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Li-ion batteries (LIBs) optimum performance and lifetime depend on temperature, with the commonly suggested operating temperature being in the range of 25 to 40 °C. It's also crucial to keep the temperature difference between battery cells below 5°C. Operation at different temperature ranges can adversely affect or degrade the performance and lifetime of LIBs. A battery thermal management system (BTMS) is essential for keeping the battery temperature within the optimum range. This paper aims to develop and analyze the BTMS for an electric heavy-duty truck. To achieve this aim, battery cells and modules are modelled in ANSYS Fluent software. Validation with experimental results and mesh sensitivity studies are also performed to increase confidence in simulation data. The model is then analyzed for a specific cooling systems to investigate its effect on battery thermal performance during the operation.

Reducing exhaust emissions has been a major focus of research for a number of years since internal combustion engines (ICE) contribute to a large number of harmful particles entering the environment. As a way of reducing emissions and helping to tackle climate change, many countries are announcing that they will ban the sale of new ICE vehicles soon. Electrical vehicles (EVs) represent a popular alternative vehicle propulsion system. However, although they produce zero exhaust emissions, there is still concern regarding non-exhaust emission, such as brake dust, which can potentially cause harm to human health and the environment. Despite EVs primarily using regenerative braking, they still require friction brakes as a backup as and when required. Moreover, most EVs continue to use the traditional grey cast iron (GCI) brake rotor, which is heavy and prone to corrosion, potentially exacerbating brake wear emissions.

Electrification is one of the main solutions for the decarbonization of the transport system. It is employed widely by the automotive industry in light- and medium-duty vehicles and recently started to be considered in heavy-duty applications. However, powertrain electrification of heavy-duty vehicles, especially for Class 8 trucks, is very challenging. In this study, the battery-electric powertrain energy and technical performance of a DAF 44 tones truck are compared for two different electric drives. The case study truck is modeled in AVL CRUISE M software and the battery electric powertrain is evaluated for long haul driving cycle. The minimum number of battery packs is determined by defining the lowest energy consumption of the powertrain designed for the proposed drive cycle. Also, a transient analysis is accomplished to investigate the impact of various electric drives on energy consumption and performance of the proposed electric powertrain.

While the shift to vehicle electrification plays a pivotal role in governments’ targets towards carbon neutrality, there exists certain technical challenges that need to be addressed. The motorsport car industry is also affected by this policy with the electric cars being included in the formula SAE and formula E competitions as one of the main categories. Moreover, there is a gap in the literature in energy assessment of the electric powertrain used in Formula SAE (FSAE) and Formula Student (FS) cars. In this paper, a Formula Student electric car powertrain was designed as a case study for energy analysis. The proposed electric powertrain is equipped with a four-wheel drive system. The vehicle was modelled in AVL CRUISE M software using technical and measured lab data as input parameters. Simulations were run in a transient driving cycle for a real circuit layout used in previous SAE competitions.

Due to the variability of real traffic conditions for vehicle testing, real-world vehicle performance estimation using simulation method become vital. Especially for heavy duty vehicles (e.g. 40 t trucks), which are used for international freight transport, real-world tests are difficult, complex and expensive. Vehicle simulations use mathematical methods or commercial software, which take given driving cycles as inputs. However, the road situations in real driving are different from the driving cycles, whose speed profiles are obtained under specific conditions. In this paper, a real-world vehicle performance estimation method using simulation was proposed, also it took traffic and real road situations into consideration, which made it possible to investigate the performance of vehicles operating on any roads and traffic conditions. The proposed approach is applicable to all kind of road vehicles, e.g. trucks, buses, etc. In the method, the real-road network includes road elevation.

Motion cueing algorithms can improve the perceived realism of a driving simulator, however, data on the effects on driver performance and simulator sickness remain scarce. Two novel motion cueing algorithms varying in concept and complexity were developed for a limited maneuvering workspace, hexapod/Stuart type motion platform. The RideCue algorithm uses a simple swing motion concept while OverTilt Track algorithm uses optimal pre-positioning to account for maneuver characteristics for coordinating tilt adjustments. An experiment was conducted on the US Army Tank Automotive Research, Development and Engineering Center (TARDEC) Ride Motion Simulator (RMS) platform comparing the two novel motion cueing algorithms to a pre-existing algorithm and a no-motion condition.

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.

The paper discusses the concept, design and final results from the ‘Ultra Boost for Economy’ collaborative project, which was part-funded by the Technology Strategy Board, the UK's innovation agency. The project comprised industry- and academia-wide expertise to demonstrate that it is possible to reduce engine capacity by 60% and still achieve the torque curve of a modern, large-capacity naturally-aspirated engine, while encompassing the attributes necessary to employ such a concept in premium vehicles. In addition to achieving the torque curve of the Jaguar Land Rover naturally-aspirated 5.0 litre V8 engine (which included generating 25 bar BMEP at 1000 rpm), the main project target was to show that such a downsized engine could, in itself, provide a major proportion of a route towards a 35% reduction in vehicle tailpipe CO2 on the New European Drive Cycle, together with some vehicle-based modifications and the assumption of stop-start technology being used instead of hybridization.

The Carbon Dioxide (CO₂) emission from a EURO 3 diesel van over a real-world driving cycle were investigated utilizing part of the Leeds University - Headingly Ring Road (LU-HR) driving cycle, which comprises both an urban (congested) and extra-urban (high speed) driving section. The vehicle used in this research was a 1.8-liter Ford Connect TDCi diesel van. Emissions were monitored by a Portable Emissions Measurement System (PEMS) incorporating an on-board FTIR (Fourier Transform Infrared) exhaust emission measurement system, a Horiba On Board emissions measuring System (OBS 1300) which measured the exhaust flow rate and air/fuel ratio, and a RaceLogic VBOX II differential GPS system provided geographical position, speed and acceleration data. Route topography is known to have substantial influence on vehicle emission.

The paper presents vehicle-based test work using tri-component, or ternary, blends of gasoline, ethanol and methanol for which the stoichiometric air-fuel ratio (AFR) was controlled to be 9.7:1. This is the same as that of conventional "E85" alcohol-based fuel. Such ternary blends are termed "GEM" after the first initial of the three components. The present work was a continuation of an earlier successful project which established that the blends were effectively invisible to a car using a virtual alcohol sensor. The vehicle used here employed the other major technology in flex-fuel vehicles to determine the proportion of alcohol fuel in the tank, a physical alcohol sensor. Another aspect of the present work included the desire to investigate ternary blend replacements for E85 having low ethanol concentrations. Evidence from the previous work suggested that under specific conditions, ethanol was required in some amount to act as a cosolvent for the gasoline and methanol in the blend.

Different driving test cycles, the Leeds-West Park (LWP) loop and the Leeds-High Park (LHP) or HPL-A and B (Leeds-Hyde Park Loop-A or B, hereafter referred as HPL-A or B cycle) loop were selected for this urban intersection research and results are presented in this study. Different emissions-compliant petrol passenger cars (EURO 1, 2, 3 and 4) were compared for their real-world emissions. A reasonable distance of steady state speed was needed and for the analysis made in this paper were chosen vehicle speeds at ~20, ~30 and ~40 km/h. Specific spot of periods of driving at the speeds mentioned above were identified, then the starting and ending point was found and the total emissions in g for that period divided by the distance was calculated. A typical urban driving cycle including a loop and a section of straight road was used for the comparison test as it was similar to the legislative ECE15 urban driving cycle.

The paper presents the concept of ternary blends of gasoline, ethanol and methanol in which the stoichiometric air-fuel ratio (AFR) is controlled to be 9.7:1, the same as that of conventional ‘E85’ alcohol-based fuel. This makes them iso-stoichiometric. Such blends are termed ‘GEM’ after the first initial of the three components. Calculated data is presented showing how the volumetric energy density relationship between the three components in these blends changes as the stoichiometric AFR is held constant but ethanol content is varied. From this data it is contended that such GEM blends can be ‘drop-in’ alternatives to E85, because when an engine is operated on any of these blends the pulse widths of the fuel injectors would not change significantly, and so there will be no impact on the on-board diagnostics from the use of such blends in existing E85/gasoline flex-fuel vehicles.

The Swedish Biomimetics 3000's μMist® platform technology has been used to develop a radically new injection system. This prototype system, developed and characterized with support from Lotus, as part of Swedish Biomimetics 3000®'s V₂IO innovation accelerating model, delivers improved combustion efficiency through achieving exceptionally small droplets, at fuel rail pressures far less than conventional GDI systems and as low as PFI systems. The system gives the opportunity to prepare and deliver all of the fuel load for the engine while the intake valves are open and after the exhaust valves have closed, thereby offering the potential to use advanced charge scavenging techniques in PFI engines which have hitherto been restricted to direct-injection engines, and at a lower system cost than a GDI injection system.

Omnivore is a single cylinder spark ignition based research engine conceived to maximize the operating range of auto-ignition on a variety of fossil and renewable fuels. In order to maximize auto-ignition operation, the two-stroke cycle was adopted with two independent mechanisms for control. The charge trapping valve system is incorporated as a means of varying the quantity of trapped residuals whilst a variable compression ratio mechanism is included to give independent control over the end of compression temperature. The inclusion of these two technologies allows the benefits of trapped residual gas to be maximised (to minimize NOx formation) whilst permitting variation of the onset of auto-ignition. 2000rpm and idle are the main focus of concern whilst also observing the influence of injector location. This paper describes the rational behind the engine concept and presents the results achieved at the time of writing using 98ulg and E85 fuels.

Concerns over energy security and global warming are beginning to be a serious issue for society and are also starting to drive customer purchasing decisions across many areas. Against this background there is an increasing call for motor sport to improve its environmental image, despite the fact that the global energy consumption and CO2 emissions attributable to motor sport are a very low proportion of the total. The real issue for motor sport in the face of the wider societal concerns is that, if it is truly at the cutting edge of relevant automotive engineering, it should be configured and managed in such a way as to drive technology for the betterment of mankind. The status quo is, it is contended, increasingly seen to be blatantly energy-profligate in the eyes of many people and this issue must be resolved if motor sport is to demonstrate the wider benefits of the technology developed by the huge financial investments committed to competing at the highest level.

The paper discusses the use of alcohol fuels in high performance pressure-charged engines such as are typical of the type being developed under the ‘downsizing’ banner. To illustrate this it reports modifications to a supercharged high-speed sports car engine to run on an ethanol-based fuel (ethanol containing 15% gasoline by volume, or ‘E85’). The ability for engines to be able to run on alcohol fuels may become very important in the future from both a global warming viewpoint and that of security of energy supply. Additionally, low-carbon-number alcohol fuels such as ethanol and methanol are attractive alternative fuels because, unlike gaseous fuels, they can be stored relatively easily and the amount of energy that can be contained in the vehicle fuel tank is relatively high (although still less than when using gasoline).

Homogenous Charge Compression Ignition (HCCI) is an alternative to Spark Ignited (SI) combustion, which can provide part-load efficiencies as high as compression ignition engines and energy densities as high as SI engines, without high levels of NOx or Particulate Matter (PM). The principle of operation involves reaching the thermal oxidization barrier of a homogeneous air-fuel mixture. This combustion practice is enabled by diluting then compressing the mixture with the Trapped Residual Gases (TRG) to dilute the initial charge thus keeping combustion temperatures down. Introduction of exhaust gasses in the mixture can be achieved by the use of early exhaust valve closure and late inlet valve opening. The charge is well mixed avoiding particulate emissions, and by using exhaust gasses for load regulation the need for throttled operation is removed allowing the realization of high efficiencies, low pumping losses and a resulting 15 - 20% improvement in fuel economy.

The control of Homogeneous Charge Compression Ignition (HCCI) (also known as Controlled Auto Ignition (CAI)) has been a major research topic recently, since this type of combustion has the potential to be highly efficient and to produce low NOx and particulate matter emissions. Ion current has proven itself as a closed loop control feedback for SI engines. Based on previous work by the authors, ion current was acquired through HCCI operation too, with promising results. However, for best utilization of this feedback signal, advanced interpretation techniques such as artificial neural networks can be used. In this paper the use of these advanced techniques on experimental data is explored and discussed. The experiments are performed on a single cylinder cam-less (equipped with a Fully Variable Valve Timing (FVVT) system) research engine fueled with commercially available gasoline (95 ON).

The main objective of this research was to validate the friction prediction capability of Ricardo Software products PISDYN and RINGPAK by comparing predictions with measured piston assembly friction force. The measurements were made by the University of Leeds on a single cylinder Ricardo Hydra gasoline engine using an IMEP method developed by the University. This technique involves the use of advanced instrumentation to make accurate measurements of cylinder pressure, crankshaft angular velocity and connecting rod strain. These measured values are used to calculate the forces acting on the piston assembly including the friction force. PISDYN was used by Ricardo to calculate friction force at the interface between the piston skirt and cylinder liner. The model used includes the effects of secondary dynamics, partial lubrication and piston skirt profile. RINGPAK was used by Ricardo to calculate the friction force at each piston ring.

There is a great deal of interest in new technologies to assist in reducing the CO2 output of passenger vehicles, as part of the drive to meet the limits agreed by the EU and the European Automobile Manufacturer's Association ACEA, itself a result of the Kyoto Protocol. For the internal combustion engine, the most promising of these include gasoline direct injection, downsizing and fully variable valve trains. While new types of spray-guided gasoline direct injection (GDI) combustion systems are finally set to yield the level of fuel consumption improvement which was originally promised for the so-called ‘first generation’ wall- and air-guided types of GDI, injectors for spray-guided combustion systems are not yet in production to help justify the added complication and cost of the NOx trap necessary with a stratified combustion concept.