Search Results

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.

Pressure variation during engine combustion generates torque fluctuation that is delivered through the driveline. Torque fluctuation delivered to the tire shakes the vehicle body and causes the body components to vibrate, resulting in booming noise. HKMC (Hyundai Kia Motor Company)’s TMED (Transmission Mounted Electric Device) type generates booming noises due to increased weight from the addition of customized hybrid parts and the absence of a torque converter. Some of the improvements needed to overcome this weakness include reducing the torsion-damper stiffness, adding dynamic dampers, and moving the operation point of the engine from the optimized point. These modifications have some potential negative impacts such as increased cost and sacrificed fuel economy. Here, we introduce a method of reducing lock-up booming noise in an HEV at low engine speed.

High-voltage battery system plays a critical role in eco-friendly vehicles due to its effect on the cost and the electric driving range of eco-friendly vehicles. In order to secure the customer pool and the competitiveness of eco-vehicle technology, vehicle electrification requires lowering the battery cost and satisfying the customer needs when driving the vehicles in the real roads, for example, maximizing powers for fun drive, increasing battery capacities for achieving appropriate trip distances, etc. Because these vehicle specifications have a critical effect on the high-voltage battery specification, the key technology of the vehicle electrification is the appropriate decision on the specification of the high-voltage battery system, such as battery capacity and power. These factors affect the size of battery system and vehicle under floor design and also the profitability of the eco-friendly vehicles.

This paper presents the second part of a multi-phased, both experimental and numerical project, devoted to the use of Virtual Prototyping techniques for seat design. The aim of this stage is to assess the capabilities of a CAE methodology to predict some comfort-related mechanical parameters, such as overall hardness and plushness, as a base engineering approach to quantify an occupant perception of both long- and short-term comfort. For hardness, a simple human surrogate (SAE AM50 Buttock Form) is applied on the bottom cushion of a fully trimmed, current production FORD seat, following a load cycle. For initial softness, a round probe is indented at different locations of both backrest and bottom cushions, following loading cycles. The resulting load-deflection curves predicted by numerical simulation are in good agreement with the experimental ones.

3D digital human modeling (DHM) tools for vehicle packaging facilitate ergonomic design and evaluation based on anthropometry, comfort, and force analysis. It is now possible to quickly predict postures and positions for drivers with selected anthropometry based on ergonomics principles. Despite their powerful visual representation technology for human movements and postures, these tools are still questioned with regard to the validity of the output they provide, especially when predictions are made for different populations. Driving postures and positions of two populations (i.e. North Americans and Koreans) were measured in actual and mock-up SUVs to investigate postural differences and evaluate the results provided by a DHM tool. No difference in driving postures was found between different stature groups within the same population. Between the two populations, however, preferred angles differed for three joints (i.e., ankle, thigh, and hip).

Shudder vibration of a hydraulic power steering system during parking maneuver was studied with numerical and experimental methods. To quantify vibration performance of the system and recognize important stimuli for drivers, a shudder metric was derived by correlation between objective measurements and subjective ratings. A CAE model for steering wheel vibration analysis was developed and compared with measured data. In order to describe steering input dependency of shudder, a new dynamic friction modeling method, in which the magnitude of effective damping is determined by average velocity, was proposed. The developed model was validated using the measured steering wheel acceleration and the pressure change at inlet of the steering gear box. It was shown that the developed model successfully describes major modes by comparing the calculated FRF of the hydraulic system with measured one from the hydraulic excitation test.

Parallel Hybrid Electric Vehicle consists of internal combustion engine, engine clutch, motor, automatic transmission, Integrated Starter Generator (ISG), and battery. Due to hybridizations such as using engine clutch to disengage the internal combustion engine and omitting torque converter from the automatic transmission to increase fuel economy, drivability will not be same as conventional vehicle. To ensure drivability comparable to conventional vehicle, dynamic simulation has been utilized to foresee the drivability issues for the proposed hybrid system and ideas for improvements are tested in simulation. CoSimulation of AMESim vehicle model and Simulink Hybrid Control Unit (HCU) model has been used to test and improve HCU logic.

A systematic process of optimization is suggested to obtain the best control maps for a parallel type hybrid electric vehicle. Taking the fuel consumption as the cost function and driving cycle as part of the constraints, an optimization problem for CVT pulley ratio control and motor torque control can be formulated. The change of the battery charge state between the start and end point of the given driving cycle also works as a constraint. In order to see the effect of various control strategies on system behavior and overall fuel consumption, a simulation model was built to accommodate the functional blocks representing hybrid powertrain subsystem components and corresponding control units.

In general, driving performance is developed to meet preference of average customers. But there is no single standardized guideline which can satisfy various driving tastes of all drivers whose gender, cultural background, and age are different. To resolve this issue, automotive companies have introduced drive mode buttons which drivers can manually select from Normal, Eco, and Sport driving modes. Although this multi-mode manual systems is more efficient than single-mode system, it is in a transient state where drivers need to go through troubles of frequently selecting their preferred drive mode in volatile driving situations It is also doubtful whether the three-categorized driving mode can meet complex needs of drivers.. In order to settle these matters, it is necessary to analyze individual driving style automatically and to provide customized driving performance service in real time.

One of the ways to improve the fuel efficiency of the HEV (Hybrid and Electric Vehicles) is to optimize automotive electric system. In order to achieve this, the LDC (Low voltage DC-DC Converter) variable voltage was controlled. Using the ADAS (Advanced Driver Assistance System) map, the charge-discharge behaviors of 12V lead-acid battery was predicted during driving so that, the battery could be charged efficiently. In this study, the feedback control system for 12V battery discharging was designed to compromise between the 12V battery SOC (State of Charge) and the driving conditions at different traffic points. In contrast to earlier approaches, this experimental result indicates that the LDC variable voltage control based on ADAS is able to reduce the LDC average output power by 17.1% therefore, increasing fuel efficiency and ensuring the durability of the 12V battery.

Conventional EPS (Electric Power Steering) systems are operated by one type of steering tuning map set by steering test drivers before being released to customers. That is, the steering efforts can't change in many different driving conditions such as road conditions (low mu, high mu and unpaved roads) or some specific driving conditions (sudden stopping, entering into EPS failure modes and full accelerating). Those conditions can't give drivers consistent steering efforts. This paper approached the new concept technology detecting those conditions by using vehicle and EPS sensors such as tire wheel speeds, vehicle speed, steering angle, steering torque, steering speed and so on. After detecting those conditions and judging what the best steering efforts for safe vehicle driving are, EPS systems automatically can be changed with the steering friction level and selection of steering optimized mapping on several conditions.

Traditional automotive seat development has relied on a series of physical prototypes that are evaluated and refined in an iterative fashion. Costs are managed by sharing prototypes across multiple attributes. To further manage costs, many OEMs and Tier 1s have, over the past decade, started to investigate various levels of virtual prototyping. The change, which represents a dramatic paradigm shift, has been slow to materialize since virtual prototyping has not significantly reduced the required number of physical prototypes. This is related to the fact virtual seat prototyping efforts have been focused on only selected seat attributes - safety / occupant positioning and mechanical comfort are two examples. This requires that physical prototypes still be built for seat attributes like craftsmanship, durability, and thermal comfort.

Professional bus drivers are highly exposed to physical fatigue and work-related injuries because driving task includes complicated actions that require a variety of ability and cause extreme concentration or strain. For this reason, there has always been some sense of concern regarding driver fatigue, especially for drivers of commercial vehicles. In this study, we have tried to analyze quantitative fatigue degree of urban bus drivers by measuring their physiological signals. The investigation is made up of the following approaches: a traditional questionnaire survey and video-ethnographic method with 4-way cameras. The close-circuit cameras are installed to observe the upper and lower body of real drivers when they are in driving or even resting. This approach can help to understand urban bus drivers' behaviors and fatigue-related issues. Based on the video-ethnographic investigation results above, we have got certain patterns of drivers.

The success of improved fuel economy is the proper integration of thermal management components which are appropriately performed to reduce friction and wasted energy. The thermal management systems of vehicle are able to balance the multiple needs such as heating, cooling, or appropriate operation within specified temperature ranges of propulsion systems. Since the propulsion systems of vehicle have changed from a single energy source based on conventional internal combustion engine to hybrid system including more electrical system such as full type of hybrid electric vehicle or plug-in hybrid electric vehicles, a new transition associated with vehicle thermal management arises. More efficient thermal management systems are required to improve the fuel economy in the hybrid electric vehicles because of the driving of electric traction motor and the increase of engine off time. The decrease of engine operation time may not sustain the proper temperature ranges of engine and gearbox.

This paper examines the effect of pulse-and-glide (PnG) driving strategies on the fuel efficiency when applied on parallel HEVs. Several PnG strategies are proposed, and these include the electrical, mechanical, and combined PnG strategies. The electrical PnG strategy denotes the hybrid powertrain control tactics in which the battery is charged or discharged according to the power demanded while maintaining the constant vehicle speed. On the other hand, the mechanical PnG strategy denotes the powertrain control tactics in which the vehicle accelerates or decelerates according to the power load while minimizing the battery usage. The combined PnG strategy involves both electrical and mechanical strategies to find a balanced point in between them. Here, a tradeoff relationship between the fuel efficiency and the vehicle drivability related to the tracking performance of the desired target speed is revealed.

To develop future electrical and autonomous cars, it is important to virtually test the car in real driving circumstances, including on wet road or under heavy rain conditions. It is especially critical to check that no water prevents the sensors of the driving assistance systems or autonomous cars from working properly, that water intrusion does not disturb electrical equipment, and that the driver’s visibility remains good under rain condition. ESI Group has introduced the Finite Point Method (FPM) in Virtual Performance Solution (VPS) as a CFD mesh free module in order to simulate the interaction of water with the car structure. It was initially specialized for tank sloshing and water drain applications for car closures and is now extended to other application fields. The objective is to enable a holistic prediction of the car behavior under realistic driving conditions, using a virtual car prototype.

This study investigates how hilly road profiles affect the optimal energy management strategy for fuel cell hybrid electric vehicle (FCHEV) with various battery sizes. First, a simplified FCHEV model is developed to describe power and energy flows throughout the powertrain and evaluate hydrogen consumption. Then, an optimal control problem is formulated to find the globally optimal energy management strategy of FCHEV over driving cycles with road elevation profile. In order to solve the optimal energy management problem of the FCHEV, Dynamic Programming, a dynamic optimization method, is used, and their results are analyzed to find out how hilly road conditions affect the optimal energy management strategies. The results show that the optimal energy management with a smaller battery tends to actively prepare (e.g. pre-charge/pre-discharge) for uphill/downhill roads in order not to violate the battery state of charge (SoC) bounds.

Suspension is a system which operates dynamically according to road condition unlike other system statically mounted to the body. Especially this is more remarkable in high performance vehicle because there are more high inputs from road to suspension than normal vehicle. For this reason, the tightening torque of suspension system of high performance vehicle is more important than other systems and normal vehicle. To support the clamping between parts against force from road when cornering, optimized tightening torque is required to maximize R&H performance. For this optimization, it should be conducted first to comprehend how much performance effects on vehicle by tightening torque. This paper presents relationship between tightening torque of suspension parts hardware and R&H performance.

Today, many automakers are using LED lamp sources in exterior lamps to establish brand awareness and introduce specialized lamp designs. These eye-catching LED lamp source solutions require many control functions as the lamp functions are diversified and advanced, and accordingly the requirements for standardization and optimization of controllers are increasing. In particular, our LED rear combination lamps have a variety of LED loads according to the design of the lamp model, the installation position, and the diagnostic regulations, so that the design complexity and the number of specifications of the controller are increased [4]. In recent years, more and more aesthetic designs and new technologies are used by various automakers to optimize their controllers in cooperation with global partners to optimize costs [1].

This study was conducted to develop and validate a multidimensional measure of shift quality as perceived by drivers during kick-down shift events for automatic transmission vehicles. As part of the first study, a survey was conducted among common drivers to identify primary factors used to describe subjective gear-shifting qualities. A factor analysis on the survey data revealed four semantic subdimensions. These subdimensions include responsiveness, smoothness, unperceivable, and strength. Based on the four descriptive terms, a measure with semantic scales on each subdimension was developed and used in an experiment as the second study. Twelve participants drove and evaluated five vehicles with different gear shifting patterns. Participants were asked to make kick-down events with two different driving intentions (mild vs. sporty) across three different speeds on actual roadway (local streets and highway).