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Hat-sections, single and double, made of steel are frequently encountered in automotive body structural components. These components play a significant role in terms of impact energy absorption during vehicle crashes thereby protecting occupants of vehicles from severe injury. However, with the need for higher fuel economy and for compliance to stringent emission norms, auto manufacturers are looking for means to continually reduce vehicle body weight either by employing lighter materials like aluminum and fiber-reinforced plastics, or by using higher strength steel with reduced gages, or by combinations of these approaches. Unlike steel hat-sections which have been extensively reported in published literature, the axial crushing behavior of hat-sections made of fiber-reinforced composites may not have been adequately probed.

Tracked vehicles are widely used for agriculture, construction and many other areas. Due to high emissions, hybrid electric driveline has been applied to tracked vehicles. The hybrid powertrain design for the tracked vehicle has been researched for years. Different from wheeled vehicles, the tracked vehicle not only requires high mobility while straight driving, but also pursues strong steering performance. The paper takes the hybrid track-type dozers (TTDs) as an example and proposes an optimal design of a novel power-split powertrain for TTDs. The commercial hybrid TTD usually adopts the series hybrid powertrain, and sometimes with an extra steering mechanism, which has led to low efficiency and made the structure more complicated. The proposed three-planetary-gear power-split hybrid powertrain can overcome the problems above by utilizing the characteristics of planetary gear sets.

An energy management strategy is needed to optimally allocate the driver's power demands to different power sources in the fuel cell hybrid vehicles. The driver's power demand is modelled as a Markov process in which the transition probabilities are estimated on the basis of the observed sample paths. The Markov Decision Process (MDP) theory is applied to design a stochastic energy management strategy for fuel cell hybrid vehicles. This obtained control strategy was then tested on a real time simulation platform of the fuel cell hybrid vehicles. In comparison to the other 3 strategies, the constant bus voltage strategy, the static optimization strategy and the dynamic programming strategy, simulations in the Beijing bus driving cycle demonstrate that the obtained stochastic energy management strategy can achieve better performance in fuel economy in the same demand of dynamic.

The objective of this work is to develop a strategy to reduce the penalties in the diesel engine performance, fuel economy and HC and CO emissions, associated with the operation in the low temperature combustion regime. Experiments were conducted on a research high speed, single cylinder, 4-valve, small-bore direct injection diesel engine equipped with a common rail injection system under simulated turbocharged conditions, at IMEP = 3 bar and engine speed = 1500 rpm. EGR rates were varied over a wide range to cover engine operation from the conventional to the LTC regime, up to the misfiring point. The injection pressure was varied from 600 bar to 1200 bar. Injection timing was adjusted to cover three different LPPCs (Location of the Peak rate of heat release due to the Premixed Combustion fraction) at 10.5° aTDC, 5 aTDC and 2 aTDC. The swirl ratio was varied from 1.44 to 7.12. Four steps are taken to move from LTC to ALTC.

The objective of the research into modeling and simulation was to provide an improvement to the Wayne State EcoCAR 2 team’s math-based modeling and simulation tools for hybrid electric vehicle powertrain analysis, with a goal of improving the simulation results to be less than 10% error to experimental data. The team used the modeling and simulation tools for evaluating different outcomes based on hybrid powertrain architecture changes (hardware), and controls code development and testing (software). The first step was model validation to experimental data, as the plant models had not yet been validated. This paper includes the results of the team’s work in the U.S. Department of Energy’s EcoCAR 2 Advanced vehicle Technical Competition for university student teams to create and test a plug-in hybrid electric vehicle for reducing petroleum oil consumption, pollutant emissions, and Green House Gas (GHG) emissions.

To address the need of increasing fuel economy requirements, automotive Original Equipment Manufacturers (OEMs) are increasing the number of turbocharged engines in their powertrain line-ups. The turbine-driven technology uses a forced induction device, which increases engine performance by increasing the density of the air charge being drawn into the cylinder. Denser air allows more fuel to be introduced into the combustion chamber, thus increasing engine performance. During the inlet air compression process, the air is heated to temperatures that can result in pre-ignition resulting and reduced engine functionality. The introduction of the charge air cooler (CAC) is therefore, necessary to extract heat created during the compression process. The present research describes the physics and develops the optimized simulation method that defines the process and gives insight into the development of CACs.

The traditional vacuum booster is gradually replaced by Brake-by-Wire system (BBW) in modern passenger car, especially Electric Vehicle (EV). Some mechanical and hydraulic components are replaced by electronic components in Brake-by-Wire system. Using BBW system in modern passenger vehicles can not only improve the automotive safety performance, reliability and stability, but also promote vehicle maneuverability, comfort, fuel economy and environmental protection. Although vehicle's braking performance is greatly improved by using BBW, the system will inevitably consume some energy of the vehicle power supply, thus introducing unexpected drawback in comparison with the traditional vacuum assist braking system, since it doesn't need any electric power. Therefore, the analysis of energy consumption on typical main cylinder booster based BBW system under typical driving cycles will contribute to advanced design of current advanced braking system.

An automotive powertrain system consists of several interactive and linked nonlinear systems. This research focuses on the coordination of Gasoline Direct Injection (GDI) engine, transmission and emission aftertreatment systems. The goal is to design an optimal control strategy for driving performance, emissions (HC, CO, NOX), fuel economy and smoothness when switching engine mode and when shifting gears, under both discrete and continuous limitations. A multivariable control strategy is used to compromise among all powertrain subsystems to achieve optimal overall performance. A nonlinear discrete dynamic programming approach is proposed for hybrid system optimization. The complex multivariable automotive control problem is then simplified into an optimization problem. The feasibility of automotive hybrid control via the discrete dynamic programming approach is demonstrated by results from many numerical simulations under different operating conditions.

Vehicle weight-driven design comes amid rising higher fuel efficiency standards and must meet the criteria—pass proving ground (PG) test events that are equivalent to customer usage. Computer-aided engineering (CAE) fatigue analysis for PG is a successful push behind to digitally simulate vehicle durability performance with high fidelity. The need for vehicle weight reduction often arises in the vehicle development final phases when CAE methods, time, and tangible cost-effective opportunities are limited or nonexistent. In this research, a new CAE methodology is developed to identify opportunities for lightweight hole placement in the chassis structure and deliver a cost-effective lightweight solution with no additional impact on fatigue life. The successful application of this new methodology exhibits the effectiveness of the truck frame, which is the key chassis structure to support the body, suspension, and powertrain.

The automotive industry is aggressively pursuing fuel efficiency improvements through hybridization of production vehicles, and there are an increasing number of racing series adopting similar architectures to maintain relevance with current passenger car trends. Hybrid powertrains offer both performance and fuel economy benefits in a motorsport setting, but they greatly increase control complexity and add additional degrees of freedom to the design optimization process. The increased complexity creates opportunity for performance gains, but simulation based tools are necessary since hybrid powertrain design and control strategies are closely coupled and their optimal interactions are not straightforward to predict. One optimization-related advantage that motorsports applications have over production vehicles is that the power demand of circuit racing has strong repeatability due to the nature of the track and the professional skill-level of the driver.

Hybrid Electric Vehicles with a power split system provide a variety of possibilities to promote the fuel economy of vehicles and better adapt to various driving conditions. In this paper, a new power split system of a hybrid electric bus which consists of double planetary gear sets and a clutch is introduced. The system is able to decouple both the torque and speed of the engine from the road load, which makes it possible for the engine to operate on its optimal operation line (OOL). Considering the features of the system configuration and bus driving cycle, the driving mode of the bus is divided into Electric Vehicle (EV) mode, Electric Variable Transmission (EVT) mode and Parallel mode. By controlling the engagement of the clutch at high vehicle speed (after the mechanical point), the system operates in the parallel mode rather than EVT mode. This avoids the problem that the system efficiency sharply declines in high speed region which EVT configurations are generally faced with.

The platooning of connected automated vehicles (CAV) possesses the significant potential of reducing energy consumption in the Intelligent Transportation System (ITS). Moreover, with the rapid development of eco-driving technology, vehicle platooning can further enhance the fuel efficiency by optimizing the efficiency of the powertrain. Since road grade is a main factor that affects the energy consumption of a vehicle, the estimation of the road grade with high accuracy is the key factor for a connected vehicle platoon to optimize energy consumption using vehicle-to-vehicle (V2V) communication. Commonly, the road grade is quantified by single consumer grade global positioning system (GPS) with the geodetic height data which is rough and in the meter-level, increasing the difficulty of precisely estimating the road grade.

Traffic congestions are increasingly severe in urban areas, especially at the merging areas of the ramps and the arterial roads. Because of the complex conflict relationship of the vehicles in ramps and arterial roads in terms of time-spatial constraints, it is challenging to coordinate the motion of these vehicles, which may easily cause congestions at the merging areas. The connected and automated vehicles (CAVs) provides potential opportunities to solve this problem. A centralized merging control method for CAVs is proposed in this paper, which can organize the traffic movements in merging areas efficiently and safely. In this method, the merging control model is built to formulate the vehicle coordination problem in merging areas, which is then transformed to the discrete nonlinear optimization form. A simulation model is built to verify the proposed method.

Due to the potential on decreasing fuel consumption and design flexibility, parallel configurations are widely used for hybrid electric vehicles (HEVs). However, the fuel economy and economic profitability of parallel HEVs for heavy-duty truck applications under Chinese driving conditions still need to be investigated. It is uneasy to improve the fuel economy of parallel HEVs with a single electric motor from control perspective only. In this article, the battery size of the architecture is optimized by using the dynamic programming (DP) approach, based on a dynamic degradation model of the LiFePO4 battery. Moreover, based on the DP results, a near-optimal control strategy of the hybrid powertrain system for online application is proposed. Finally, with two economic assumptions, the initial costs, operation costs, and payback periods are obtained in a total cost of ownership framework perspective.

The new control algorithm for parallel hybrid electric vehicle is presented systematically, in which engine operation points are limited within higher efficient area by the control algorithm and the state of charge (SOC) is limited in a range in order to enhance the batteries' charging and discharging efficiency. In order to determine the ideal operating point of the vehicle's engine, the control strategy uses a lookup table to determine the torque output of the engine. The off-line simulation model of parallel HEV power train is developed which includes the control system and controlled objective (such as engine, electric motor, battery pack and so on). The results show that the control algorithm can effectively limite engine and battery operation points and much more fuel economy can be achieved than that of conventional one.

A multiple-injection combustion strategy has been developed for heated gasoline direct injection compression ignition (HGCI). Gasoline was injected into a 0.4L single cylinder engine at a fuel pressure of 300bar. Fuel temperature was increased from 25degC to a temperature of 280degC by means of electric injector heater. This approach has the potential of improving fuel efficiency, reducing harmful CO and UHC as well as particulate emissions, and reducing pressure rise rates. Moreover, the approach has the potential of reducing fuel system cost compared to high pressure (>500bar) gasoline direct injection fuel systems available in the market for GDI SI engines that are used to reduce particulate matter. In this study, a multiple injection strategy was developed using electric heating of the fuel prior to direct fuel injection at engine speed of 1500rpm and load of 12.3bar IMEP.

The superior fuel economy of direct injection internal combustion engines (diesel and gasoline) is related to use of a high compression ratio to auto-ignite the fuel and the overall lean combustible mixture. Two of the major problems in diesel engine emissions are the NOx and soot emissions, which are caused by the heterogeneity of the charge and the properties of the diesel fuel. Conventional Direct Injection Spark Ignition Gasoline engines don't have these problems because of the fuel properties particularly its volatility. However, its efficiency and specific power output are limited by the knock, knock produced preignition and the sporadic preignition phenomenon. The Gasoline Direct Injection Compression Ignition (GDICI) engine combines the superior features of the two engines by increasing the compression ratio and use of gasoline as a fuel.

Gasoline particulate filter (GPF) is considered a suitable solution to meet the increasingly stringent particle number (PN) regulations for both gasoline direct injection (GDI) and multi-port fuel injection (MPI) engines. Generally, GDI engines emit more particulate matter (PM) and PN. In recent years, GDI engines have gained significant market penetration in the automobile industry owing to better fuel economy and drivability. In this study, an accelerated ash loading method was tested by doping lubricating oil into the fuel for a GDI engine. Emission tests were performed at different ash loads with different driving cycles and GPF combinations. The results showed that the GPF could significantly reduce particle emissions to meet the China 6 regulation. With further ash loading, the filtration efficiency increased above 99% and the effects on fuel consumption and backpressure were found to be limited, even with an ash loading of up to 50 g/l.

The effects of different blends of Soybean Methyl Ester (biodiesel) and ultra low sulfur diesel (ULSD) fuel: B-00 (ULSD), B-20, B-40, B-60, B-80 and B-100 (biodiesel); on autoignition, combustion, performance, and engine out emissions of different species including particulate matter (PM) in the exhaust, were investigated in a single-cylinder, high speed direct injection (HSDI) diesel engine equipped with a common rail injection system. The engine was operated at 1500 rpm under simulated turbocharged conditions at 5 bar IMEP load with varied injection pressures at a medium swirl of 3.77 w ithout EGR. Analysis of test results was done to determine the role of biodiesel percentage in the fuel blend on the basic thermodynamic and combustion processes under fuel injection pressures ranging from 600 bar to 1200 bar.

Gasoline direct injection (GDI) engines have been developed rapidly in recent years, driven by stringent legislative requirements on vehicle fuel efficiency and emissions. However, one challenge facing GDI is the formation of particulate emissions, particularly with the presence of injector tip deposits. The Chinese market features some gasoline fuels that contain no detergent additives and are prone to deposit formation, which can affect engine performance and emissions. The use of detergent additives to mitigate the formation of injector deposits in a GDI engine was investigated in this study by testing a 1.5L turbocharged GDI engine available in the Chinese market. The engine was operated both on base gasoline and on gasoline dosed with detergent additives to evaluate the effect on injector deposit formation and engine performance and emissions.