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This paper describes the application of eye tracking technology in the automotive industry in the context of vehicle assessment in customer clinics. The paper presents the mentioned technology, the applied experimental methodology and selected results. In particular, the hypotheses that were expressed during the research of the topic and during the preparation of the experiment are answered. In this way, the innovative technology of eye tracking can be used to reflect the "voice of the customer" in the vehicle design. [ABSTRACT FROM AUTHOR]

The research paper "Eye-tracking technology in automotive industry" describes the implementation of eye-tracking technology into the development of new vehicles and their decisionmaking process. This objective technology tracks the eye movement of a participant, detects where the subject is looking during an interval of an experiment, and thus offers a wide range of applications. It can be used to detect distractions while driving on a simulator under a certain workload or to record objective data during an otherwise subjective customer-oriented clinic. In this topic, we evaluate areas of the vehicle which are the most interesting for customers, and therefore provide support and recommendations for new vehicle designs. [ABSTRACT FROM AUTHOR]

The article presents information on the development of Starship spacecraft by private rocket company SpaceX. Topics discussed include the plan of U.S. National Aeronautics and Space Administration's (NASA) Ames Research Center planetary scientist Jennifer Heldmann to use Starship to probe lunar ice, the failure of NASA's Lunar Crater Observation and Sensing Satellite mission, and the objectives of SpaceX chief executive officer Elon Musk in developing Starship.

Driving style has been proposed to be a critical factor in automated driving. However, the role of driving style in the process of taking over during automated driving needs further investigation. The main purpose of this study was to investigate the influence of driving style on takeover performance under the influence of warning system factors. In addition, this study also explored whether the impact of driving style on reaction time varies over time and the role of driving style on a comprehensive takeover quality indicator. Two driving simulation experiments with different takeover request (TOR) designs were conducted. In experiment 1, content warning information was provided in the TOR with different warning stage designs; in experiment 2, countdown warning information was provided in the TOR with different warning stage designs. Sixty-four participants (32 for experiment 1 and 32 for experiment 2) were classified into two groups based on their driving style (i.e., aggressive, or defensive) using the Chinese version of the Multidimensional Driving Style Inventory (the brief MDSI-C). The results suggested that drivers' driving style had significant effects on takeover performance, but the effects were influenced by warning system designs. Specifically, defensive participants performed better takeover performance, i.e., shorter reaction time and cautious vehicle control behaviors, than aggressive participants in most warning conditions. The content and countdown warning information and warning stage design affected the roles of driving style on takeover performance: 1) compared to the one-stage warning design, the two-stage warning design significantly shortened the reaction time of the participants with different driving styles, 2) compared to the countdown warning information design, the design of content warning information can shorten the reaction time of aggressive participants and lengthen the reaction time of defensive participants in the two-stage warning conditions, and 3) compared to the content warning information design, countdown warning information can improve the safe takeover performance of defensive participants. This study provides a better understanding of the role of driving style on takeover performance, and driving style should be considered when designing warning systems for autonomous vehicles. [ABSTRACT FROM AUTHOR]

İnterior design deals with the construction of any volume that is limited in the infinite space and that interacts with the user. The main purpose of the interior design is to arrange the volume in a way that allows users to use them in the most efficient way. However, several requirements in the interior design and their outcomes vary. Aside from the functional difference, this variability is due to the needs and priorities that need to be met in a limited volume. This "limited space design" requirement applies to all mobile venue-structure types. This requirement was considered as a design problem and military submarines, where a large number of crew members had to live together for a long time, were chosen as the subject of study. The insufficiency of the studies related to the interior design of military vehicles and the need to make a contribution to this field were influential in this choice. In this study, all military submarines were kept within the scope of the study, regardless of class, and interior design approaches were examined within the scope of ergonomics principles. [ABSTRACT FROM AUTHOR]

Highlights the role of inventor John Ericsson in engineering the ironclad Monitor during 1861-1863. How Monitor was engineered; Design; Relations of Ericsson with the Navy Department's Bureaus of Construction and Repair and of Steam Engineering; Wars fought by Monitor; Triumphs of Ericsson.

Electric hydraulic power steering (EHPS) system has been widely used in large and medium cars, which plays an important role in determining the energy loss, driving safety and driving comfort of vehicles. This work mainly discusses the parameter design of the EHPS system based on the multi-objective optimization method. Since there is no explicit standard for the performance indexes of EHPS system, this work takes the energy consumption, steering road feel, steering sensibility and steering stability as the main performance indexes of EHPS system. The quantization formula of each performance index is explored and deduced. Based on these, a multi-objective optimization model is established. Then, the non-dominated sorting genetic algorithm-III based on fitness function (NSGA-III-FF) is proposed, which has better convergence than the original non-dominated sorting genetic algorithm-III (NSGA-III). Besides, the technique for order preference by similarity to an ideal solution (TOPSIS) is applied to select the ideal optimization solution. Simulation results show that the NSGA-III-FF enhances the comprehensive performance of the EHPS system, which can successfully achieve the goal of multi-objective optimization for steering flexibility, steering road feel, and steering energy loss while ensuring the steering stability. [ABSTRACT FROM AUTHOR]

• Efficient sequential approximate optimization method is developed for hypersonic vehicle design. • An experimental design method for constrained design space is developed. • A novel adaptive infill strategy based on inaccurate search is proposed. • Satisfactory optimization results are obtained at very low costs. • The proposed framework can be helpful for researchers in aerodynamic optimization field. Hypersonic vehicles are receiving increased attention within the aerospace community due to their high cruise speed and long-range capabilities. In this paper, a modified Sequential Approximate Optimization method is proposed for an optimized aerodynamic design of a hypersonic vehicle. As part of this approach, a constrained experimental design method is developed to handle the constraints more efficiently. A radial basis function is used to surrogate time-consuming CFD analysis. An efficient and more robust numerical mesh morphing scheme for the hypersonic vehicle is developed for the generation of high-quality meshes. Within this paper, a novel adaptive infilling strategy is proposed which uses an inaccurate search technique coupled with an elite archive. This allows the location of a more promising sample region and hence improves the surrogate accuracy, thereby further enhancing the optimization efficiency. A hypersonic vehicle aerodynamic design problem is solved using the proposed approach and satisfactory results are obtained at much lower computational costs. The lift-to-drag ratio is increased by 23.8% when compared with the base configuration while also satisfying the volume and lift constraints. The pressure and Mach contours have been compared with those of the base configuration and the results demonstrate the strength of the optimized configuration. The modified sequential approximate optimization for designing an improved hypersonic vehicle is worth referencing in future work. [ABSTRACT FROM AUTHOR]

• An autonomous vehicle (AV) incentive program includes AV lanes and purchase subsidy. • A model framework is proposed to consider the uncertainty of AV purchase price. • Numerical experiments are conducted to demonstrate the proposed models. This study proposes an autonomous vehicle incentive program design (AV-IPD) problem for a local government, which aims to promote the adoption of autonomous vehicles (AVs) by deploying AV lanes and subsidizing the purchase of AVs with the objective of system optimum subject to a fixed budget. As it is difficult to anticipate the changing AV market conditions in the future, we take into account the uncertainty in AV purchase price. For the AV-IPD problem, we firstly decide which regular lanes should be converted into exclusive AV lanes. Secondly, we determine the AV purchase subsidy for each realization of AV purchase price with a given AV lane deployment scheme. A binary logit model is applied to characterize the vehicle choice behavior of users. The AV-IPD problem is formulated as a two-stage stochastic programming model with equilibrium constraints. To solve the AV-IPD problem, we develop a solution method based on linear approximation techniques and duality theories. Numerical experiments are conducted to demonstrate the effectiveness of the proposed model and solution method. [ABSTRACT FROM AUTHOR]

An inverse design methodology on a waverider is proposed under strong geometric constraints on the basis of the generation method of an arbitrarily-shaped shock wave to obtain an improved performance. First, the generation method of the body contour that can form an arbitrarily-shaped shock wave is introduced in detail based on the method of characteristics. The effectiveness and accuracy of the generation method are verified through numerical simulation. Second, with the aid of the generation method, an inverse design method on waveriders under strong geometric constraints is presented. The waverider designed by the proposed method can satisfy the geometric constraints completely. Then, the influences of the shock wave shapes on the performance of the waveriders are studied through numerical simulation. In comparison with a traditional cone-derived waverider, the waverider based on the shock wave with convex quality can considerably increase the aerodynamic performance under the current geometric constraints. Conversely, the shock wave with concave quality deteriorates the aerodynamic performance of waveriders. The volumetric efficiency can also be improved with the adoption of the shock wave with concave quality. In conclusion, the numerical simulation result demonstrates that the proposed waverider design method can provide an increased flexibility and meet the different requirements of an actual design of hypersonic vehicles in geometric constraints and aerodynamic performances. • A design method of waveriders under strong geometric constraints is proposed. • The proposed design method is based on the generation of predefined shock waves. • The generation method of the shock wave is based on MOC and is verified by CFD tools. • The effectiveness and accuracy of the proposed method is verified by CFD tools. • The predefined shock waves show great influence on the waverider performances. [ABSTRACT FROM AUTHOR]

• Solar PV prosumers to play a vital role in the global energy transition. • Annual energy costs of PV prosumers much less compared to grid supply by 2050. • First global study to analyse PV prosumers with a range of complementary storages. • Threshold for economical maximum battery capacity per installed PV capacity is estimated. • Self-consumption ratios, demand cover ratios and heat cover ratios presented. Globally, PV prosumers account for a significant share of the total installed solar PV capacity, which is a growing trend with ever-increasing retail electricity prices. Further propelled by performance improvements of solar PV and innovations that allow for greater consumer choice, with additional benefits such as cost reductions and availability of incentives. PV prosumers may be one of the most important enablers of the energy transition. PV prosumers are set to gain the most by maximising self-consumption, while avoiding large amounts of excess electricity being fed into the grid. Additionally, electricity and heat storage technologies, heat pumps and battery electric vehicles are complementary to achieve the highest possible self-consumption shares for residential PV prosumer systems, which can reach grid-parity within this decade in most regions of the world. This research finds the cost optimal mix of the various complementary technologies such as batteries, electric vehicles, heat pumps and thermal heat storage for PV prosumers across the world by exploring 4 different scenarios. Furthermore, the research presents the threshold for economical maximum battery capacity per installed PV capacity, along with self-consumption ratios, demand cover ratios and heat cover ratios for 145 different regions across the world. This is a first of its kind study to conduct a global analysis of PV prosumers with a range of options to meet their complete energy demand from a future perspective, up to 2050. Maximising self-consumption from solar PV generation to meet all energy needs will be the most economical option in the future, for households across most regions of the world. [ABSTRACT FROM AUTHOR]

Abstract This paper presents the failure and fatigue analysis results of a coil spring removed from a personal vehicle after having failed in service. Using experimental procedures like visual observations, optical and scanning electron microscopy, the failed coil was examined in order to determine the causes of the fracture. Furthermore, the chemical composition of the material was determined and a hardness test performed. It was concluded that the continuous contact between the coils formed corrosion pits that served as crack initiation points leading to the final fracture. Based on these findings, the finite element model of the coil spring was built to run the stress analysis under stochastic variable dynamic loading. The quarter car model was used for the assessment of vehicle behaviour under dynamic loading. Matlab numerical routine was used to perform rainflow counting as well as Miner's cumulative damage assessment in accordance with Goodman failure criterion. The obtained results give prediction of the spring fatigue life. The results can be useful in the further design optimization of motor vehicle coil springs. Highlights • Failure and fatigue analysis results of a personal vehicle coil spring • Causes of fracture determined using experimental procedures • Continuous contact between coils formed corrosion pits that served as crack initiation points • Finite element stress analysis under stochastical loading performed • Quarter car model used for assessment of vehicle behaviour under dynamic loading and spring fatigue life prediction [ABSTRACT FROM AUTHOR]

The mountain tram is an environmentally friendly transportation system that is driven wirelessly on an embedded track constructed on former mountain roads. While it has a number of strong points, including being able to be driven in spite of a frozen road, some difficulties are caused on sharp and steep tracks. In this study, after possible technical problems were defined in mountain trams driven on sharp and steep tracks, design solutions for the coupling structure of bogie and car body were proposed. In addition, a prototype was made and its performance was tested to verify the solution. Since the distance difference of inner and outer rails on the sharp curve is severe enough to interrupt running, independently rotating wheels with different angular speeds were developed and applied. To prevent derailment due to large attack angle and lateral force caused by the previous vehicle in a 2-bogie-1-carbody design on a sharp curve, a 1-bogie-1-carbody vehicle was designed and applied. A prototype 1-bogie-1-carbody vehicle with independent rotating wheels was made to prove the performance during test drives on a small track. To absorb the large rotations of 3 degrees-of-freedom between the car bodies of a mountain tram driven on the steep curved track, a coupler was designed. After a small scale prototype was made, the performance was verified through a function test. [ABSTRACT FROM AUTHOR]

Abstract This paper presents the methodology and the optimization strategy applied by Bertin Technologies for over 10 years to perform space launch vehicle design and implemented by using the property software platform HADES V15.0. The problem formulation consists of finding the best launch vehicle concept i.e. the one minimizing launch cost while satisfying technical, mission and architecture constraints (payload mass on final orbit, number of stages, propulsive technologies ...). The strategy is based on a Multidisciplinary Design Feasible (MDF) approach coupled with the use of Genetic Algorithms (GA) for global optimization, and Gradient-Based Algorithms for final tuning and results refining. The HADES V15.0 platform provides the associated software environment, integrating a number of technical and economic modules consistently interconnected within a system optimization loop. The main disciplines taken into account in the platform are related to the launcher's propulsion, structure, aerodynamics, trajectory optimization and costs. The use of an integrated platform for multi-objective and multi-disciplinary optimization enables an efficient process and quick optimization. This methodology is particularly well fitted to the design of a small space launch vehicle, allowing to take into account the multidisciplinary nature of such a complex system and to manage the inherent sensitivity for this kind of vehicle. This platform was used specifically to design Bertin Technologies' cost-effective expandable Space Launch Vehicle (SLV) for Microsatellites, ROXANE, and to design the space launch vehicle in the H2020 ALTAIR project. Highlights • Development of a software platform to preliminary design space launch vehicle. • Multidisciplinary design optimization applied to space launch vehicle. • Optimization of twelve space launch vehicles for a minimum launch cost. • Application to the designs of two space launch vehicle, ROXANE and ALTAIR. [ABSTRACT FROM AUTHOR]

Traditionally, the main structural components of land transport vehicles, e.g. passenger vehicles and trucks, have been made of metals such as steel and aluminium. As the number of vehicles increases on the road, global effort to reduce pollutant emission has put pressure on the vehicle manufacturers to design and manufacture fuel-efficient vehicles using strong and light-weight structures made of materials such as fibre-reinforced polymer composite (FRP) laminates [1]. For instance, with regard to the new Volvo performance car, Polestar 1, a majority of the parts in the upper body, including doors, bonnet and boot lid, are made of carbon FRP (CFRP) laminates [2]. Interestingly, this design not only provides for maximum stiffness and lightness, but reduces the weight of the upper body, lowers the vehicle's centre of gravity that results in enhanced handling, performance and drivability [2]. [ABSTRACT FROM AUTHOR]

Highlights • General-purpose multibody simulation (GPMBS) software packages cannot be directly employed to simulate railway vehicle dynamics but have a lot of inherent advantages compared with specialized railway vehicle dynamics simulation software. This paper proposes a framework to make it possible to use GPMBS software packages to simulate railway vehicle dynamics. • A multi-language supported loose coupling method is presented for integrating the self-developed force element programs into GPMBS software packages. • A strategy combing the top-down approach and the sub-mechanism feature is recommended to construct the railway vehicle dynamics design and simulation model. Abstract In terms of simulation efficiency, modelling and visualization, general-purpose multibody simulation (GPMBS) software packages have a lot of inherent advantages compared with specialized railway vehicle dynamics simulation software packages. However, their application is limited due to the absence of specialized force elements and contact models, and thus cannot be directly employed for railway vehicle dynamics simulation. To deal with this issue, this paper proposes a novel framework to use GPMBS software packages to simulate the dynamic behavior of the railway vehicle. This framework contains a loose coupling method, a sub-mechanism feature and a top-down modelling method and allows users to take full advantage of the advanced functionalities of the GPMBS software packages to improve the efficiency of railway vehicle dynamics simulation. The feasibility of this framework is verified by integrating extensions for two representative GPMBS software packages. In addition, the two comparisons between the self-developed extensions (for LMS Virtual.Lab Motion and Unity3D) and the widely used specialized railway vehicle dynamics simulation software (Simpack and Universal Mechanism), further confirm the validity of the framework. [ABSTRACT FROM AUTHOR]

As engineers increasingly pursue air vehicle designs with slender, lightweight aerostructures, it has become necessary to model nonlinear aeroelastic effects earlier in the design process. As a result, high-fidelity analysis tools are required that can efficiently identify flutter within the flight envelope, and find design modifications to alleviate adverse aeroelastic behavior. To address these requirements, we have systematically evaluated automated methods to identify the damping of an aeroelastic system from a time-domain simulation. The techniques evaluated include the log decrement method, envelope function methods that use the Hilbert transformation, the half-power bandwidth method, and the matrix pencil method. The optimal approach was determined to be the matrix pencil method due to its robustness to noise and its ability to handle multi-component signals over short time simulations. Identification of the flutter boundary of the AGARD-445.6 wing is demonstrated with an automated method based on the adjoint sensitivities and the matrix pencil method. While the matrix pencil method is robust, identification of the flutter boundary using gradient-based optimization is shown to be sensitive to the initial dynamic pressure guess. [ABSTRACT FROM AUTHOR]

Abstract To reduce energy consumption and environmental pollution, the Chinese government is vigorously promoting the adoption of electric vehicles (EVs). As one of the first demonstration and promotion cities for EVs in China, Beijing has played an important leading role in the promotion of EVs. Based on the theory of planned behavior (TPB), this study introduced consumer cognitive status, product perception, and incentive policy measures (non-monetary incentive policy measures and monetary incentive policy measures) to build a purchase intention influence mechanism model for EVs. A questionnaire survey was conducted from March to April of 2018 among potential consumers in Beijing. A total of 502 valid survey responses were obtained, and a structural equation model (SEM) was used for an empirical analysis of the factors influencing EV purchasing intention. The results show that attitude, perceived behavior control, cognitive status, product perception and monetary incentive policy measures have significant positive effects on consumers' intentions to purchase EVs in Beijing. However, subjective norms and non-monetary incentive policy measures have no significant impact on purchasing intention. In addition, the analysis results of the multi-group SEM show that there are significant differences in demographic variables (gender, age, education level, income, and ownership of cars) in the path of consumer purchase intention. Implications for policy makers and scope for further research are discussed. Highlights • TPB is expanded to include cognitive status and situational factors. • Attitude toward EVs has the largest significant and positive effect. • Subjective norms and non-monetary incentives have few significant effects. • Crowd characteristics affect purchasing intention for the consumer. [ABSTRACT FROM AUTHOR]

Highlights • Geometric design consistency is closely related to CO 2 emissions. • CO 2 emission rate increases as the geometric design consistency worse. • The design of consistent roads leads to environmentally sustainable highways. Abstract Highway vehicles driving on rural roads account for more than 50% of all CO 2 emissions produced by the transportation sector in Europe. Although the policy measures to mitigate Greenhouse Gas emissions are increasing, these do not include policies aimed at reducing emissions by means of highway geometric design, which significantly influences drivers' speeds and accelerations and, consequently, plays a major role on fuel consumption and emissions. Therefore, the main objective of this research is to study the influence of the geometric design consistency on vehicle CO 2 emissions. To do this, continuous speed data were collected on 47 homogeneous road segments by means of Global Positioning System devices. Vehicle CO 2 emissions were estimated by applying the VT-micro model, whereas geometric design consistency was assessed considering different global consistency models. As a conclusion, vehicle CO 2 emissions decreases as the consistency level of a homogeneous road segment increases. Specifically, a good consistency road segment has been found to present an emission rate 20–30% lower than a poor-consistent one. Therefore, the design of consistent roads allows, in addition to maximize road safety, to help to achieve more environmentally sustainable highways, reducing CO 2 emission production. [ABSTRACT FROM AUTHOR]

The high prediction accuracy of FEM calculations is an important prerequisite for their growing use in the field of crash load cases for vehicle body design. Although the simulation accuracy of crash calculations for steel structures already is at a high standard, continuous improvements and a further development of the simulation models are crucial in the field of vehicle design. Existing studies on the simulation accuracy for steel structures under crash load focus on the deformation behaviour of idealized component-like structures. These studies do not allow for conclusions on the simulation accuracy of crash calculations based on vehiclerelated components with increased geometric complexity as well as with different material combinations, joining techniques and bead structures. This was the reason for conducting the experimental and numerical investigations on crash boxes outlined in this paper. The goal was to investigate whether the FE code is capable of increasing the accuracy of the simulation of the experimental results by considering the information obtained from technical measurements. [ABSTRACT FROM AUTHOR]

Highlights • Experimental validation of a road roughness classification system. • Continuous classification of the driven road classes according to ISO 8608. • Onboard signals of two-wheeled vehicles are feasible for identifying customer usage profiles. • Development of an impact detection strategy using a machine learning approach. • Robust identification of service loads, mild special events, and severe special events. Abstract First, this publication presents the experimental validation of a road roughness classification method. Second, an impact detection strategy for two-wheeled vehicles is proposed including a classification of service loads, mild special events, and severe special events. The methods presented utilise the vehicle’s onboard signals to gather field data. The modular road roughness classification system operates with the vehicle’s transfer functions, and continuously classifies the road profile, according to ISO 8608. The method was successfully validated on test tracks with known road profiles. The impact detection strategy was developed using a supervised machine learning technique. Six road obstacles were ridden over using different velocities to invoke mild and severe special events. The most popular classifiers were trained for comparison and prediction of future observations. The developed impact detection strategy shows a high accuracy and was successfully validated using a k-fold cross-validation. The combination of the road roughness classification system and the impact detection strategy, enables a holistic field data acquisition of customer usage profiles, in the context of durability engineering. The collection of customer usage profiles improves vehicle design targets and enables a virtual load acquisition. [ABSTRACT FROM AUTHOR]

Particle swarm optimization, a widely used metaheuristic algorithm, mimics the cooperation behavior among species. The PSO algorithm has become a new trend owing to its simplicity and strong optimization capacity. However, premature convergence problem is also a serious issue for PSO comparable with other evolutionary algorithms. Diversity loss is generally known as one of the major causes. For enhancing the diversity of swarms during optimization procedure, an improved PSO algorithm named OLAR-PSO-d is proposed, which incorporates design of experiment technique as well as adaptive reset operator into standard PSO. The OLAR-PSO-d algorithm is compared with other 10 heuristic algorithms. The numerical experiments' results demonstrate the priority of OLAR-PSO-d both in optimization ability and algorithm stability. The proposed algorithm is also used in a vehicle lightweight design problem. The auto-body achieves 20.25 kg weight reduction with meeting all the performance requirements of crashworthiness. [ABSTRACT FROM AUTHOR]

To overcome the shortage of traditional rear axle compliance steering (RACS) technology, a kind of viscoelastic smart material is introduced into the rear suspension of a vehicle to construct rear wheel semiactive steering system. This article focuses on the nonlinear dynamic behavior of the vehicle with RACS incorporating viscoelastic smart material. First of all, considering the tire nonlinearity and the fractional derivative constitutive relation of the viscoelastic material, the nonlinear dynamic model of the vehicle with RACS is formulated. Then, the lateral dynamic behavior of the vehicle with RACS is demonstrated through numerical experiments. Finally, some factors that influence shimmy of the compliance steering wheel are investigated. Numerical results demonstrate the Hopf bifurcation characteristics of the vehicle with RACS and disclose the influence factors of Hopf bifurcation characteristics for the vehicle with RACS, which lay the theoretical foundation for the development of the rear wheel semiactive steering technology. [ABSTRACT FROM AUTHOR]

This study investigates the coupled ride and directional performance characteristics of an articulated frame-steered vehicle (AFSV). A three-dimensional multi-body dynamic model of the vehicle is formulated integrating the hydro-mechanical frame steering and hydro-pneumatic suspension (HPS) systems. The model parameters are obtained from field-measured data acquired for an unsuspended AFSV prototype and a validated scaled HPS model. The HPS is implemented only at the front axle, which supports the driver cabin. The main parameters of the HPS, including the piston area, and flow areas of bleed orifices and check valves, are selected through design sensitivity analyses and optimisation, considering ride vibration, and roll- and yaw-plane stability performance measures. These include the frequency-weighted vertical vibration of the front unit, root-mean-square lateral acceleration during the sustained lateral load transfer ratio period prior to absolute rollover of the rear unit, and yaw-mode oscillation frequency following a lateral perturbation of the vehicle. The results suggested that the implementation of the HPS to the front unit alone could help preserve the directional stability limits compared to the unsuspended prototype vehicle and reduce the ride vibration exposure by nearly 30%. The results of sensitivity analyses revealed that the directional stability performance limits are only slightly affected by the HPS parameters. Further reduction in the ride vibration exposure was attained with the optimal design, irrespective of the payload variations. The vehicle operation at relatively higher speeds, however, would yield greater vibration exposure. [ABSTRACT FROM AUTHOR]

This paper provides a complete design solution about adaptive optimal shaking vibration control for electric vehicles. A general 4-DOF and 5-order linear torsional vibration model is established under given wheel speed, and the frequency characteristics of the vibration system are elaborately analysed in terms of variation of wheel speed and different model parameters. Aiming at decreasing the shaking vibration at the least sacrifice of acceleration loss, and improving the robustness of the system against external disturbance, a combination of feed-forward and feed-backward adaptive control structure is proposed. Further, a non-linear multi-constraint optimisation problem is formulated for solving the optimal adaptive control variables within the two-dimensional design space composed of the wheel speed and driver's torque command. Furthermore, the distribution of the optimal adaptive control variables within the design space and its extended application under different tyre road conditions are discussed. Eventually, several simulation test cases are particularly designed to verify the performances of the controller on all aspects. Test results show that the optimal adaptive controller achieves satisfactory anti-shaking vibration, acceleration maintaining and robustness performances within the whole adaptive design space as desired. [ABSTRACT FROM AUTHOR]

Tepex continuous-fiber-reinforced thermoplastic composite semi-finished products are becoming increasingly popular in lightweight automotive design. Underbody components represent an important field of application with strong growth prospects. These components are manufactured in compression and flow molding processes using thermoplastic molding compounds. The semi-finished products serve as overlays, which significantly increase the mechanical performance of the compression-molded components while offering cost-effective component solutions. [ABSTRACT FROM AUTHOR]

Highlights • Experimental and theoretical methodology for data acquisition of unsteady thermal state. • Description of test equipment and the algorithm for solving the inverse heat conduction problem. • Study of carbon/carbon shell for its use as hot structure in application such as windward connections. Abstract The aim of this paper is to study a shell structure for space applications. The aim of the structure is to be reusable and thick. This first study will focus on thermal environment. Starting from a defined geometry, a prototype will be manufactured. Thermo-structural behavior of the structure will be analyzed by numerical analysis and tests. Thermal properties, such as thermal conductivity and heat capacity, will be studied by the use of the inverse method. A robust numerical approach, such as inverse method, is one of the best for this problem as many parameters concur for the determination of properties. Such approach permits to perform the parametric and structural identification of the model. These procedures are presented including both experimental investigation and methodical-numerical aspects. Special test equipment and the regularizing algorithm for solving the ill-posed inverse heat conduction problem are described. In the frame of thermal properties determination, a verification and prediction of thermocouple error will be performed. Developed in the frame of this work the experimental and theoretical methodology for complex data acquisition of unsteady thermal state of the prototype of shell structure is proposed. [ABSTRACT FROM AUTHOR]

This paper proposes a stochastic decision making problem for a wind power producer (WPP) in the day-ahead (DA) and balancing markets. In this problem, bidding strategy of the WPP in a competitive electricity market and also its participation to supply demand response (DR) and electric vehicle (EV) aggregators is determined to achieve the maximum profit. In this model, DR and EV aggregators are able to choose the most competitive WPP in such a way that their energy payments be minimized in the scheduling horizon. Therefore, the problem is formulated as a stochastic bi-level programming model with conflict objectives of the WPP and the aggregators. Moreover, owing to the uncertainties associated with market prices, offered prices by rival WPPs, demand of DR and EV aggregators, conditional value at risk (CVaR) is applied to the proposed model. The attained stochastic bi-level problem is transformed to a linear stochastic single level problem with equilibrium constraints using Karush–Kuhn–Tucker (KKT) optimality conditions. The proposed model is evaluated on a realistic case study and the impacts of risk-averse behavior and demand response participants on the decision making problem of the WPP are investigated. Numerical results indicate that with increasing DR participants of 0%, 60% and 100%, CVaR of WPP increases 33.81%, 40.79% and 46.99%, respectively. This means that if the loads are more responsive, the WPP tries to control the profit variability due to the uncertainties of loads. [ABSTRACT FROM AUTHOR]