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This paper presents the “Virtual Failure Mode and Effects Analysis (vFMEA)” system, which is a high-fidelity electrical-failure-simulation platform, and applies it to the software verification of an electric power steering (EPS) system. The vFMEA system enables engineers to dynamically inject a drift fault into a circuit model of the electronic control unit (ECU) of an EPS system, to analyze system-level failure effects, and to verify software-implemented safety mechanisms, which consequently reduces both cost and time of development. The vFMEA system can verify test cases that cannot be verified using an actual ECU and can improve test coverage as well. It consists of a cycle-accurate microcontroller model with mass-production software implemented in binary format, analog and digital circuit models, mechanical models, and a state-triggered fault-injection mechanism.

“Virtual Failure Mode and Effects Analysis” (vFMEA), a novel safety-verification method of control software for automotive electronic systems, was proposed to save prototyping cost at verification stage. The proposed vFMEA is system-level FMEA method, which uses virtualized electronic control units (ECUs) consisting of microcontroller models on a microcontroller simulator and a transistor-level circuit models on a circuit simulator. By using the structure, the control software in binary code formats can be verified when a circuit-level fault occurs in the ECU hardware. As an illustrative example, vFMEA was applied to an engine ECU. As a result of short-circuit fault into a driver IC, engine revolution and engine speed decreased. However, the engine continued to operate normally when an open-circuit fault occurred in a capacitor connected in parallel. Effects of the hardware faults in ECU on a vehicle are demonstrated; thereby software verification can be performed using vFMEA system.

In recent truck applications, single-piece large-diameter propshafts, in lieu of two-piece propshafts, have become more prevalent to reduce cost and mass. These large-diameter props, however, amplify driveline radiated noise. The challenge presented is to optimize prop shaft modal tuning to achieve acceptable radiated noise levels. Historically, CAE methods and capabilities have not been able to accurately predict propshaft airborne noise making it impossible to cascade subsystem noise requirements needed to achieve desired vehicle level performance. As a result, late and costly changes can be needed to make a given vehicle commercially acceptable for N&V performance prior to launch. This paper will cover the development of a two-step CAE method to predict modal characteristics and airborne noise sensitivities of large-diameter single piece aluminum propshafts fitted with different liner treatments.

This paper presents an experimental comparative study between the OCTOGONAL-Gate Silicon-on-Insulator (SOI) nMOSFET (OSM) and the conventional SOI nMOSFET (CSM) considering the same bias conditions and the same gate area (AG), in order to verify the influence of this new MOSFET layout style to handle high current for automotive modules. Analog integrated circuits (ICs) design tends to be considered an art due to a large number of variables and objectives to achieve the product specifications. The designer has to find the right tradeoffs to achieve the desired automotive specification such as low power, low voltage, high speed and high current driver. SOI MOSFET's technology is required to provide the growth of embedded electronics. This growth is driving demand for power-handling devices that are smaller yet still provide high current driver capabilities.

Over the last two decades, engine research has been mainly focused on reducing fuel consumption in view of compliance with stringent homologation targets and customer expectations. As it is well known, the objective of overall engine efficiency optimization can be achieved only through the improvement of each element of the efficiency chain, of which mechanical constitutes one of the two key pillars (together with thermodynamics). In this framework, the friction reduction for each mechanical subsystems has been one of the most important topics of modern Diesel engine development. In particular, the present paper analyzes the lubrication circuit potential as contributor to the mechanical efficiency improvement, by investigating the synergistic impact of oil circuit design, oil viscosity characteristics (including new ultra-low formulations) and thermal management. For this purpose, a combination of theoretical and experimental tools were used.

The main objective of this paper is to simulate the springback using combined kinematic/isotropic hardening model. Material parameters in the hardening model are identified by an inverse method. Three-point bending test is conducted on 6022-T4 aluminum sheet. Punch stroke, punch load, bending strain and bending angle are measured directly during the tests. Bending moments are then computed from these measured data. Bending moments are also calculated based on a constitutive model. Material parameters are identified by minimizing the normalized error between two bending moments. Micro genetic algorithm is used in the optimization procedure. Stress-strain curves is generated with the material parameters found in this way, which can be used with other plastic models. ABAQUS/Standard 5.8, which has the combined isotropic/kinematic hardening model, is used to simulate draw-bend of 6022-T4 series aluminum sheet. Absolute springback angles are predicted very accurately.

Sintered parts mechanical properties are very sensitive to final density, which inevitable cause an enormous density gradient in the green part coming from the compaction process strategy. The current experimental method to assess green density occurs mainly in set up by cutting the green parts in pieces and measuring its average density in a balance using Archimedes principle. Simulation is the more accurate method to verify gradient density and the main benefit would be the correlation with the critical region in terms of stresses obtained by FEA and try to pursue the optimization process. This paper shows a case study of a part that had your fatigue limit improved 1000% using compaction process simulation for better optimization.

The flight area of drones and other unmanned aerial vehicles (UAVs) had been highly restricted but has been relaxing, including flights beyond the scope of sight. Deregulation without aircraft-reliability improvement increases the risk of accidents. However, demanding high reliability for all aircraft leads to an increase in the price of the aircraft. Therefore, if airspace restrictions are relaxed for more reliable aircraft, the cost of higher reliability and its benefits can be balanced. This will improve efficiency and optimize cost-effectiveness. The purpose of this proposal is to balance the cost of aircraft-reliability improvement (which allows flight to continue in the event of a failure) and its advantages. Specifically, the author proposes rules that apply more relaxed airspace restrictions to UAVs with higher FCLs (Flight Continuity Possibility Levels) and stricter airspace restrictions to those with lower FCLs.

Powertrain mounting systems design and development involves creating and optimizing a solution using specific mount rates and evaluation over multiple operating conditions. These mount rates become the recommended “nominal” rates in the specifications. The powertrain mounts typically contain natural materials. These properties have variation, resulting in a tolerance around the nominal specification and lead to differences in noise and vibration performance. A powertrain mounting system that is robust to this variation is desired. The design and development process requires evaluation of these mounts, within tolerance, to ensure that the noise and vibration performance is consistently met. During the hardware development of the powertrain mounting system, a library of mounts that include the range of production variation is studied. However, this is time consuming.

Simple planetary gears are widely used in automobile industry due to their compact design and high power density. A simple planetary gear set consists of a Sun gear, Ring gear, Planets and Carrier which houses planet gears. Mounting of planet pinions on carrier is through pins which is supported on needle roller bearings. A process called staking is used to assemble the pinion pins on to the carrier. Pinion pins have a staking region which after assembly expands outward into staking groove on the carrier to prevent axial movement of the pins. Design of the groove plays a vital role for the fixation of planet pins and robustness a carrier. Planetary carrier staking grooves are designed to meet pinion pin retention and strength targets.

Planetary gear set is one of the most commonly used gear systems in automotive industry as they cater to high power density requirements. A simple planetary gear set consists of a sun gear, ring gear, planets and carrier which houses planet gears. Efficiency of a transmission is dependent upon performance of gear sets involved in power transfer to a great extent. Structural rigidity of a planetary carrier is critical in a planetary gear set as its deflection may alter the load distribution of gears in mesh causing durability and noise issues. Limited studies exist based on geometrical parameters of a carrier which would help a designer in selecting the dimensions at an early stage. In this study, an end to end automated FEA process based on DOE and optimization in Isight is developed. The method incorporates a workflow allowing for an update of carrier geometry, FE model setup, analysis job submission and post-processing of results.

As conventional vehicle design is adjusted to suit the needs of all-electric, hybrid, and fuel-cell powered vehicles, designers are seeking new methods to improve system-level design and enhance structural efficiency; here, multi-material optimization is suggested as the leading method for developing these novel architectures. Currently, diverse materials such as composites, high strength steels, aluminum and magnesium are all considered candidates for advanced chassis and body structures. By utilizing various combinations and material arrangements, the application of multi-material design has helped designers achieve lightweighting targets while maintaining structural performance requirements. Unlike manual approaches, the multi-material topology optimization (MMTO) methodology and computational tool described in this paper demonstrates a practical approach to obtaining the optimum material selection and distribution of materials within a complex automotive structure.

Structures with multiple materials have now become one of the perceived necessities for automotive industry to address vehicle design requirements such as light-weight, safety, and cost. The objective of this study is to develop a design methodology for multi-material structures accountable for vehicle crash durability. The heuristic topology synthesis approach of Hybrid Cellular Automaton (HCA) framework is implemented to generate multi-material structures with the constraint on the volume fraction of the final design. The HCA framework is integrated with ordered-SIMP (solid isotropic material with penalization) interpolation, artificial material library, as well as statistical analysis of material distribution data to ensure a smooth transition between multiple practical materials during the topology synthesis.

As automakers continue to develop new lightweight vehicles, the application of multi-material parts, assemblies and systems is needed to enhance overall performance and safety of new and emerging architectures. To achieve these goals conventional material selection and design strategies may be employed, such as standard material performance indices or full-combinatorial substitution studies. While these detailed processes exist, they often succeed at only suggesting one material per component, and cannot consider a clean-slate design; here, multi-material topology optimization (MMTO) is suggested as an effective computational tool for performing large-scale combined multi-material selection and design. Unlike previous manual methods, MMTO provides an efficient method for simultaneously determining material existence and distribution within a predefined design domain from a library of material options.

In order to increase the efficiency of automotive turbochargers at low speed without compromising the performance at maximum boost conditions, variable geometry compressor (VGC) systems, based on either variable inlet guide vanes or variable geometry diffusers, have been recently considered as a future design option for automotive turbochargers. This work presents a modeling, analysis and optimization study for a Diesel engine equipped with a variable geometry compressor that help understand the potentials of such technology and develop control algorithms for the VGC systems,. A cycle-averaged engine system model, validated on experimental data, is used to predict the most important variables characterizing the intake and exhaust systems (i.e., mass flow rates, pressures, temperatures) and engine performance (i.e., torque, BMEP, volumetric efficiency), in steady-state and transient conditions.

We have developed a model-based control for the air intake system in a variable valve engine, employing total engine simulation, the response surface method and multi-objective optimization scheme. In our technique, we performed the simulation model tuning and validation, followed by the creation of a dataset for the polynomial regression analysis of the charging efficiency. A D-optimal design, robust least squares method, and likelihood-ratio test were demonstrated to yield a robust and accurate control model. Coupling the total engine simulator with a genetic algorithm, model based calibration for optimal valve timing stored in lookup table was carried out under multiple objectives and restrictions. The reliability of the implementation control model, which considers the effect of gas dynamics in the intake system, was confirmed using a model-in-the-loop simulation.

The purpose of this study is to develop model-based methodologies which employ thermo-fluid dynamic engine simulation and multiple-objective optimization schemes for engine control and calibration, and to validate the reliability of the method using a dynamometer test. In our technique, creating a total engine system model begins by first entirely capturing the characteristics of the components affecting the engine system's behavior, then using experimental data to strictly adjust the tuning parameters in physical models. Engine outputs over the full range of engine operation conditions as determined by design of experiment (DOE) are simulated, followed by fitting the provided dataset using a nonlinear response surface model (RSM) to express the causal relationship among engine operational parameters, environmental factors and engine output. The RSM is applied to an L-jetronic® air-intake system control logic for a turbocharged engine.

The increasing number of controllable parameters in modern engine systems leads to complicated and enlarged engine control software. This in turn has led to dramatic increases in software development time and costs in recent years. Model-based control design seems to be an effective way to reduce development time and costs. In the present study, we have developed model-based methodologies for the engine calibration process using an engine cycle simulation technique combined with a regression analysis of engine responses. From the results it was clear that the engine cycle simulation technique was useful in the engine calibration process, if the empirical parameters included in physical models were adjusted at typical sampling-points in several engine speeds and loads. The cycle simulation produced a multi-dimensional MBT map, and a response surface method was employed in the modeling of the engine map dataset using a polynomial equation.

To cope with the increasing number of advanced features (e.g., smart-phone integration and side-blind zone alert.) being deployed in vehicles, automotive manufacturers are designing flexible hardware architectures which can accommodate increasing feature content with as fewer as possible hardware changes so as to keep future costs down. In this paper, we propose a formal and quantitative definition of flexibility, a related methodology and a tool flow aimed at maximizing the flexibility of an automotive hardware architecture with respect to the features that are of greater importance to the designer. We define flexibility as the ability of an architecture to accommodate future changes in features with no changes in hardware (no addition/replacement of processors, buses, or memories). We utilize an optimization framework based on mixed integer linear programming (MILP) which computes the flexibility of the architecture while guaranteeing performance and safety requirements.

In recent decades, significant technological advances have made cruise control systems safer, more automated, and available in more driving scenarios. However, comparatively little progress has been made in optimizing vehicle efficiency while in cruise control. In this paper, two distinct strategies are proposed to deliver efficiency benefits in cruise control by leveraging flexibility around the driver’s requested set speed, and road information that is available on-board in many new vehicles. In today’s cruise control systems, substantial energy is wasted by rigidly controlling to a single set speed regardless of the terrain or road conditions. Introducing even a small allowable “error band” around the set speed can allow the propulsion system to operate in a pseudo-steady state manner across most terrain. As long as the vehicle can remain in the allowed speed window, it can maintain a roughly constant load, traveling slower up hills and faster down hills.