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Consumers design different PHEVs than expert analysts assume. Experts almost uniformly assume PHEVs that offer true all-electric driving for 10 to 60 miles; consumers are more likely to design PHEVs that do not offer true all-electric driving and have short ranges over which they use grid-electricity. Thus consumers? PHEV designs are less expensive. These consumer PHEV designs do, or don?t, produce lower GHG emissions than experts? PHEVs over the next ten years. The devil is in the details, i.e., which powerplant emissions to assign to new electricity demand: marginal or average. If (based on marginal powerplant emissions) it makes almost no difference whether we sell consumer-designed or expert-assumed PHEVs over the next ten years, yet as the grid continues to de-carbonize all-electric PHEV designs emerge as clearly the better option, there is a trajectory we could be on from blended, ?short range? PHEVs to all-electric ?long range? PHEVs.

In the analysis for durability or R&H performance with the full vehicle multibody models, the need for component flexibility is increasing along with demand for more precise full vehicle system. The component elastic deformations are usually expressed by modal superposition from component normal mode analysis with finite element model for reducing model size and simulation time. Although the simulation results of MBD analysis are more accurate according to increasing the number of flexible body and modes, the increasing of flexible components makes worse simulation time and convergence in MBD analysis. Especially, in the MBD analysis including a flexible upper body, in substitution for large number degree of freedom FE model such as trimmed body, it should take a few times longer than the case of rigid upper body This paper proposes the methods of reducing computational cost with adequate mode selections without the loss of simulation accuracy in the flexible MBD.

In contrast to highway, there are some sections not well maintained in urban roads. In these sections, there may be faint lane marks or static obstacles due to construction or some other reasons. Therefore, an automated vehicle following system such as traffic jam assistant should consider these sections to guarantee the safety of the system. In order to achieve this purpose, a model predictive control (MPC) scheme has been developed. The objectives of MPC are to compute the sequence of optimal steering input for vehicle following with obstacle avoidance. For this, the MPC uses the lead vehicle's state and obstacle's position obtained by lidars. For this purpose, a simplified nonlinear model of the vehicle was used to predict the future evolution of the system. Based on this prediction, performance index is optimized under operating constraints at each time step. A test vehicle equipped with two lidars on left and right corner of the front bumper has been developed.

In this paper, we propose algorithms for cost minimization of physical wires that are used to connect electronic devices in the vehicle. The wiring cost is one of the most important drivers of electrical architecture selection. Our algorithms perform wire routing from a source device to a destination device through harnesses, by selecting the optimized wire size. In addition, we provide optimized splice allocation with limited constraints. Based on the algorithms, we develop a tool which is integrated into an off-the-shelf optimization and workflow system-level design tool. The algorithms and the tool provide an efficient, flexible, scalable, and maintainable approach for cost analysis and architecture selection.

Novel water management and reactant distribution strategies are critical to next generation polymer electrolyte membrane fuel cell systems (PEMFCs). Improving these strategies in PEMFCs leads to higher power density and reduced stack size for vehicle applications, which reduces weight and improves the price competitiveness of these systems. Interdigitated flow fields induce convective transport (cross flow) through the porous GDL between adjacent channels and are superior at water removal beneath land areas, which can lead to higher cell performance. However, the head loss due to flow, among other factors, may cause cross flow maldistribution of reactants down the channel. Such maldistribution may lead to areas of low or areas of excess cross flow. This, in turn, can cause areas of low oxygen concentration and water build up, and therefore higher pressure losses and uneven membrane hydration, all of which reduce overall cell performance.

The assessment of the Transmission Loss (TL) of vehicle components at Low-Mid Frequencies generally raises difficulties associated to the physical mechanisms of the noise transmission through the automotive panel. As far as testing is concerned, it is common in the automotive industry to perform double room TL measurements of component baffled cut-outs, while numerical methods are rather applied when prototype or hardware variants are not available. Indeed, in the context of recent efforts for reduction of vehicle prototypes, the use of simulation is constantly challenged to deliver reliable means of decision during virtual design phase. While the Transfer matrix method is commonly and conveniently used at Mid-High frequencies for the calculation of a trimmed panel, the simulation of energy transfer at low frequencies must take into account modal interactions between the vehicle component and the acoustic environment.

For (benchmark) tests it is not only useful to study the acoustic performance of the whole vehicle, but also to assess separate components such as the engine. Reflections inside the engine bay bias the acoustic radiation estimated with sound pressure based solutions. Consequently, most current methods require dismounting the engine from the car and installing it in an anechoic room to measure the sound emitted. However, this process is laborious and hard to perform. In this paper, two particle velocity based methods are proposed to characterize the sound radiated from an engine while it is still installed in the car. Particle velocity sensors are much less affected by reflections than sound pressure microphones when the measurements are performed near a radiating surface due to the particle velocity's vector nature, intrinsic dependency upon surface displacement and directivity of the sensor. Therefore, the engine does not have to be disassembled, which saves time and money.

To provide a feasible transitional solution from all-by-human driving style to fully autonomous driving style, this paper proposed concept and its control algorithm of a robust lane-keeping ‘co-pilot’ system. In this a semi-autonomous system, Learning based Model Predictive Control (LBMPC) theory is employed to improve system's performance in target state tracking accuracy and controller's robustness. Firstly, an approximate LTI model which describes driver-vehicle-road closed-loop system is set up and real system's deviations from the LTI system resulted by uncertainties in the model are regarded as bounded disturbance. The LTI model and bounded disturbances make up a nominal model. Secondly, a time-varying model which is composed of LTI model and an ‘oracle’ component is designed to observe the possible disturbances numerically and it is online updated using Extended Kalman Filter (EKF).

Since the amount of emitted CO2 is directly related to car fuel economy, attention is being drawn to DISI (Direct-Injection Spark-Ignition) engines, which have better fuel economy than conventional gasoline engines. However, it has been a problem that the rich air-fuel mixtures associated with fuel films during cold starts due to spray impingement produce particulate matter (PM). In predicting soot formation, it is important to predict the mixture field precisely. Thus, accurate spray and film models are a prerequisite of the soot model. The previous models were well matched with low-speed collision conditions, such as those of diesel engines, which have a relatively high ambient pressure and long traveling distances. Droplets colliding at low velocities have an order of magnitude of kinetic energy similar to that of the sum of the surface tension energy and the critical energy at which the splash occurs.

It is known that SEA is a rapid and simple methodology for analyzing complex vibroacoustic systems. However, the SEA principle is not always valid and one has to be careful about the physical conditions at which the SEA principle is acceptable. In this study, the appropriate damping loss factor of the vehicle interior cavity is studied in the viewpoint of the modal overlap factor of the cavity and the decay per mean free path (DMFP) of the cavity. Virtual SEA tests are performed with an FE model combination, which is suggested by a previous study of Stelzer et al. for the simulation of the sound transmission loss (STL) of vehicle panel structure. The FE model combination is consisting of the body in white (BIW), an acoustical-excited hemisphere-shaped exterior cavity, and the interior cavity. It is found that the DMFP of the interior cavity is appropriate between 0.5 ~ 1 dB for applying SEA principle.

In the brake system, unevenly distributed disc-pad contact pressure not only leads to a falling-off in braking feeling due to uneven wear of brake pads, but also a main cause of system instability which leads to squeal noise. For this reason there have been several attempts to measure contact pressure distribution. However, only static pressure distribution has been measured in order to estimate the actual pressure distribution. In this study a new test method is designed to quantitatively measure dynamic contact pressure distribution between disc and pad in vehicle testing. The characteristics of dynamic contact pressure distribution are analyzed for various driving conditions and pad shape. Based on those results, CAE model was updated and found to be better in detecting propensity of brake squeal.

CO2 emission is more serious in recent years and automobile manufacturers are interested in developing technologies to reduce CO2 emissions. Among various environmental-technologies, the use of solar roof as an electric energy source has been studied extensively. For example, in order to reduce the cabin ambient temperature, automotive manufacturers offer the option of mounting a solar cell on the roof of the vehicle [1]. In this paper, we introduce the semi-transparent solar cell mounted on a curved roof glass and we propose a solar energy management system to efficiently integrate the electricity generated from the solar roof into internal combustion engine (ICE) vehicles. In order to achieve a high efficiency solar system in different driving, we improve the usable power other than peak power of solar roof. Peak power or rated power is measured power (W) in standard test condition (@ 25°C, light intensity of 1000W/m2(=1Sun)).

An investigation into two new control strategies for the vehicle Anti-lock Braking System (ABS) are made for a possible replacement of current non-optimal slip control methods. This paper applies two techniques in order to maximize the braking force without any wheel locking. The first considers the power dissipated by the brake actuator. This power method does not use slip to construct its reference signal for control. A heuristic approach is taken with this algorithm where one searches for the maximum power dissipated. This can open up easier implementation of regenerative braking concurrently with ABS on an electro-hydraulic braking system. Parameter scheduling is explored in this algorithm. The second algorithm employs the use of perturbation based Extremum Seeking Control (ESC) to provide a reference slip and a Youla controller in a negative feedback loop.

Impact resistance of plastic underbody parts was studied using simulated injection-molded specimen which can be tested according to different types of material used, injection molding variants like position and number of injection molding gates, and features of ribs. Material applied was glass fiber reinforced polyamide which can be used in underbody parts. Test was performed using several combinations of injection molding gates and rib types. From the test result, optimal design guide for plastic underbody parts was determined. Also, new high impact resistant plastic material made of glass fiber reinforced polyamide 66 (PA66) and polyamide 6 (PA6) alloy was developed and the material properties useful for CAE were determined. As a case study, oil pan and muffler housing were designed following the optimal design guide and CAE. And the reliability of the sample muffler housing designed was verified.

This paper focuses on the optimization of the cross-section of a panel type impact door beam. The key parameters of the cross-section of the beam were artificially changed by using a geometry morphing tool FCM (Fast Concept Modeler), which is plugged in to CATIA. Then, the metamodel of FE (Finite Element) analysis results was created and optimized using LS-OPT. The ANOVA (Analysis of Variance) analysis of results was carried out to find the factor of weight reduction. Finally, a new cross section concept was proposed to overcome the limitation of old structure. The optimization was carried out for the beam with the final cross-section to have 10 % or more reduction in total weight.

Textbook engine thermodynamics predicts that SI (Spark Ignition) engine efficiency η is a function of both the compression ratio CR of the engine and the specific heat ratio γ of the working fluid. In practice the compression ratio of the SI engine is often limited due to “knock”. Knock is in large part the effect of end gases becoming too hot and auto-igniting. Knock results in increase in heat transfer to the walls which negatively affects efficiency. Not to mention damages to the piston. One way to lower the end-gas temperature is to cool the intake gas before inducting it into the combustion chamber. With colder intake gases, higher CR can be deployed, resulting in higher efficiencies. In this regard, we investigated the efficiency of a standard Waukesha CFR engine. The engine is operated in the SI engine mode, and was operated with two differing mixtures at different temperatures.

We assessed the engine-out emissions of an ultra-low sulfur diesel (ULSD) and a neat hydrogenated vegetable oil (HVO) from a light-duty diesel truck equipped with common rail direct injection. The vehicle was tested at least twice on each fuel using the LA-92 drive cycle and at steady-state conditions at 30 mph and 50 mph at different loads. Results showed reductions in the engine-out total hydrocarbon (THC), carbon monoxide (CO), nitrogen oxide (NOx), and particulate emissions with HVO. The reductions in soot mass, solid particle number, and particulate matter (PM) mass emissions with HVO were due to the absence of aromatic and polyaromatic hydrocarbon compounds, as well as sulfur species, which are known precursors of soot formation. Volumetric fuel economy, calculated based on the carbon balance method, did not show statistically significant differences between the fuels.

Two-mode hybrid architectures with three planetary gear sets and four clutches will bring both flexibility and complexity to energy management of powertrains. In order to take full advantage of the increased degrees of freedom, highly delicate operation strategies are needed. We develop transmission efficiency models for power-split modes, and present a mode shift strategy assuming no battery power. When battery load leveling is additionally considered, the respective optimal operation set for each mode can be obtained and compared to yield a mode shift algorithm for general hybrid operation situations. The investigation of the strategies shows how frequently each mode is used, and verifies the effectiveness of fixed gear operations. We check the validity of the strategies by applying the algorithm to dynamic optimization and by predicting how it works during an actual driving simulation.

This paper describes a driving control algorithm based on skid steering for a Robotic Vehicle with Articulated Suspension (RVAS). The driving control algorithm consists of four parts; speed controller for tracking of the desired speeds, yaw rate controller which computes a yaw moment input to track desired yaw rates, longitudinal tire force distribution which determines an optimal desired longitudinal tire force and wheel torque controller which determines a wheel torque command at each wheel to keep slip ratio at each wheel below a limit value as well as track the desired tire force. Longitudinal and vertical tire force estimators are designed for optimal tire force distribution and wheel slip control. The dynamic model of RVAS for simulation study is validated using vehicle test data.

Plug-in hybrid electric vehicles (PHVs) consume both fossil fuel and grid electricity, which imposes emission testing challenges on the current constant volume sampler (CVS) test method. One reason is that in the charge-depleting cycle, PHVs having all-electric range operate the engine for a small portion of the traction energy need, causing the CVS to overdilute the exhaust gas. The other reason is that the dilution factor (DF) in the EPA calculation has an error caused by ignoring the CO₂ concentration in ambient air. This paper evaluates these challenges by testing a Toyota PHV on the industry standard CVS system combined with additional continuous sampling methodology for continuous diluents, smooth approach orifice (SAO) measurement for ambient air flow, and fuel flow meter (FFM) measurement for fuel consumption. The current EPA DF can produce an error resulting in higher mass calculation.