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For the vehicles with frequent stop-start operations, fuel consumption can be reduced significantly by implementing stop-start operation. As one way to realize this goal, the pneumatic hybrid technology converts kinetic energy to pneumatic energy by compressing air into air tanks installed on the vehicle. The compressed air can then be reused to drive an air starter to realize a regenerative stop-start function. Furthermore, the pneumatic hybrid can eliminate turbo-lag by injecting compressed air into manifold and a correspondingly larger amount of fuel into the cylinder to build-up full-load torque almost immediately. This paper takes the pneumatic hybrid engine as the research object, focusing on evaluating the improvement of fuel economy of multiple air tanks in different test cycles. Also theoretical analysis the benefits of extra boost on reducing turbo-lag to achieve better performance.

China is the world’s largest automotive producer and has the world’s biggest automobile market. However, in the past decades, the development of China’s automotive industry has depended primarily on the foreign direct investment; domestic automakers have struggled in the lower ranks of car producers. In recent years, China’s automotive industry, supported by government policies, has been improving their Research and Development (R&D) capacity, to compete with their international peers. Against this background, China’s automotive industry requires a large number of R&D professionals who have not only a higher degree but also the applied and practical knowledge and skills of research. For the purpose of meeting the industry’s needs, a new Professional Automotive Engineering Masters Programme was launched in 2009, which aims to deliver the Masters to be the R&D professionals in the future.

This paper reports on an investigation into the potential for a thermoelectric generator (TEG) to improve the fuel economy of a mild hybrid vehicle. A simulation model of a parallel hybrid vehicle equipped with a TEG in the exhaust system is presented. This model is made up by three sub-models: a parallel hybrid vehicle model, an exhaust model and a TEG model. The model is based on a quasi-static approach, which runs a fast and simple estimation of the fuel consumption and CO2 emissions. The model is validated against both experimental and published data. Using this model, the annual fuel saving, CO2 reduction and net present value (NPV) of the TEG’s life time fuel saving are all investigated. The model is also used as a flexible tool for analysis of the sensitivity of vehicle fuel consumption to the TEG design parameters. The analysis results give an effective basis for optimization of the TEG design.

In this paper the effects of a rough underbody on the rear wake structure of a simplified squareback model (the Windsor model) is investigated using balance measurements, base pressure measurements and two and three component planar PIV. The work forms part of a larger study to develop understanding of the mechanisms that influence overall base pressure and hence the resulting aerodynamic drag. In the work reported in this paper the impact of a rough underbody on the base pressure and wake flow structures is quantified at three different ground clearances. The underbody roughness has been created through the addition of five roughness strips to the underbody of the model and the effects on the wake at ground clearances of 10.3%, 17.3% and 24.2% of the model height are assessed. All work has been carried out in the Loughborough University Large Wind Tunnel with a ¼ scale model giving a blockage ratio of 4.4% for a smooth under-body or 4.5% with the maximum thickness roughness strips.

Sports Utility Vehicles (SUVs) typically have a blunt rear end shape (for design and practicality), however this is not beneficial for aerodynamic drag. Drag can be reduced by a number of passive and active methods such as tapering and blowing into the base. In an effort to combine these effects and to reduce the drag of a visually square geometry slots have been introduced in the upper side and roof trailing edges of a squareback geometry, to take air from the freestream and passively injects it into the base of the vehicle to effectively create a tapered body. This investigation has been conducted in the Loughborough University’s Large Wind Tunnel with the ¼ scale generic SUV model. The basic aerodynamic effect of a range of body tapers and straight slots have been assessed for 0° yaw. This includes force and pressure measurements for most configurations.

Recovering the braking energy and reusing it can significantly improve the fuel economy of a vehicle which is subject to frequent braking events such as a city bus. As one way to achieve this goal, pneumatic hybrid technology converts kinetic energy to pneumatic energy by compressing air into tanks during braking, and then reuses the compressed air to power an air starter to realize a regenerative Stop-Start function. Unlike the pure electric or hybrid electric passenger car, the pneumatic hybrid city bus uses the rear axle to achieve regenerative braking function. In this paper we discuss research into the blending of pneumatic regenerative braking and mechanical frictional braking at the rear axle. The aim of the braking function is to recover as much energy as possible and at the same time distribute the total braking effort between the front and rear axles to achieve stable braking performance.

The performance of energy flow management strategies is essential for the success of hybrid electric vehicles (HEVs), which are considered amongst the most promising solutions for improving fuel economy as well as reducing exhaust emissions. The heavy duty HEVs engaged in cycles characterized by start-stop configuration has attracted widely interests, especially in off-road applications. In this paper, a fuzzy equivalent consumption minimization strategy (F-ECMS) is proposed as an intelligent real-time energy management solution for heavy duty HEVs. The online optimization problem is formulated as minimizing a cost function, in terms of weighted fuel power and electrical power. A fuzzy rule-based approach is applied on the weight tuning within the cost function, with respect to the variations of the battery state-of-charge (SOC) and elapsed time.

Engine downsizing is a promising trend to decarbonise vehicles but it also poses a challenge on vehicle driveability. Electric turbochargers can solve the dilemma between engine downsizing and vehicle driveability. Using the electric turbocharger, the transient response at low engine speeds can be recovered by air boosting assistance. Meanwhile, the introduction of electric machine makes the engine control more complicated. One emerging issue is to harness the augmented engine air system in a systematical way. Therefore, the boosting requirement can be achieved fast without violating exhaust emission standards. Another raised issue is to design an real time energy management strategy. This is of critical to minimise the required battery capacity. Moreover, using the on-board battery in a high efficient way is essential to avoid over-frequent switching of the electric machine. This requests the electric machine to work as a generator to recharge the battery.

This work describes the application of Non-Linear Autoregressive Models with Exogenous Inputs (NLARX) in order to predict the NOx emissions of heavy-duty diesel engines. Two experiments are presented: 1.) a Non-Road-Transient-Cycle (NRTC) 2.) a composition of different engine operation modes and different engine calibrations. Data sets are pre-processed by normalization and re-arranged into training and validation sets. The chosen model is taken from the MATLAB Neural Network Toolbox using the algorithms provided. It is teacher forced trained and then validated. Training results show recognizable performance. However, the validation shows the potential of the chosen method.

It is recognized that the heavier vehicles, the more emissions, thus the more imperative to electrify. In this study, long haul heavy-duty trucks are referred as HDTs, which are recognized as one of the hard-to-electrify vehicle segments, though the automotive industry has gained trending advantages of electrifying both light-duty cars and SUVs. Since big rigs such as Class 8 HDTs have significant road-block challenges for electrification due to the demanding long-hour work cycles in all weathers, this study focuses on quantifying those electrification challenges by taking advantage of the public data of Class 8 tractors & trailers. Tesla Semi is the research target though its vehicle spec data is sorted out with fragmentary information in the public domain. The key task is to analyze the battery capacity requirements due to environmental temperature and inherent aging over the lifespan.

Sports Utility Vehicles (SUVs) often have blunt rear end geometries for design and practicality, which is not typically aerodynamic. Drag can be reduced with a number of passive and active methods, which are generally prioritised at zero yaw, which is not entirely representative of the “on road” environment. As such, to combine a visually square geometry (at rest) with optimal drag reductions at non-zero yaw, an adaptive system that applies vertical side edge tapers independently is tested statically. A parametric study has been undertaken in Loughborough University’s Large Wind Tunnel with the ¼ scale Windsor Model. The aerodynamic effect of implementing asymmetric side tapering has been assessed for a range of yaw angles (0°, ±2.5°, ±5° and ±10°) on the force and moment coefficients.

Hybrid electric vehicles offer significant fuel economy benefits, because battery and fuel can be used as complementing energy sources. This paper presents the use of dynamic programming to find the optimal blend of power sources, leading to the lowest fuel consumption and the lowest level of harmful emissions. It is found that the optimal engine behavior differs substantially to an on-line adaptive control system previously designed for the Lotus Evora 414E. When analyzing the trade-off between emission and fuel consumption, CO and HC emissions show a traditional Pareto curve, whereas NOx emissions show a near linear relationship with a high penalty. These global optimization results are not directly applicable for online control, but they can guide the design of a more efficient hybrid control system.

It has been recognised that the ideal flow conditions that exist in the modern automotive wind tunnel do not accurately simulate the environment experienced by vehicles on the road. This paper investigates the effect of varying one flow parameter, freestream turbulence, and a single shape parameter, leading edge radius, on aerodynamic drag. The tests were carried out at model scale in the Loughborough University Wind Tunnel, using a very simple 2-box shape, and in the MIRA Full Scale Wind Tunnel using the MIRA squareback Reference Car. Turbulence intensities up to 5% were generated by grids and had a strong effect on transcritical Reynolds number and Reynolds sensitivity at both model scale and full scale. There was a good correlation between the results in both tunnels.

GTDI engines are becoming more efficient, whether individually or part of a HEV (Hybrid Electric Vehicle) powertrain. For the latter, this efficiency manifests itself as increase in zero emissions vehicle mileage. An ideal device for energy recovery is a turbogenerator (TG), and, when placed downstream the conventional turbine, it has minimal impact on catalyst light-off and can be used as a bolt-on aftermarket device. A Ricardo WAVE model of a representative GTDI engine was adapted to include a TG (Turbogenerator) and TBV (Turbine Bypass Valve) with the TG in a mechanical turbocompounding configuration, calibrated using steady state mapping data. This was integrated into a co-simulation environment with a SISO (Single-Input, Single-Output) dynamic controller developed in SIMULINK for the actuator control (with BMEP, manifold air pressure and TG pressure ratio as the controlled variables).

Electric vehicles offer cleaner transportation with lower emissions, thus their increased popularity. Although, electric powertrains contribute to quieter vehicles, the shift from internal combustion engines to electric powertrains presents new Noise, Vibration, and Harshness challenges. Unlike traditional engines, electric powertrains produce distinctive tonal noise, notably from motor whistles and gear whine. These tonal components have frequency content, sometimes above 10 kHz. Furthermore, the housing of the powertrain is the interface between the excitation from the driveline via the bearings and the radiated noise (NVH). Acoustic features of the radiated noise can be predicted by utilising the transmitted forces from the bearings. Due to tonal components at higher frequencies and dense modal content, full flexible multibody dynamics simulations are computationally expensive.

On future UAVs it is envisaged that the power requirements of all on-board electrical systems will increase. In most flight (mission) situations the installed power generation will have adequate capacity to operate the aircraft. It is possible that during abnormal situations such as coolant blockage the generators on-board may be forced to operate under very high load conditions. The main failure mechanism for a generator is overheating and subsequent disintegration of windings, hence the research problem being addressed here is to manage the loads upon the generator to prevent overheats. The research presented here summarizes the modeling of the generator and formation of the load management system. Results are presented showing the system reallocating loads after a fault during flight, preventing overheat of the generators and successfully completing the mission.

This paper surveys publications on automotive powertrain control, relating to modern GTDI (Gasoline Turbocharged Direct Injection) engines. The requirements for gasoline engines are optimising the airpath but future legislation suggests not only a finely controlled airpath but also some level of electrification. Fundamentals of controls modelling are revisited and advancements are highlighted. In particular, a modern GTDI airpath is presented based on basic building blocks (volumes, turbocharger, throttle, valves and variable cam timing or VCT) with an example of a system interaction, based on boost pressure and lambda control. Further, an advanced airpath could be considered with applications to downsizing and fuel economy. A further electrification step is reviewed which involves interactions with the airpath and requires a robust energy management strategy. Examples are taken of energy recovery and e-machine placement.

Thermoelectric generator (TEG) has received more and more attention in its application in the harvesting of waste thermal energy in automotive engines. Even though the commercial Bismuth Telluride thermoelectric material only have 5% efficiency and 250°C hot side temperature limit, it is possible to generate peak 1kW electrical energy from a heavy-duty engine. If being equipped with 500W TEG, a passenger car has potential to save more than 2% fuel consumption and hence CO2 emission reduction. TEG has advantages of compact and motionless parts over other thermal harvest technologies such as Organic Rankine Cycle (ORC) and Turbo-Compound (TC). Intense research works are being carried on improving the thermal efficiency of the thermoelectric materials and increasing the hot side temperature limit. Future thermoelectric modules are expected to have 10% to 20% efficiency and over 500°C hot side temperature limit.

In the globalization of the automotive businesses, manufacturing companies and their suppliers are forced to distribute the various lifecycle phases in different geographical locations. Misunderstandings arising from the variety of personnel involved, each with different requirements, backgrounds, roles, cultures and skills for example can result in increased cost and development time. To enable collaborating companies to have a common platform for interaction, the COMPANION project at Loughborough University has been undertaken to develop a common model-based environment for manufacturing automotive engines. Through the use of this environment, the stakeholders will be able to “visualize” consistently the evolution of automated systems at every lifecycle stage i.e. requirements definition, specification, design, analysis, build, evaluation, maintenance, diagnostics and recycle.

Full hybrid electric vehicles are usually defined by their capability to drive in a fully electric mode, offering the advantage that they do not produce any emissions at the point of use. This is particularly important in built up areas, where localized emissions in the form of NOx and particulate matter may worsen health issues such as respiratory disease. However, high degrees of electrification also mean that waste heat from the internal combustion engine is often not available for heating the cabin and for maintaining the temperature of the powertrain and emissions control system. If not managed properly, this can result in increased fuel consumption, exhaust emissions, and reduced electric-only range at moderately high or low ambient temperatures negating many of the benefits of the electrification. This paper describes the development of a holistic, modular vehicle model designed for development of an integrated thermal energy management strategy.