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Tubular sections are found in many automotive structural components such as front rails, cross beams, and sub-frames. They are also used in other vehicular structures, such as buses and rails. In many of these components, smaller tubular sections may be joined together using an adhesive to build the required structure. For crash safety applications, it is important that the joined tube sections be able to provide high energy absorption capability and withstand the impact load before the adhesive bond failure occurs. In this study, single lap tubular joints between two aluminum tubes are investigated for their crush performance at both quasi-static and high impact speeds using finite element analysis. A crash optimized adhesive Betamate 1496 is considered. The joint parameters, such as adhesive overlap length, tube diameters and tube lengths, are varied to determine their effects on energy absorption, peak and mean loads, and tube deformation mode.

This paper proposes a new nonlinear model predictive control (NMPC) for autonomous vehicle path tracking problem. The vehicle is equipped with active rear steering, allowing independent control of front and rear steering. Traditional NMPC, which runs at fixed sampling rate, has been shown to provide satisfactory control performance in this problem. However, the high throughput of NMPC limits its implementation in production vehicle. To address this issue, we propose a novel event-triggered NMPC formulation, where the NMPC is triggered to run only when the actual states deviate from prediction beyond certain threshold. In other words, the event-triggered NMPC will formulate and solve a constrained optimal control problem only if it is enabled by a trigger event. When NMPC is not triggered, the optimal control sequence computed from last NMPC instance is shifted to determine the control action.

The existing indoor test method for tire and vehicle braking performance in the Automated Indoor Braking Analyzer (AIBA) see Ref. 3, is operating fully automatic with standard vehicle braking systems. The tire’s braking performance is evaluated by the braking distance from defined initial speed (e. g. 80 km/h) to standstill of the vehicle, on specified and exchangeable surfaces (e.g. asphalt) under wet or dry road conditions. Vehicle dynamics and control algorithms are intrinsically part of the overall test system. Another known and accredited test procedure for label and type approval is the traction trailer test which currently is used on outdoor proving grounds. With this method the tire will be tested under constant speed while braking until maximum braking force which is the indicator for the tire performance (μ-peak). We introduce in our presentation a new Analytic Test Vehicle which combines advantages of vehicle- and trailer-based test methods.

The articulated steering system is widely used in engineering vehicles due to its high mobility and low steering radius. The design parameters have a vital impact on the selection of the steering system assemblies, such as the operation stroke, pressure, and force of the hydraulic cylinders during the steering process, which will affect the system weight. The system energy consumption is also relevant to the geometry parameters. According to the kinetic analysis of the steering system and dynamic analysis of the steering process, the kinetic model of an engineering vehicle steering system is built, and the length and pressure variation of the cylinder is calculated and validated by the field test. The influence of the factors is analyzed based on the established model. To lower the system weight, needed pressure, and force, the multi-objective particle swarm optimization method is initiated to optimize the geometry parameter of the articulated steering system.

Current numerical simulation practice does not capture the seat mounted Side Airbag (SAB) breaking out through the seat tear seam and its correct early deployment characteristics. A late SAB breakout negatively impacts full SAB deployment and occupant coverage. An early breakout enhances timely SAB positioning and coverage, providing early cushioning to the occupant from the intruding barrier. This paper presents a numerical modeling process capable of predicting and enhancing seat tear seam breakout time and early SAB deployment kinematics. The critical phases used in the development of SAB breakout modeling process are as follows: Phase 1: Physical Tear Seam and Seat Trim coupon tests to characterize physical material properties for the numerical material model development; Phase 2: Numerical Modeling of the Tear Seam and Seat Trim breakout and, Phase 3: Numerical prediction of SAB breakout through a candidate seat tear seam.

Safety, fuel economy and uptime are key requirements for the operation of heavy-duty line-haul trucks within a fleet. With the penetration of connectivity and automation technologies, energy optimal and safe operation of the trucks are further improved through Advanced Driver Assistance System (ADAS) features and automated technologies as in truck platooning. Understanding the braking capability of the vehicle is very important for optimal ADAS and platooning control system design and integration. In this paper, the importance of tire connectivity and tire conditions on truck stopping distance are demonstrated through testing. The test data is further utilized to develop tire models for integration in an optimal vehicle automation for platooning. New ways to produce and use the tire related information in real-time optimal control of platooning trucks are proposed and the contribution of tire information in fuel economy is quantified through simulations.

An automated driving system (ADS) shall provide safer conditions for highly automated vehicle (HAV) users compared to standard vehicles since human error is excluded. In the following decades, however, one can expect a mixed fleet of both standard and automated vehicles on roads. Therefore, collisions between manually driven cars and HAVs are to be expected. On the other hand, HAVs’ occupants access more room in the vehicle which allows them to rotate their seats to have a comfortable position. This work aims to address the issue of HAV’s occupant safety using tools of numerical simulations. We consider an FE model of a seat with the standard three-point belt at two initial orientations 45° and 90°. The occupant (50th percentile male) is represented with the Virthuman model. We test the idea of employing the active seat rotation system. By detecting a crash well in time an initially rotated seat is reoriented into a standard seating orientation in a rear-end crash.

This study presents a design methodology to predict the crash behavior of mid-size sedan with a simplified crash model. Without detailed conventional finite element, the simplified crash model can be adopted in the early stage of the vehicle design. Designing vehicle structure to satisfy crash performance target is highly complex problem in the early design stage, because of the nonlinear mechanical behavior, high number of degrees-of-freedom, lack of information and boundary conditions changing over the following development process. In this study, the front structure of the vehicle is divided into load-carrying members and the rigid element through the analysis of load-carrying mechanism, and its physical property (force-displacement relation) is parameterized as the property of the non-linear discrete beam element of the LS-DYNA. The effectiveness of the proposed research is shown by the example of the mid-size sedan.

This paper summarizes a series of matched-pair frontal sled tests using the Test device for Human Occupant Restraint 50th Percentile Male (THOR-50M) anthropomorphic test device (ATD). Testing was conducted to compare the response of an ATD equipped with an on-board data acquisition system (DAS) to that of one equipped with an off-board system. Sled testing was performed using a modified version of NHTSA’s Gold-Standard test method consisting of a generic buck with a ridged seat and a 3-point seatbelt system. Eight tests were conducted, all using a common generic 30 km/h crash pulse with a peak deceleration of 9 G’s, and a 2.5 kN load limiting 3-point seatbelt retractors without pretentioners. Four tests were conducted with each ATD, two tests with a left shoulder belt routing and two with a right shoulder belt routing to allow for evaluation of the ATD repeatability under each belt routing.

Recently, keen interest has been focused on the reduction of fuel consumption through the development of eco-friendly and weight-effective vehicles. This is due in part to the strengthening of regulatory standards for fuel efficiency in each country. This study will focus on the optimization of the IP (Instrument Panel) module, in particular, the cowl crossbar, which in some vehicles, can account for more than 33% of the IP module weight. The design objectives of the cowl crossbar were to use continuous fiber thermoplastic composite materials to achieve high stiffness, while optimizing the strength to weight performance as evaluated through vehicle sled and crash testing. This research will introduce the development and optimization methodology for an alternative material, which achieved about a 30% weight reduction as compared to steel.

Assessment of the boundaries for knock in spark ignition engines (related with self-ignition of unburned charge) is required for development of the engine control and charge composition when designing the gas engines with variable fuel compositions. In this work the extension of the single-zone model of the SI engine cycle is proposed. It includes simulation of the fresh charge temperature and pre-flame reactions based on detailed chemical kinetic mechanism of self-ignition. The heat release is modelled based on Wiebe function; the heat transfer is modelled by the Woschni correlation. To extend the capabilities of the single-zone models the closure problem of the heat-transfer surface of unburned charge to combustion chamber walls based on mass fraction burned is addressed in frame of energy balance equation for unburned charge.

To efficiently reduce the required experimental data and improve the prediction accuracy, a virtual engine model has been built by integrating an artificial neural network (ANN) system consisting of multiple subnets with the genetic algorithm (GA). The GA algorithm could reduce the risk of local minima and lead to a more efficient training process. The engine model has been adopted to predict the combustion phases (including CA10, CA50 and CA90), exhaust gas temperature, brake specific fuel consumption rate (be) and engine emissions which are un-burnt hydrocarbon (UBHC), NOx and CO. The results are then compared with the experimental data from around 5000 operating points of a boosted DISI engine running at universal performance map and conditions with various valve timing configurations. The mean absolute errors of combustion phases are all below 1.0 crank angle degree. The averaged errors of the exhaust gas temperature and be are 10.1 K and 1.1%, respectively.

The paper illustrates and validates a novel predictive combustion model for the estimation of performances and pollutant production in CI engines. The numerical methodology was developed by the authors for near real-time applications, while aiming at an accurate description of the air mixing process by means of a multi-zone approach of the air-fuel mass. Charge stratification is estimated via a 2D representation of the fuel spray distribution that is numerically derived by an axial one-dimensional control-volume description of the direct injection. The radial coordinate of each control volume is reconstructed a posteriori by means of a local distribution function. Fuel mass clustered in each zone is further split in ‘liquid’, ‘unburnt’ and ‘burnt’ sub-zones, given the local properties of the fuel spray control volumes with respect to space-time location of modelled ignition delay, liquid length, and flame lift-off.

To speed up the development of the next-generation combustion engines with renewable fuels, the importance of reliable and robust simulations cannot be overemphasized. Compared to gasoline, methanol is a promising fuel for spark-ignited engines due to its higher research octane number to resist auto-ignition, higher flame speed for faster combustion and higher heat of vaporization for intake charge cooling. These advantageous properties all contribute to higher thermal efficiency and lower knock tendency, and they need to be well-captured in the simulation environment in order to generate accurate predictions. In this paper, the sub-models which estimate the burning velocities and ignition delay of methanol are revisited. These building blocks are implemented and integrated in a quasi-dimensional simulation environment to predict the combustion behavior, which are subsequently validated against test data measured on both light-duty and heavy-duty engines.

In the recent years, the interest in heavy-duty engines fueled with Compressed Natural Gas (CNG) is increasing due to the necessity to comply with the stringent CO2 limitation imposed by national and international regulations. Indeed, the reduced number of carbon atoms of the NG molecule allows to reduce the CO2 emissions compared to a conventional fuel. The possibility to produce synthetic methane from renewable energy sources, or bio-methane from agricultural biomass and/or animal waste, contributes to support the switch from conventional liquid fuels to CNG. To drive the engine development and reduce the time-to-market, the employment of numerical analysis is mandatory. This requires a continuous improvement of the simulation models toward real predictive analyses able to reduce the experimental R&D efforts. In this framework, 1D numerical codes are fundamental tools for system design, energy management optimization, and so on.

Aiming at meeting the stringent regulations imposed by the EU and other legislators in the transport sector, various advanced combustion modes for Internal Combustion Engines (ICEs) are currently under investigation. Among those, Homogeneous Charge Compression Ignition (HCCI) appears a promising solution, simultaneously reducing pollutant emission and enhancing thermal efficiency. Hence, to simulate HCCI combustion mode, a general multi-zone model has been developed and implemented through user coding into a commercial software (GT-Power™). This model is based on a control mass Lagrangian multi-zone approach, and it incorporates a procedure based on an off-line tabulation of chemical kinetics (Tabulated Kinetic of Ignition - TKI). It performs an accurate and fast prediction of the air/fuel mixture auto-ignition, combining the accuracy of detailed chemistry with a lighter computational effort.

Model based calibration is extensively used by the automotive OEMs (Original Equipment manufacturers) because of its correlation accuracy with test data and freezing the operating parameters such as injection timings, EGR rates, fuel quantity etc. The prediction of Brake specific Fuel consumption (BSFC), Exhaust and intake temperatures are very close to test data. The prediction of Brake specific NOx is directionally reliable with acceptable tolerance.

Pre-chamber ignition has demonstrated capability to increase internal combustion engine in-cylinder burn rates and enable the use of low engine-out pollutant emission combustion strategies. In the present study, newly designed passive pre-chambers with different nozzle-hole patterns - that featured combinations of radial and axial nozzles - were experimentally investigated in an optically accessible, single-cylinder research engine. The pre-chambers analyzed had a narrow throat geometry to increase the velocity of the ejected jets. In addition to a conventional inductive spark igniter, a nanosecond spark ignition system that promotes faster early burn rates was also investigated. Time-resolved visualization of ignition and combustion processes was accomplished through high-speed hydroxyl radical (OH*) chemiluminescence imaging. Pressure was measured during the engine cycle in both the main chamber and pre-chamber to monitor respective combustion progress.

Increasingly strict emission regulations and unfavorable economic climate bring severe challenges to the energy conservation of marine low-speed engine. Besides traditional methods, the energy and exergy analysis could acknowledge the losses of fuel from a global perspective to further improve the engine efficiency. Therefore, the energy and exergy analysis is conducted for a marine low-speed engine based on the experimental data. Energy analysis shows the exhaust gas occupies the largest proportion of all fuel energy waste, and it rises with the increment of engine load. The heat transfer consumes the second largest proportion, while it is negatively correlated to engine load. The energy analysis indicates that the most effective way to improve the engine efficiency is to reduce the energy wasted by exhaust gas and heat transfer. However, the latter exergy analysis demonstrates that there are other effective approaches to improve the engine efficiency.

Dimethyl ether (DME) represents a promising fuel for heavy-duty engines thanks to its high cetane number, volatility, absence of aromatics, reduced tank-to-wheel CO2 emissions compared to Diesel fuel and the possibility to be produced from renewable energy sources. However, optimization of compression-ignition engines fueled with DME requires suitable computational tools to design dedicated injection and combustion systems: reduced injection pressures and increased nozzle diameters are expected compared to conventional Diesel engines, which influences both the air-fuel mixing and the combustion process. This work intends to evaluate the validity of two different combustion models for the prediction of performance and pollutant emissions in compression-ignition engines operating with DME. The first one is the Representative Interactive Flamelet while the second is the Approximated Diffusive Flamelet.