (porous) material. The proposed method consists of three stages: The first stage is to generate a conceptual design using a topology optimization algorithm so that a variable density is distributed within the structure minimizing its compliance. The second stage is to cluster the variable density using a machine-learning algorithm to reduce the dimension of the design space. The third stage is to maximize structural crashworthiness indicators (e.g., internal energy absorption) and minimize mass using a metamodel-based multi-objective genetic algorithm. The final structure is synthesized by optimally selecting cellular material phases from a predefined material library. In this work, the Hashin-Shtrikman bounds are derived for the two-phase cellular material, and the structure performances are compared to the optimized structures derived by our proposed framework.

The trajectory planning and the accurate path tracking are the two key technologies to realize the intelligent driving. The research of the steering wheel angle plays an important role in the path tracking. The purpose of this study is to optimize the steering wheel angle input during the automated lane changing. A dynamic programming approach to trajectory planning is proposed in this study, which is expected to not only achieve a quick reaction to the changing driving environment, but also optimize the balance between vehicle performance and driving efficiency. First of all, the lane changing trajectory is planned based on the positive and negative trapezoidal lateral acceleration method. In addition, the multi-objective optimization function is built which includes such indexes: lateral acceleration, lateral acceleration rate, yaw rate, lane changing time and lane changing distance.

Diesel engine cylinder deactivation (CDA) can be used to reduce petroleum consumption and greenhouse gas (GHG) emissions of the global freight transportation system. Heavy duty trucks require complex exhaust aftertreatment (A/T) in order to meet stringent emission regulations. Efficient reduction of engine-out emissions require a certain A/T system temperature range, which is achieved by thermal management via control of engine exhaust flow and temperature. Fuel efficient thermal management is a significant challenge, particularly during cold start, extended idle, urban driving, and vehicle operation in cold ambient conditions. CDA results in airflow reductions at low loads. Airflow reductions generally result in higher exhaust gas temperatures and lower exhaust flow rates, which are beneficial for maintaining already elevated component temperatures. Airflow reductions also reduce pumping work, which improves fuel efficiency.

This work presents the implementation of the Efficient Global Optimization (EGO) approach for the design of composite materials under dynamic loading conditions. The optimization algorithm is based on design and analysis of computer experiments (DACE) in which smart sampling and continuous metamodel enhancement drive the design towards a global optimum. An expected improvement function is maximized during each iteration to locate the designs that update the metamodel until convergence. The algorithm solves single and multi-objective optimization problems. In the first case, the penetration of an armor plate is minimized by finding the optimal fiber orientations. Multi-objective formulation is used to minimize the intrusion and impact acceleration of a composite tube. The design variables include the fiber orientations and the size of zones that control the tube collapse.