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When designing an electric vehicle (EV) traction system, overcoming the issues arising from the variations in the battery voltage due to the state of charge (SoC) is critical, which otherwise can lead to a deterioration of the powertrain energy efficiency and overall drive performance. However, systems are typically documented under fixed voltage and temperature conditions, potentially lacking comprehensive specifications that account for these variations across the entire range of the vehicle operating regions. To tackle this challenge, this paper seeks to adjust an optimal DC-link voltage across the complete range of drive operating conditions by integrating a DC-DC converter into the powertrain, thereby enhancing powertrain efficiency. This involves conducting a comprehensive analysis of power losses in the power electronics of a connected converter-inverter system considering the temperature variations, along with machine losses, accounting for variable DC-link voltages.

The transition towards battery electric vehicles (BEVs) has increased the focus of vehicle manufacturers on energy efficiency. Ensuring adequate airflow through the heat exchanger is necessary to climatize the vehicle, at the cost of an increase in the aerodynamic drag. With lower cooling airflow requirements in BEVs during driving, the front air intakes could be made smaller and thus be placed with greater freedom. This paper explores the effects on exterior aerodynamics caused by securing a constant cooling airflow through intakes at various positions across the front of the vehicle. High-fidelity simulations were performed on a variation of the open-source AeroSUV model that is more representative of a BEV configuration. To focus on the exterior aerodynamic changes, and under the assumption that the cooling requirements would remain the same for a given driving condition, a constant mass flow boundary condition was defined at the cooling airflow inlets and outlets.

The transport sector is experiencing a shift to zero-carbon powertrains driven by aggressive international policies aiming to fight climate change. Battery electric vehicles (BEVs) will play the main role in passenger car applications, while diversified solutions are under investigation for the heavy-duty sector. Within this framework, Light Commercial Vehicles (LCVs) impact is not negligible and accountable for about 2.5% of greenhouse gas (GHG) emissions in Europe. In this regard, few LCV comparative assessments on green powertrains are available in the scientific literature and justified by the fact that several factors and limitations should be considered and addressed to define optimal powertrain solutions for specific use cases. The proposed research study deals with a comparative numerical assessment of different zero-carbon powertrain solutions for LCV. BEVs are compared to hydrogen-based fuel cells (FC) and internal combustion engines (ICE) powered vehicles.

The automotive industry continues to increase the utilization of computer-aided engineering. This put demands on finding reliable objective measures that correlate to subjective driver assessments on driving stability performance. However, the drivers’ subjective perception of driving stability can be difficult to quantify objectively, especially on test tracks where the wind conditions cannot be controlled. The advancement in driving simulator technology may enable evaluation of driving stability with high repeatability. The purpose of this study is to correlate the subjective assessment of driving stability to reliable objective measures and to evaluate the usefulness of a driving simulator for the subjective assessment. Two different driver clinic studies were performed in a state-of-the-art driving simulator. The first study included 38 drivers (professional, experienced and common drivers) and focused on crosswind gust sensitivity.

In vehicle development, a subjective evaluation of the vehicle’s behavior at high speeds is usually conducted by experienced drivers with the objective of assessing driving stability. To avoid late design changes, it is desirable to predict and resolve perceived instabilities early in the development phase. In this study, a mathematical model is developed from measurements during on-road tests to predict the driver’s ability to identify vehicle instabilities under excitations such as aerodynamic excitations. A vehicle is fitted with add-ons to create aerodynamic excitations and is driven by multiple drivers on a high-speed track. Drivers’ evaluation, responses, cabin motion, and crosswind conditions are recorded. The influence of yaw and roll rates, lateral acceleration, and steering angle at various frequency ranges when predicting the drivers’ evaluation of induced excitation is demonstrated. The drivers’ evaluation of vehicle behavior is influenced by driver-vehicle interactions.

The shift toward electrification and limitations in battery electric vehicle technology have led to high demand for hybrid vehicles (HEVs) that utilize a battery and an internal combustion engine (ICE) for propulsion. Although HEVs enable lower fuel consumption and emissions compared to conventional vehicles, they still require combustion of fuels for ICE operation. Thus, emissions from hybrid vehicles are still a major concern. Engine starts are a major source of emissions during any driving event, especially before the three-way catalyst (TWC) reaches its light-off temperature. Since the engine is subjected to multiple starts during most driving events, it is important to mitigate and better understand the impact of these emissions. In this study, experiments were conducted to analyze engine starts in a hybrid powertrain on different experimental setup.

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.

The three-way-catalyst (TWC) is an essential part of the exhaust aftertreatment system in spark-ignited powertrains, converting nearly all toxic emissions to harmless gasses. The TWC’s conversion efficiency is significantly temperature-dependent, and cold-starts can be the dominating source of emissions for vehicles with frequent start/stops (e.g. hybrid vehicles). In this paper we develop a thermal TWC model and calibrate it with experimental data. Due to the few number of state variables the model is well suited for fast offline simulation as well as subsequent on-line control, for instance using non-linear state-feedback or explicit MPC. Using the model could allow an on-line controller to more optimally adjust the engine ignition timing, the power in an electric catalyst pre-heater, and/or the power split ratio in a hybrid vehicle when the catalyst is not completely hot.

Bus drivers are a group at risk of often suffering from musculoskeletal problems, such as low-back pain, while bus passengers on the last-row seats experience accelerations of high values. In this paper, the contribution of K-seat in decreasing the above concern is investigated with a detailed simulation study. The K-seat model, a seat with a suspension that functions according to the KDamper concept, which combines a negative stiffness element with a passive one, is benchmarked against the conventional passive seat (PS) in terms of comfort when applied to different bus users’ seats. More specifically, it is tested in the driver’s and two different passengers’ seats, one from the rear overhang and one from the middle part. For the benchmark shake, both are optimized by applying excitations that correspond to real intercity bus floor responses when it drives over a real road profile.

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.

Modelling is widely used for the development of hybrid electric vehicle (HEV) powertrain technologies, since it can provide accurate prediction of fuel consumption and CO₂ emissions, for a fraction of the resources required in experiments. For comparison of different technologies or powertrain parameters, the results should be accurate relative to each other, since powertrains are simulated under identical model details and simulation parameters. However, when CO₂ emissions of a vehicle model are simulated under a driving cycle, significant deviances may occur between actual tests and simulation results, compromising the integrity of simulations. Therefore, this paper investigates the effects of certain modelling and simulation parameters on CO₂ emission results, for a parallel HEV under three driving cycles (NEDC, WLTC and RTS95 to simulate real driving emissions (RDE)).

In this paper, the turbulent flow induced by a production side-view mirror assembled on a full-scale production truck is simulated using a compressible k-ω SST detached eddy simulation (DES) approach -- the improved delayed DES (IDDES). The truck configuration consists of a compartment and a trailer. Due to the large size and geometric complexity of the configuration, some simplifications are applied to the simulation. A purpose of this work is to investigate whether the simplifications are suitable to obtain the reasonable properties of the flow near the side-view mirror. Another objective is to study the aerodynamic performances of the mirror. The configuration is simplified regarding two treatments. The first treatment is to retain the key exterior components of the truck body while removing the small gaps and structures. Furthermore, the trailer is shaped in an apex-truncated square pyramid.

Many technological developments in automobile powertrains have been implemented in order to increase efficiency and comply with emission regulations. Although most of these technologies show promising results in official fuel economy tests, their benefits in real driving conditions and real driving emissions can vary significantly, since driving profiles of many drivers are different than the official driving cycles. Therefore, it is important to assess these technologies under different driving conditions and this paper aims to offer an overall perspective, with a numerical study in simulations. The simulations are carried out on a compact passenger car model with eight powertrain configurations including: a naturally aspirated spark ignition engine, a start-stop system, a downsized engine with a turbocharger, a Miller cycle engine, cylinder deactivation, turbocharged downsized Miller engine, a parallel hybrid electric vehicle powertrain and an electric vehicle powertrain.

Existing battery parameter model structures are evaluated by estimating model parameters on real driving data applying standard system identification methods. Models are then evaluated on the test data in terms of goodness of fit and RMSE in voltage predictions. This is different from previous battery model evaluations where a common approach is to train parameters using standardized tests, e.g. hybrid pulse-power capability (HPPC), with predetermined charge and discharge sequences. Equivalent linear circuit models of different complexity were tested and evaluated in order to identify parameter dependencies at different state of charge levels and temperatures. Models are then used to create voltage output given a current, state of charge and temperature. The average accuracy of modelling the DC bus voltage provides a model goodness of fit average higher than 90% for a single RC circuit model.

The ability to adapt to rapidly evolving market demands continues to be the one of the key challenges in the automation of assembly processes in the aerospace industry. To meet this challenge, industry and academia have made efforts to automate flexible fixturing. LOCOMACHS (Low Cost Manufacturing and Assembly of Composite and Hybrid Structures) - a European Union funded project with 31 partners - aims to address various aspects of aero-structure assembly with a special attention directed to the development of a new build philosophy along with relevant enabling technologies. This paper aims to present the results on the developed wing box build philosophy and the integration of automated flexible tooling solutions into the assembly process. The developed solution constitutes the use of synchronized hexapods for the assembly of front spar to upper cover whereas another hexapod was developed to install a rib by using of a force feedback sensor.

The current work investigates a method in 1D modeling of cooling systems including discretized cooling package with non-uniform boundary conditions. In a stacked cooling package the heat transfer through each heat exchanger depends on the mass flows and temperature fields. These are a result of complex three-dimensional phenomena, which take place in the under-hood and are highly non-uniform. A typical approach in 1D simulations is to assume these to be uniform, which reduces the authenticity of the simulation and calls for additional calibrations, normally done with input from test measurements. The presented work employs 3D CFD simulations of complete vehicle in STAR-CCM+ to perform a comprehensive study of mass-flow and thermal distribution over the inlet of the cooling package of a Volvo FM commercial vehicle in several steady-state operating points.

In the next 20 years the share of small electric vehicles (SEVs) will increase especially in urban areas. SEVs show distinctive design differences compared to traditional vehicles. Thus the consequences of impacts of SEVs with vulnerable road users (VRUs) and other vehicles will be different from traditional collisions. No assessment concerning vehicle safety is defined for vehicles within European L7e category currently. Focus of the elaborated methodology is to define appropriate test scenarios for this vehicle category to be used within a virtual tool chain. A virtual tool chain has to be defined for the realization of a guideline of virtual certification. The derivation and development of new test conditions for SEVs are described and are the main focus of this work. As key methodology a prospective methodical analysis under consideration of future aspects like pre-crash safety systems is applied.

The work investigates the integration between tools for analysis and simulation of cooling systems at Volvo Group Trucks Technology. At the same time it is a consequent step in evaluating GT-SUITE for the purposes of analysis and simulation of such systems. The focus is on 1D simulation tools, which are generally preferred in the context of transient simulations of engine and power train installation systems. The Cooling Analysis and Simulations group at Volvo Group Trucks Technology use a variety of 1D simulation tools for analysis of cooling performance. Volvo Power Train, on the other hand, use among others GT-SUITE for engine simulations. It is expected to improve the quality of the simulation, (i.e the accuracy of the results) and improve system integration by using one tool for both areas of simulation. This work delivers two transient models of FH 13L cooling system integrated with a predictive model of the engine and a detailed model of the main coolant circuit.

Semi-active suspension systems for ground vehicles have been the focus of research for several years as they offer improvements in vehicle comfort and handling. This kind of suspension has attracted more interest compared to active suspension systems especially due to lower cost and energy consumption. In this paper the capabilities of a semi-active front axle suspension are investigated for a commercial vehicle. A half-truck model of a 4x2 tractor and semitrailer combination is developed in Matlab/Simulink for this purpose. Also, a 2 DOF roll plane model is considered to capture the roll motion of the vehicle body mass. Employing the above-mentioned models, results from on-off and continuous variable semi-active damping systems are compared to the ones from the passive suspension system according to ride comfort and handling safety characteristics.

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.