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Battery Electric Vehicles and Extended Range Electric Vehicles, like the Chevrolet Volt, can use electrical energy from the Grid to meet the majority of a driver�s transportation needs. This has the positive societal effects of displace petroleum consumption and associated pollutants from combustion on a well to wheels basis, as well as reduced energy costs for the driver. CO2 may also be lower, but this depends upon the nature of the grid energy generation. There is a mix of sources � coal-fired, gas -fired, nuclear or renewables, like hydro, solar, wind or biomass for grid electrical energy. This mix changes by region, and also on the weather and time of day. By monitoring the grid mix and communicating it to drivers (or to their vehicles) in real-time, electrically driven vehicles may be recharged to take advantage of the lowest CO2, and potentially lower cost charging opportunities.

A comparative study on engine performance and emissions (NOx, soot) formation has been carried out for the Volvo D12C diesel engine fueled by Rapeseed Methyl Ester, RME and conventional diesel oil. The fuel and combustion models used in this paper are the modifications of those described in [1–3]. The numerical results for different load cases illustrate that for both fuels nearly 100% combustion efficiency was predicted; in the case of RME, the cumulative heat release was compared with the RME LHV, 37.2 kJ/g. To minimize soot and NOx emissions, 25–30% EGR levels depending on the engine loads and different injection timings were analyses. To illustrate the optimal engine performance conditions, a special technique based on the time-transient parametric ϕ-T maps [4] has been used.

Automotive aerodynamics measurements and simulations now routinely use a moving ground and rotating wheels (MVG&RW), which is more representative of on-road conditions than the fixed ground-fixed wheel (FG&FW) alternative. This can be understood as a combination of three elements: (a) moving ground (MVG), (b) rotating front wheels (RWF) and (c) rotating rear wheels (RWR). The interaction of these elements with the flow field has been explored to date by mainly experimental means. This paper presents a mainly computational (CFD) investigation of the effect of RWF and RWR, in combination with MVG, on the flow field around a saloon vehicle. The influence of MVG&RW is presented both in terms of a combined change from a FG&FW baseline and the incremental effects seen by the addition of each element separately. For this vehicle, noticeable decrease in both drag and rear lift is shown when adding MVG&RW, whereas front lift shows little change.

The incorporation of hydrogen fuel cells into heavy duty tactical mobility vehicles can bring about great opportunities in reducing the pollutant emissions of this kind of platforms (GVW > 30,000 kg). Furthermore the transportation of fuel to operational areas has become a key aspect for any deployment therefore optimal use of this resource is of paramount importance. Finally, it is also quite common for such platforms to serve additional purposes, besides freight delivery, such as powering external equipment (i.e. field hospitals or mobile artillery pieces). This work will describe the intelligent energy management system for a PEM Fuel Cell-Battery-Ultracapacitor Hybrid 8×8 heavy truck of the aforementioned weight class which also contemplates an internal electric/traction power generation unit. It will describe how the system optimizes the use of battery and hydrogen fuel energy while keeping system efficiency and performance at a maximum.

Fuel consumption of vehicles has received increased attention in recent years; however one neglected area that can have a large effect on this is the energy usage for the interior climate. This study aims to investigate the energy usage for the interior climate for different conditions by measurements on a complete vehicle. Twelve different NEDC tests in different temperatures and thermal states of the vehicle were completed in a climatic wind tunnel. Furthermore one temperature sweep from 43° to −18°C was also performed. The measurements focused on the heat flow of the air, from its sources, to its sink, i.e. compartment. In addition the electrical and mechanical loads of the climate system were included. The different sources of heating and cooling were, for the tested powertrain, waste heat from the engine, a fuel operated heater, heat pickup of the air, evaporator cooling and cooling from recirculation.

The high-pressure isobaric combustion has been proposed as the most suitable combustion mode for the double compre4ssion expansion engine (DCEE) concept. Previous experimental and simulation studies have demonstrated an improved efficiency compared to the conventional diesel combustion (CDC) engine. In the current study, isobaric combustion was achieved using a single injector with multiple injections. Since this concept involves complex phenomena such as spray to spray interactions, the computational models were extensively validated against the optical engine experiment data, to ensure high-fidelity simulations. The considered optical diagnostic techniques are Mie-scattering, fuel tracer planar laser-induced fluorescence (PLIF), and natural flame luminosity imaging. Overall, a good agreement between the numerical and experimental results was obtained.

Squeak and rattle (S&R) are nonstationary annoying and unwanted noises in the car cabin that result in considerable warranty costs for car manufacturers. Introduction of cars with remarkably lower background noises and the recent emphasis on electrification and autonomous driving further stress the need for producing squeak- and rattle-free cars. Automotive manufacturers use several road disturbances for physical evaluation and verification of S&R. The excitation signals collected from these road profiles are also employed in subsystem shaker rigs and virtual simulations that are gradually replacing physical complete vehicle test and verification. Considering the need for a shorter lead time and the introduction of optimisation loops, it is necessary to have efficient and inclusive excitation load cases for robust S&R evaluation.

Axial cooling fans are commonly used in electric vehicles to cool batteries with high heating load. One drawback of the cooling fans is the high aeroacoustic noise level resulting from the fan blades and the obstacles facing the airflow. To create a comfortable cabin environment in the vehicle, and to reduce exterior noise emission, a low-noise installation design of the axial fan is required. The purpose of the study is to investigate efficient computational aeroacoustics (CAA) simulation processes to assist the cooling-fan installation design. In this paper we report the current progress of the investigation, where the narrow-band components of the fan noise is focused on. Two methods are used to compute the noise source. In the first method the source is computed from the flow field obtained using the unsteady Reynolds-averaged Navier-Stokes equations (unsteady RANS, or URANS) model.

To characterize the effects of renewable fuels on particulate emissions from GDI engines, engine experiments were conducted using EN228-compliant gasoline fuel blends containing no oxygenates, 10% ethanol (EtOH), or 22% ethyl tert-butyl ether (ETBE). The experiments were conducted in a single cylinder GDI engine using a 6-hole fuel injector operated at 200 bar injection pressure. Both PN in raw exhaust and solid PN (SPN) were measured at two load points and various start of injection (SOI) timings. Raw PN and SPN results were classified into various size ranges, corresponding to current and future legislations. At early SOI timings, where particulate formation is dominated by diffusion flames on the piston due to liquid film, the oxygenated blends yielded dramatically higher PN and SPN emissions than reference gasoline because of fuel effects.

Energy management strategies greatly influence the power performance and fuel economy of series hybrid electric tracked bulldozers. In this paper, we present a procedure for the design of a power management strategy by defining a cost function, in this case, the minimization of the vehicle’s fuel consumption over a driving cycle. To explore the fuel-saving potential of a series hybrid electric tracked bulldozer, a dynamic programming (DP) algorithm is utilized to determine the optimal control actions for a series hybrid powertrain, and this can be the benchmark for the assessment of other control strategies. The results from comparing the DP strategy and the rule-based control strategy indicate that this procedure results in approximately a 7% improvement in fuel economy.

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.

In light of the drive for energy efficiency and low CO2 emissions, extensive research is performed to reduce vehicle aerodynamic drag. The wheels are relatively shielded from the main flow compared to the exterior of the passenger car; however, they are typically responsible for around 25% of the overall vehicle drag. This contribution is large as the wheels and tyres protrude into the flow and change the flow structure around the vehicle underbody. Given that the tyre is the first part of the wheel to get in contact with the oncoming flow, its shape and features have a significant impact on the flow pattern that develops. This study aims at identifying the general effects of two main tyre features, the longitudinal rain grooves and lateral pattern grooves, using both Computational Fluid Dynamics (CFD) and wind tunnel tests. This is performed by cutting generic representations of these details into identical slick tyres.

In jet atomization, breakup length is the length of the continuous jet segment, before its breakup to discontinuous droplets. Hydrodynamic instability theory, implemented in CFD codes, is often complemented by semi-empirical correlations for breakup length, which may limit parametric investigations. A basic mechanistic approach to the breakup length prediction, based on a simple momentum balance between the injected jet and the aerodynamic drag force due to the surrounding gas, which complements the classic hydrodynamic instability breakup mechanism, is suggested. This model offers a simple complementing mechanistic model. It is shown that obtained results compare well with published experiments, and with the established empirical correlation of Wu and Faeth (1995). A simplified version of the model, taking into account an inviscid hydrodynamic model is shown to maintain plausibility of breakup length predictions in fuel-injection relevant conditions.

The current trend toward more fuel efficient vehicles with lower emission levels has prompted development of new combustion techniques for use in gasoline engines. Stratified combustion has been shown to be a promising approach for increasing the fuel efficiency. However, this technique is hampered by drawbacks such as increased particulate and standard emissions. This study attempts to address the issues of increased emission levels by investigating the influence of high frequency ionizing ignition systems, 350 bar fuel injection pressure and various tumble levels on particulate emissions and combustion characteristics in an optical SGDI engine operated in stratified mode on isooctane. Tests were performed at one engine load of 2.63 bar BMEP and speed of 1200 rpm. Combustion was recorded with two high speed color cameras from bottom and side views using optical filters for OH and soot luminescence.

The automotive trends of vehicles with lower aerodynamic drag and more powerful drivetrains have caused increasing concern regarding stability issues at high speeds, since more streamlined bodies show greater sensitivity to crosswinds. This is especially pronounced for high vehicles, such as sports utility vehicles. Besides, the competitiveness in the automotive industry requires faster development times and, thus, a need to evaluate the high speed stability performance in an early design phase, preferable using simulation tools. The usefulness of these simulation tools partly relies on realistic boundary conditions for the wind and quantitative measures for assessing stability without the subjective evaluation of experienced drivers. This study employs an on-road experimental measurements setup to define relevant wind conditions and to find an objective methodology to evaluate high speed stability.

The potential of 48V Mild Hybrid is promising in meeting the present and future CO2 legislations. There are various system layouts for 48V hybrid system including P0, P1, P2. In this paper, P2 architecture is used to investigate the effects of water injection benefits in a mild hybrid system. Electrification of the conventional powertrain uses the benefits of an electric drive in the low load-low speed region where the conventional SI engine is least efficient and as the load demand increases the IC Engine is used in its more efficient operating region. Engine downsizing and forced induction trend is popular in the hybrid system architecture. However, the engine efficiency is limited by combustion knocking at higher loads thus ignition retard is used to avoid knocking and fuel enrichment becomes must to operate the engine at MBT (Maximum Brake Torque) timing; in turn neutralizing the benefits of fuel savings by electrification.

Future pressures to reduce the fuel consumption of passenger cars may require the exploitation of alternative combustion strategies for gasoline engines to replace, or use in combination with the conventional stoichiometric spark ignition (SSI) strategy. Possible options include homogeneous lean charge spark ignition (HLCSI), stratified charge spark ignition (SCSI) and homogeneous charge compression ignition (HCCI), all of which are intended to reduce pumping and thermal losses. In the work presented here four different combustion strategies were evaluated using the same engine: SSI, HLCSI, SCSI and HCCI. HLCSI was achieved by early injection and operating the engine lean, close to its stability limits. SCSI was achieved using the spray-guided technique with a centrally placed multi-hole injector and spark-plug. HCCI was achieved using a negative valve overlap to trap hot residuals and thus generate auto-ignition temperatures at the end of the compression stroke.

Advanced engine control and diagnosis strategies for internal combustion engines need accurate feedback information from the combustion engine. The feedback information can be utilized to control combustion features which allow the improvement of engine's efficiency through real-time control and diagnosis of the combustion process. This article describes a new method for combustion phase and IMEP estimation using one in-cylinder pressure and engine speed. In order to take torsional deflections of the crankshaft into account a gray-box model of the crankshaft is identified by subspace identification. The modeling accuracy is compared to a stiff physical crankshaft model. For combustion feature estimation, the identified MISO (multiple input single output) system is inverted. Experiments for a four-cylinder spark-ignition engine show the superior performance of the new method for combustion feature estimation compared to a stiff model approach.

The aviation sector has played a significant role in shaping the world into what it is today. The rapid growth of global economies and the corresponding sharp rise in the number of people now wanting to travel on business and for pleasure, has largely been responsible for the development of this industry. With a predicted rise in Revenue Passenger Kilometers (RPK) by over 150% in the next 20 years, the industry will correspondingly be a significant contributor to environmental emissions. Under such circumstances optimizing aircraft trajectories for lowered emissions will play a critical role amongst various other measures, in mitigating the probable environmental effects of increased air traffic. Aircraft trajectory optimization using evolutionary algorithms is a novel field and preliminary studies have indicated that a reduction in emissions is possible when set as objectives.

Testing real-time vehicular systems challenges the tester to design test cases for concurrent and sequential input events, emulating unexpected user and usage profiles. The vehicle response should be robust to unexpected user actions. Sequence Covering Arrays (SCA) offer an approach which can emulate such unexpected user actions by generating an optimized set of test vectors which cover all possible t-way sequences of events. The objective of this research was to find an efficient nonfunctional sequence testing (NFST) strategy for testing the robustness of real-time automotive embedded systems measured by their ability to recover (prove-out test) after applying sequences of user and usage patterns generated by combinatorial test algorithms, considered as “noisy” inputs. The method was validated with a case study of an automotive embedded system tested at Hardware-In-the-Loop (HIL) level. The random sequences were able to alter the system functionality observed at the prove-out test.