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An engine model for use in computer simulation of transient behavior in drivetrain and vehicle systems is presented. Two elements, important for deviation (e.g. turbo-lag) from steady state characteristics, are the inertia of the supercharging unit (turbo shaft) and the fuel injection control system. No extensive combustion calculations are carried out within the model. Instead it uses condensed results from existing combustion models and measurements. The model is semi-empirical. Some of the engine specific properties needed for simulation are (e.g. for a turbocharged diesel): engine data in steady state operation, mappings of compressor and turbine performance, inertia of the engine components condensed to the crankshaft, turbo shaft inertia, displacement, compression ratio and the essentials of the fuel injection control strategy. Input parameters to the computer program based on the model are accelerator pedal position and external torque acting on the flywheel.

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.

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.

Today CFD is an important tool for engineers in the automotive industry who model and simulate fluid flow. For the complex field of Underhood Thermal Management, CFD has become a very important tool to engineer the cooling airflow process in the engine bay of vehicles. To model the cooling airflow process accurately in CFD, it is of utmost importance to model all components in the cooling airflow path accurately. These components are the heat exchangers, fan and engine bay blockage effect. This paper presents CFD simulations together with correlating measurements of a cooling airflow system placed in a test rig. The system contains a heavy duty truck louvered fin radiator core, fan shroud, fan ring and fan. Behind the cooling module and fan, a 1D engine silhouette is placed to mimic the blockage done by a truck engine. Furthermore, a simple hood is mounted over the module to mimic the guiding of air done by the hood shape in an engine bay.

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.

In order to meet emissions and power requirements, modern engine design has evolved in complexity and control. The cost and time restraints of calibration and testing of various control strategies have made virtual testing environments increasingly popular. Using Hardware-in-the-Loop (HiL), Volvo Penta has built a virtual test rig named VIRTEC for efficient engine testing, using a model simulating a fully instrumented engine. This paper presents an innovative Artificial Neural Network (ANN) based model for engine simulations in HiL environment. The engine model, herein called Artificial Neural Network Engine (ANN-E), was built for D8-600 hp Volvo Penta engine, and directly implemented in the VIRTEC system. ANN-E uses a combination of feedforward and recursive ANNs, processing 7 actuator signals from the engine management system (EMS) to provide 30 output signals.

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.

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.

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.