Analysis of Sensitivity and Optimization for Chassis Design Parameters on the X-Wind Stability

<div class="htmlview paragraph">In order to improve the emission and performance capabilities of modern engines several devices are introduced in the system. One of such devices is the Continuously Variable Cam Phaser (CVCP), which, by shifting the relative angle between the crank and cam shafts, allows to modify the opening and closing times of the inlet and outlet valves with respect to the base engine configuration, thus giving more design freedom. The control of the CVCP is performed by the Engine Control Unit, which both sets the desired values for the CVCP shift angle and commands the CVCP actuator to control it at the correct position.</div> <div class="htmlview paragraph">The new FIRE engine 1.4l 16v also includes a CVCP. The aim of the activity described in the paper was to perform a functional validation of the CVCP position control algorithms, through a sensitivity analysis of the CVCP control performance to a series of environmental and production variables.</div> <div class="htmlview paragraph">In order to reduce at a minimum the costs of this analysis the choice to use virtual testing as an alternative to experimental testing on the engine test bench, was taken. By this choice it was possible to analyze in simulation many more system configurations, than those available for a real experimental set-up. The building bricks for the analysis were: the definition of the test cases, operating conditions, and performance indicators for the analysis; functional simulation models of the CVCP, its actuators and sensors, developed with the device supplier, INA, of the ECU software for the control of the CVCP, and of the main environmental parameters affecting the CVCP control performance; a toolbox for the Design of Experiments, by which, once selected the design parameters subject to production, mounting or operating variability, defining the set of virtual tests to perform; some tools for the visualization and analysis of the results of the DOE.</div> <div class="htmlview paragraph">The sensitivity analysis results showed that the CVCP control system was robust to parameters variability within the tolerance ranges, being able to satisfy the prescribed performance targets.</div>

<div class="section abstract"><div class="htmlview paragraph">In the present scenario, automobile manufacturers are forced to reduce the weight of each components through design optimization. In a bid to enhance the fuel efficiency and load carrying capacity of the vehicle; however this approach may not be practical for all the parts in real life, and the engineer will end up adding further mass to the component. This is carried out to enhance the strength of the component, since considerable over load application in real world usage condition which can damage the component drastically.</div><div class="htmlview paragraph">In this paper, steering tie rod arm of a heavy commercial vehicle was taken as a case study. The Steering tie rod arm is a part which connects the wheel spindle with steering system linkage i.e. Track rod. Track rod transfers the steered force from one wheel to another wheel and steering tie rod arm transfers the force from track rod to wheel spindle to steer both the wheels in same direction.</div><div class="htmlview paragraph">During vehicle operating conditions, this steering tie rod arm experiences very high tensile and compressive loads and consecutively this part undergoes fatigue. Authors discussed on initial design proposal of steering tie rod arm, CAE (Computer Aided Engineering) Analysis, Instrumentation and Vehicle data acquisition on different operating conditions, block programming of test data, life predictions using strain life approach and physical testing. The predicted life was compared with CAE life and actual component test life to establish correlation. Optimization of design was carried out virtually using this established correlation and further substantiated by rig and vehicle level testing</div></div>

<div class="section abstract"><div class="htmlview paragraph">The job of a suspension system is to maximize the friction between the tires and the road surface, to provide steering stability with good handling and to act as a cushioning device to ensure the comfort of the driver and passengers. The suspension system also protects the vehicle and any cargo or luggage from damage and wear.</div><div class="htmlview paragraph">Commonly the strength of these suspension systems is evaluated by endurance trials on field or Rig testing which are time consuming and costly. On the other hand, virtual testing methods for strength and stiffness evaluation provide useful information early in the design cycle and save significant time and cost. However, the virtual method also needs validation, which can be achieved by physical co-relations (via rig tests).</div><div class="htmlview paragraph">A study has been done to predict the behavior of Leaf Spring Suspensions entirely through the FEA (Finite Element Analysis) route and correlating those results with physical test. Initially the acceleration data is abstracted via RLDA (Road Load Data Acquisition) pasting the accelerometers at axle points. Strain Gauges are used to acquire strain values with respect to accelerations. This acceleration data is then used as input in rig setup at axle points and relatively strain is measured at same strain gauge locations as done while RLDA. This is done primarily to validate the test rig.</div><div class="htmlview paragraph">After Rig validation, a virtual validation is required. Leaf Spring assemblies modeled in FEA are similar to rig test bed setup. Tests are performed on the rig and gauges are used to extract the data for virtual co-relation. At the time of simulation, various parameters have been modified to achieve realistic behavior. Correlations between Stiffness and Stress have been achieved at these strain gauge locations between the Rig test and CAE (Computer Aided Engineering) results.</div><div class="htmlview paragraph">Correlation (around 90%) has been achieved between Rig test data and FEA results at measured locations. Correlation has helped in reducing product design time and cost of running the rig until crack. This process has also reduced the cost by using soft validation for multiple Leaf Spring Suspensions like Semi-elliptical, Parabolic, Weveller, Bogie and Bell Crank. Hence, this FEA based methodology has facilitated our organization in designing an excellent suspension system which will prove beneficial to our customers.</div></div>

<div class="section abstract"><div class="htmlview paragraph">An Air intake system (AIS) is a duct system which leads the airflow going into the internal combustion engine. Combustion requires oxygen, and the more oxygen is provided into the combustion process the more power it will produce. The lower the air temperature, the higher its density, and hence there is more oxygen in a unit volume. The quality of air entering engine can be measured with the air temperature.</div><div class="htmlview paragraph">AIS design and routing influence the air charge temperature (ACT) at intake manifold runners and ACT is normally measured at AIS throttle body in reality. Higher ACT lead to inefficient combustion and can lead to spark retard. Optimization of AIS designs and reduction of ACT can improve engine performance and vehicle fuel economy.</div><div class="htmlview paragraph">High ACT can be a result of two different phenomena: <ul class="list disc"><li class="list-item"><div class="htmlview paragraph">Recirculation - Hot air from the underhood environment ingested into the dirty side of the air intake system. This is the result of the AIS snorkel not being isolated or sealed from the engine compartment hot air.</div></li><li class="list-item"><div class="htmlview paragraph">Underhood temperature rise - Air inside AIS is heated by the ducts walls because it is routed through a hot underhood environment. The longer the length and larger the diameter of the air induction system, and the higher duct skin temperatures, the worse the temperature rise.</div></li></ul></div><div class="htmlview paragraph">In this paper, it is planned to simulate and study the effects of following factors on ACT with CFD using a FCA production vehicle: <ul class="list disc"><li class="list-item"><div class="htmlview paragraph">Snorkel location: snorkel sucking fresh air at side air guide or snorkel sucking underhood hot recirculation air.</div></li><li class="list-item"><div class="htmlview paragraph">Exhaust hot end at front of an east-west engine or at the rear of the engine; these two arrangements will result in different underhood air temperatures and radiation to AIS surfaces.</div></li><li class="list-item"><div class="htmlview paragraph">Heat shield effects on ACT: heat shield blocks radiation from exhaust system to AIS surfaces, and hence reduces charge air heat pick from AIS duct walls.</div></li><li class="list-item"><div class="htmlview paragraph">The effects of other measures such as cutting holes on hood or fenders to lower engine compartment air temperatures.</div></li></ul></div><div class="htmlview paragraph">Although the airflow in vehicle AIS duct is transient in nature, steady CFD simulations will be performed to study the above cases for simplification, and CFD approach will be discussed in details. Vehicle test data will be used to validate the CFD models.</div><div class="htmlview paragraph">Finally, general practices of AIS development will be discussed, and future work on this topic will be outlined.</div></div>

<div class="section abstract"><div class="htmlview paragraph">The Automotive industry’s use of digital technology such as Computer Aided Engineering (CAE) to perform virtual validation has progressed to effectively replace a large percentage of physical validation. This is primarily due to the increased accuracy and cost/time efficiencies that virtual validation offers compared to conventional physical prototyping and testing. With product development (PD) cycles becoming more compressed, CAE has assumed a more significant role in early, advanced design and structural evaluation. One of the areas where CAE is widely employed is in development of the Instrument Panel (IP) commonly referred to as the dashboard. For the purposes of this study, the term IP represents the plastic/polymer structure only, and not the full IP sub-system. The IP sub-system includes the structural member, the Cross Car Beam (CCB) assembly and all the IP mounted modules.</div><div class="htmlview paragraph">The primary objective of this exercise is to guide upfront IP design using a simplified representation of the IP sub-system. The CCB assembly is represented as a parametric, simplified and scalable beam model. This simplified CCB model can then be used to simulate the IP sub-system as soon as the studio “class A” surface data is available in conjunction with assumptions for the masses of key IP mounted modules. The exercise is expected to yield a reliable process to guide the IP design, for structural stiffness objectives, at early stages of the PD cycle. To prove the effectiveness of this process, it is implemented on several IPs from different vehicle classes, and the global frequencies of the resulting simplified models are compared to the fully contented, traditionally built models.</div></div>

<div class="section abstract"><div class="htmlview paragraph">In an automotive suspension, the shock absorber plays a significant role to enable the vehicle performances, especially in ride, handling and Noise-Vibration-Harshness (NVH). Understanding its physical characteristics is of great importance, as it has a main influence on the overall vehicle performance.</div><div class="htmlview paragraph">Within this research project simulation models for different passive monotube shock absorber systems have been created in a 1-D system simulation software. The simulation models are designed and parameterized physically.</div><div class="htmlview paragraph">To validate the simulation models measurements on different hydropulse-shaker with specially designed control signals to investigate the response during high frequency excitation, have been done. A detailed discussion of the several models and results of a simulation to measurement comparison is given. After detailed investigation the shock absorber simulation models are now adaptable to the multi body simulation.</div><div class="htmlview paragraph">As a result nearly equal experimental and simulated response of the different shocks was found. Some deviations are remaining during high frequency (>30Hz) operation of the damper. Dominant parameters to influence the damper response have been found. A sensitivity analysis shows the influences of these parameters. An analytical model to approach the shim stack stiffness was designed. For a validation detailed Finite-Element-Method (FEM) models of the shim stack have been developed and compared with load cases up to 100 bar hydraulic pressure. Additionally an FEM-model of the shock absorber and detailed modal analysis have been made to calculate and validate the natural frequencies of the shock. Limitations of this current study are the investigated monotube shock absorber systems, not including and including stroke-dependent-damping.</div><div class="htmlview paragraph">The presented novelty is the method of the configuration of the shock absorber simulation models only with geometric data. The shim stack models to calculate its stiffness instead of fatigue calculation are new as well. The new configuration approach increases the possibility to design automotive shock absorbers in advance of having a prototype. With the multi-body simulations of the chassis forecasts of the cars behaviour are possible at earlier stages during the development cycle. As OEM it is possible to simulate the behavior of the shock absorber in detailed car models.</div></div>

<div class="htmlview paragraph">A free piston internal combustion engine coupled with a linear generator is proposed for hybrid vehicle application. The engine works on CI two-stroke cycle with direct fuel injection. Uniflow was chosen for an efficient scavenge process. The exhaust valve timing and lift are to be dynamically controlled by electromechanical driven poppet valves, developed by FEV.</div> <div class="htmlview paragraph">A numerical simulation model of the proposed engine has been generated in this paper. The piston dynamics, cylinder scavenge process, combustion process, and friction characteristics are coupled together for systematic analysis with the code. It is meant to be a tool for prediction and optimization of the engine design and control parameters, such as fuel injection timing, valve/port timing, and electric power output. The analysis results are discussed in this paper.</div>

<div class="htmlview paragraph">Controlled Auto-Ignition (CAI) combustion, also known as HCCI or PCCI, has recently emerged as a viable alternative combustion process to the conventional spark ignition (SI) or compression ignition (CI) process for internal combustion (IC) engines, owing to its potential for high efficiency and extremely low emissions. One of the most effective and practical means of achieving CAI combustion in an engine is to retain or recycle the burnt gases. In order to understand better the effects of recycled burnt gases on CAI combustion, detailed analytical and experimental studies have been carried out. The analytical studies were performed using an engine simulation model with detailed chemical kinetics.</div> <div class="htmlview paragraph">The five effects of the recycled burned gases studied include:</div> <div class="htmlview paragraph"> <ol class="list nostyle"> <li class="list-item"><span class="li-label">(1.)</span><div class="htmlview paragraph">Charge heating effect: higher intake charge temperature due to hot burned gases;</div></li> <li class="list-item"><span class="li-label">(2.)</span><div class="htmlview paragraph">Dilution effect: the reduction of oxygen due to the presence of the burned gases;</div></li> <li class="list-item"><span class="li-label">(3.)</span><div class="htmlview paragraph">Heat capacity effect: due to higher specific heat capacity of burned gases;</div></li> <li class="list-item"><span class="li-label">(4.)</span><div class="htmlview paragraph">Chemical effect: chemical reactions involving CO<sub>2</sub> and H<sub>2</sub>O in the burned gases</div></li> <li class="list-item"><span class="li-label">(5.)</span><div class="htmlview paragraph">Stratification effect: recycled burned gases are stratified from the fuel/air mixture.</div></li> </ol> </div> <div class="htmlview paragraph">And the main conclusions are:</div> <div class="htmlview paragraph"> <ol class="list nostyle"> <li class="list-item"><span class="li-label">(1.)</span><div class="htmlview paragraph">The charge heating effect is mainly responsible for the advanced AI timing due to hot burned gases. It increases the heat release rate and shortens the combustion duration.</div></li> <li class="list-item"><span class="li-label">(2.)</span><div class="htmlview paragraph">The dilution effect does not affect AI timing, but it extends combustion duration. Its slows down the heat release rate only when large amount of burned gases is present.</div></li> <li class="list-item"><span class="li-label">(3.)</span><div class="htmlview paragraph">The heat capacity effect is mainly responsible for the reduction in the heat release rate, and it has a similar effect to extend the combustion duration as the dilution effect.</div></li> <li class="list-item"><span class="li-label">(4.)</span><div class="htmlview paragraph">The chemical effect does not affect AI timing and heat release rate. It reduces the combustion duration slightly at high concentrations of burned gases.</div></li> <li class="list-item"><span class="li-label">(5.)</span><div class="htmlview paragraph">The stratified burned gases facilitate the CAI combustion due to the presence of higher temperature region at the boundary between of the hot burned gases and combustible charge.</div></li> </ol> </div>

<div class="section abstract"><div class="htmlview paragraph">Battery temperature is known to have a critical influence on overall battery pack performance, from electrochemical behavior, charge acceptance, power availability, trip efficiency, safety, reliability and life-cycle costs. Temperature monitoring is critical to ensure safe and reliable battery pack operation.</div><div class="htmlview paragraph">Monitoring of cell temperatures in battery packs allows for control and estimation algorithms that can ensure homogenous pack temperature distribution, prevent excessive pack temperature rise and even infer cell core temperature, potentially allowing to both predict and mitigate onset of thermal runaway.</div><div class="htmlview paragraph">The increasing need for improved accuracy requires inclusion of more detail in the modelling stage, leading inevitably to ever larger-scale, ever more complex dynamical systems. Simulations in such large-scale settings lead in turn to unmanageably large demands on computational resources, which is the main motivation for Model Order Reduction.</div><div class="htmlview paragraph">Model Order Reduction is focused on reducing the complexity of large-scale dynamical systems, while preserving their input-output behavior. Reduced models mimic the complex behavior of large-scale dynamical systems, and can be efficiently used for design, optimization and sensitivity analysis. The resulting reduced order model can be used to replace the original system as a component in a larger simulation or it might be used to develop a simpler and faster controller suitable for real time applications.</div><div class="htmlview paragraph">Three model order reduction techniques are compared. The first method, Balanced Truncation, assumes access to the high-fidelity model structure is available whilst the other two, Nyquist and neural network approximation, assume only input/output behavioral knowledge is available. The reduced order models are compared, in simulation, to a high-fidelity model of a battery pack in terms of simulation speed-up, model accuracy and property preservation. The applicability of each technique for real-time applications, particularly in the context of xEV (grid connected electric vehicle) thermal management, together with pros and cons of each method is discussed.</div></div>

<div class="htmlview paragraph">Lean burn spark-ignition engines (S.I.E) are currently under scrutiny for their fuel economy and pollution reduction potential while using fuels with ordinary anti-knock quality.</div> <div class="htmlview paragraph">This study was concentrated on turbulence generation in a simulated inlet manifold of S.I.E. via the use of several designs of turbulence generators. A special test set-up was specifically designed and built for this study, and special measuring probes were constructed, developed and calibrated to find out the turbulence level behind each turbulence generator. Four types of swirl and turbulence generators were used and tested to find out the optimum design and operational parameters.</div> <div class="htmlview paragraph">The investigation has been carried out using air as the working medium, while the effect of flow velocity, temperature and turbulence generator design parameters were studied and their effect on the relative turbulence kinetic energy was experimentally found out. Also the decay in turbulence level in the inlet manifold was measured as well as the effect of air to fuel ratio and the existence of bends downstream the generator. Correlations were developed for each type of turbulence generators to predict the level of turbulence as well as the turbulence decay with distance. The optimum type of turbulence generators was put forward and optimum design parameters for the generator were found out.</div> <div class="htmlview paragraph">Based on the results of this study it can be concluded that replacing the conventional throttle valve of the engine by two turbulence generators in series (disc type of delta-wing type) may be the optimum way to achieve a high turbulence level and a high volumetric efficiency.</div>

<div class="section abstract"><div class="htmlview paragraph">High pressure EGR provides NO<sub>x</sub> emission reduction even at low exhaust temperatures. To maintain a safe EGR system operation over a required lifetime, the EGR cooler fouling must not exceed an allowable level, even if the engine is operated under worst-case conditions.</div><div class="htmlview paragraph">A reliable fouling simulation model represents a valuable tool in the engine development process, which validates operating and calibration strategies regarding fouling tendency, helping to avoid fouling issues in a late development phase close to series production.</div><div class="htmlview paragraph">Long-chained hydrocarbons in the exhaust gas essentially impact the fouling layer formation. Therefore, a simulation model requires reliable input data especially regarding mass flow of long-chained hydrocarbons transported into the cooler.</div><div class="htmlview paragraph">There is a huge number of different hydrocarbon species in the exhaust gas, but their individual concentration typically is very low, close to the detection limit of standard in-situ measurement equipment like GC-MS.</div><div class="htmlview paragraph">Therefore, a new measurement and analysis approach has been developed, where the exhaust gas is guided to a metal foam collector, in which HC`s are deposited. The probe is then analyzed in a suited thermogravimetrical system (TGA) in nitrogen atmosphere, temperature range 25°C to 650°C. Analyzing the TGA curve, HC concentration data for 6 different boiling temperature ranges are obtained, provided to an adapted 1-d fouling simulation model.</div><div class="htmlview paragraph">Using these data along with further input parameters like cooler geometry, gas temperature, pressure, flow, particle size distribution and coolant temperature, the simulation model has proven as a suitable tool to predict the fouling and identify engine settings for fouling reduction.</div></div>

<div class="section abstract"><div class="htmlview paragraph">With the fast development of computational analysis tools and capacities during the past ten years, complex and substantial computer-aided engineering (CAE) simulations are now economically possible. While the cost of crash tests has risen steadily, the fidelity and complexity, which numerical simulations could address, has multiplied keeping the cost of computational analysis more stable. The fundamental goal of CAE is to achieve significant reduction in the number of physical tests conducted during the product development process. However, validating the CAE model with physical tests is essential to ensure accuracy and reliability. Simulations performed using a validated CAE model could be used to make decisions like airbag deployment or high voltage shutdown without an actual physical test being conducted. This paper discusses validating an electric commercial vehicle CAE model during a side impact thus emphasizing the safety of a high voltage battery system. The critical parameters considered for fine-tuning the CAE model are discussed. The qualitative comparison looks at global displacement of the vehicle, local deformations and failure of the structural components. The acceleration time histories measured from different locations of the test vehicle are compared with the same obtained from the CAE simulation for quantitative correlation. While most of the quantitative comparison metrics are limited to time domain, this paper discusses a time, frequency and time-frequency domain comparison of the acceleration curves measured from test and CAE. The qualitative and quantitative comparison of the results shows the correlation level of the CAE simulation with the physical test outcome.</div></div>

<div class="section abstract"><div class="htmlview paragraph">Within gear pair development, the simulation of loaded transmission error, line of action and summarized mesh point are crucial information in design optimization as well as reliability, NVH and efficiency prediction. These properties and variables are difficult to evaluate and are usually only assessed through proxy-variables such as unloaded transmission error or contact pattern assessment. Alternatively, large design loops can be generated when prototypes are produced to directly assess the results of reliability, NVH and efficiency and simulation models updated to the results, but not directly calibrated.</div><div class="htmlview paragraph">This work will showcase an advanced test facility with the unique capabilities to evaluate all gear contact types (including hypoid, beveloid, cylindrical and spiral) under loaded conditions while assessing position and force data that can be used to validate simulation models directly and enhance design development.</div><div class="htmlview paragraph">Results will be shown for the assessment of hypoid gear fatigue life while also showing the effect of manufacturing tolerances on performance and the evolution of these critical variables throughout the life as they vary with run-in and gradual flank wear.</div></div>

<div class="section abstract"><div class="htmlview paragraph">Driver model has been developed since 1950s and quite a lot of attention has been attracted on this aspect. Today there is a body of knowledge regarding driver mathematic model. Since driving behavior is highly complex, involving psychology and physiology factors, it is not easy to use a simple driver model to represent all characteristic features comprehensively, according to the utilization of driver model, some assumptions are necessarily proposed in order to tackle the specific problem easily.</div><div class="htmlview paragraph">Optimal Preview Acceleration Driver Model was put forward based on the Preview-Following Theory proposed by Prof. Guo in 1983. This driver model is quite simple and easy to understand, and accurate for great curvature path following. However, recent study has shown that more work is needed to improve the path following ability for sharp corner or urgent corner (higher frequency steering input). This paper will investigate and analyze the Optimal Preview Acceleration Driver Model in details, and propose an improvement based on this classical driver model to make it suitable for more specific conditions, especially for urgent cornering. Finally, the modified driver model will be verified to be more capable of realizing high frequency steering behavior than the previous driver model.</div></div>

<div class="htmlview paragraph">Side impact occupant safety has been evaluated and optimized using a MADYMO vehicle compartment model with prescribed structural motion. A CPU efficient approach is presented where reliability is optimized in three stages: <ul class="list disc"> <li class="list-item"> <div class="htmlview paragraph">Stochastic (random) analysis to calculate the scatter that could be expected for the initial design</div></li> <li class="list-item"> <div class="htmlview paragraph">Optimization taking scatter into account by safety margins derived from the first stage</div></li> <li class="list-item"> <div class="htmlview paragraph">Robustness verification</div></li></ul></div> <div class="htmlview paragraph">To evaluate scatter resulting from dummy hardware variations a stochastic model of the ES-2 dummy was used. Variation of dummy & seat position and variation of airbag and door trim properties were included using the scatter database developed in the EC projects VITES and APROSYS.</div> <div class="htmlview paragraph">Two sets of 150 simulations were used for the scatter analysis (including 23 scatter parameters) and 120 simulations were necessary in the optimization (including 3 design parameters). The CPU per analysis was 2 hours and the total process took 9 days using up to 6 processors. These numbers prove that this method can be used in a vehicle development process. In this project the EuroNCAP side impact sub-score has been evaluated. The initial stochastic analysis showed results ranging from 3-5 stars where in particular the parameters related to dummy and seat position have a major influence. The optimization showed results ranging from 4-5 stars, with an increased probability of obtaining 5 stars.</div>