Automotive and Engine Technology最新文献

In the automotive industry, the demand for fuel economy and emission reduction has resulted in engine downsizing, with turbochargers playing a key role in compensating for the performance loss. To be effective, a turbocharger’s compressor must be accurately designed to match the engine’s requirements. This study presents a novel non-parametric optimisation of the turbocharger compressor diffuser based on the compressor efficiency. The numerical models are based on the validation and mesh dependency study against experimental data from three points on each speed line of 150,000 (rpm) and 80,000 (rpm). The geometry and case data are related to the TD025-05T4 compressor from the 1.2-L Renault Megane passenger car. The turbocharger compressor diffuser geometry was optimised using the adjoint solver method within ANSYS FLUENT 2019 R1. The adjoint solver provides a gradient-based optimisation that can automatically create a series of iterations of a design, so that the mesh gradually deforms into an optimal shape to achieve a single target, the compressor efficiency in this study. The study considers a total of six operating cases on the compressor map to optimise the full and partial load compressor operations, leading to a real-world drive cycle. These cases are the three cases (closer to surge, stable midpoint, and closer to the choke point) on each of the speed lines. A typical result for mid-stable operation on a 150,000 (rpm) speed line shows a gradual increase in efficiency up to a maximum of 2.6% improvement. The optimal diffuser geometry impacts the overall car engine efficiency for real-world drive cycles, increasing power output and improving thermal efficiency.

Solving the optimal control problem within optimization-based hybrid control strategies usually leads to high frequency changes between driving modes. Depending on the powertrain configuration, these mode shifts can simply mean activation and deactivation of the internal combustion engine (ICE), switching between different hybrid modes, e.g. series and parallel driving or even gear selection. Especially under dynamic as well as real driving conditions any kind of post-processing is very likely required for limitation of this frequency due to drivability reasons. Most commonly used are time domain filters, hystereses or penalty terms. Nevertheless, these post-processing methods affect the fuel efficiency of the control strategy itself and do not achieve optimal behaviour under all circumstances. Therefore, in this paper, a new possibility for debounce of mode shifts has been investigated using dynamic longitudinal vehicle simulation. By including a physical transition cost vs. benefit estimation for each possible shift in driving mode an energy-based debounce method can be set up. The proposed method enables further improvements towards optimal control. The debounce approach itself requires no predictive knowledge. Recently, both drivability and efficiency can be obtained simultaneously and even for customer use.

Particulate emissions from diesel engines are a matter of public concern and continued industrial development. For an internal combustion engine, particles may originate either from the after treatment box or from the crankcase ventilation system. This paper quantifies and discusses particle sources within the crankcase ventilation system of a medium-duty 4-cylinder and a heavy-duty 6-cylinder engine and their dependence on the engine oil parameters viscosity (expressed as Noack number) and HTHS volatility. Crankcase aerosol spectra were measured by an optical particle counter in the size range of 0.3–5 µm. For a few cases data of filter samples downstream the separator unit are discussed for the total blow-by aerosol. Engines were found to behave very similarly with regard to changes in either oil parameter, with volatility generally being the far stronger factor of influence. Total particle mass concentration increased by a factor of up to 5 for a rise in Noack volatility of about 13–25%. The mass concentration downstream of the separator also increases with oil volatility. A variation of HTHS viscosity from 3.5 to 2.6 mPas generated a marginal change in aerosol output by a factor of about 1.2. However, and unexpectedly, the most viscose oil generated the relatively highest particle mass concentrations for both engines.

Improvement in fuel conversion efficiency in an internal combustion engine increases power and reduces fuel consumption. The efficiency of an engine increases either by the increase in compression ratio or expansion ratio. This paper presents a new concept for a higher expansion process in comparison to compression process stroke on the base of the Miller cycle, rather than early or late closing inlet valves. The proposed mechanism works with eccentric crankshaft movement around the eccentric-derived path to achieve a shorter compression process and longer over-expansion process stroke. The theoretical simulation results of SI engine were obtained using thermodynamic quasi-dimensional combustion (burned and unburned zone) power cycle integrated with the intake and exhaust system. The best result of over-expansion (OE) system over non-OE has been observed at 1500–2000 rpm, and the corresponding results are: increment in indicated thermal efficiency from 36 to 38.5%, brake torque from 32 to 46 N-m, brake power from 6.52 to 9.46 kW and indicated power from 7.36 to 10.89 kW, and maximum BSFC decrement 5.42% at 1500 rpm. OE system has a higher value of CO concentration throughout the speed range; however, the NO concentration in ppm decreased by 1.62% at 1500 rpm at the same EVO crank angle. Thus, this mechanism offers significant benefits in thermal efficiency, fuel consumption, and NO emission. And, it is highly beneficial at 1500–2000 rpm engine run, which shows most suitable for engine-integrated electric power generation.

Using Vehicle Thermal Management (VTM) simulations to predict the thermal load experienced by components is a popular method within the automotive industry. The VTM simulation approach is fast becoming equivalent to conducting thermal load tests with prototypes for vehicles powered by internal combustion engines. This is especially true in the early development phase of the vehicle. The accuracy of the VTM simulations plays a pivotal role at them being accepted as an eventual replacement for physical testing. The correct prediction of thermal loads in VTM simulations depends on a multitude of different parameters, but the modelling of the exhaust system plays a central role in it. This is because the exhaust gas, and with it the exhaust system, is the primary source of heat in a vehicle powered by an internal combustion engine. The developed approach not only needs to be accurate but also modular enough to allow for different exhaust configurations to be tested. It also needs to be capable of integration into any VTM simulation workflow while maintaining an industrially acceptable turnaround time. This paper explores a new methodology to achieve these requirements. A 1D/3D hybrid approach to exhaust system modelling is presented. In this, the components that have an enthalpy change of the exhaust gas, such as the turbocharger, have been modelled as 1D and simple components such as pipes have been modelled in 3D. This has the advantage of combining the speed of 1D simulations with the spatial accuracy of 3D simulations. The method uses a unique three-code co-simulation technique for full vehicle VTM simulations. The coupling is between a 3D CFD software, a 1D simulation tool, and a Finite Element based thermal solver. The methodology was validated against experimental data for multiple loadcases. The results show good agreement with experiment within acceptable tolerances.

In this paper, a model predictive control (MPC) approach for the lateral and longitudinal control of a highly automated electric vehicle with all-wheel drive and dual-axis steering is presented. For the prediction of state trajectories a two-track vehicle model is used. The MPC problem for trajectory tracking is formulated by controlling the front and rear steering angle as well as the individual drive torques with respect to actuator and design constraints. Beside the steering angles, the MPC controller computes the individual drive torques to not only match the reference velocity but also to support the lateral dynamics of the vehicle using torque vectoring. The MPC problem is solved using ACADOS, a software package for efficiently solving optimal control problems. The effectiveness of the proposed MPC scheme is demonstrated via simulation.

Finding the optimum design of electrical machines for a certain purpose is a time-consuming task. First results can be achieved, however, with scaling known machine designs in length and turns per coil by means of analytical equations, while scaling in diameter requires finite element analysis (FEA), since electromagnetic properties change significantly. In this paper, the influence of diameter, length and turns per coil on the torque, power and efficiency of a permanent magnet synchronous machine (PMSM) are investigated in a sensitivity analysis. Furthermore, their impact on energy consumption in different drive cycles and different vehicle types is outlined. A highway car and a city car are compared in a highway cycle, a city cycle and the Worldwide Harmonized Light Vehicle test Cycle. The results describe significant differences in energy consumption for different machine designs in one application but also between different applications. This highlights the necessity to decide whether or not the powertrain should be optimized for a single purpose or for universal use.

Selective catalytic reduction (SCR) systems are the state-of-the-art technology to reduce nitrogen oxide emissions (NO_x) of modern diesel engines. The system behaviour is well understood in the common temperature working area. However, the system properties below light-off temperature are less well known and offer a wide scope for further investigations. Vehicle measurements show that under specific conditions during cold start, NO_x can be partially stored and converted on on-filter and flow-through SCR catalysts. The purpose of this work was in a first step to analyse the main influence parameters on the NO_x storage behaviour. Therefore, synthetic gas test bench measurements have been carried out, varying the gas concentrations, temperature, and gas hourly space velocity (GHSV). These investigations showed that the NO_x storage effect strongly depends on the NH₃ level stored in the catalyst, GHSV, the adsorbed water (H₂O) on the catalyst, and the temperature of the catalyst. Further influence parameters such as the gas composition with focus on carbon monoxide (CO), short-chain hydrocarbons and long-chain hydrocarbons have been analysed on a synthetic gas test bench. Depending on operating conditions, a significant amount of NO_x can be stored on a dry catalyst during the cold start phase. The water vapor from the combustion condenses on the cold exhaust pipe during the first seconds, or up to a few minutes after a cold start. As the water vapor reaches the surface of the catalyst, it condenses and adsorbs onto it, leading to a sudden temperature rise. This exothermal reaction causes the stored NO_x to be desorbed, and furthermore it is partially reduced by the NH₃ stored in the catalyst.

The focus on the expansion of the electrification of vehicles becomes stronger. Thus, the development process of powertrains of those cars needs to be more dynamic to react to the new challenges. One way to accelerate the development is to automate predevelopment and evaluation at an early stage. An automated method to synthesize transmission topologies and pre-design gears for the generated topologies for electric vehicles is presented within this paper. The method contains two internal evaluations—one after the topology synthesis and the second after the initial design of the gears. The results of the method are gear ratios and gear data for the single transmission steps of each topology. The inputs and boundary conditions can be easily changed and fitted to specific requirements for all use-cases. Here, the process is explained, and the methods' results are validated using state-of-the-art passenger vehicle transmission. As for electric trucks, no state-of-the-art electric powertrains exist; the method is subsequently applied to find topologies for a heavy-duty truck. Extracts of the results are presented. The application for trucks is carried out within the publicly funded research project “Concept ELV²”. In general, the method is capable of synthesizing transmissions for any given vehicle and motor combination.

Unlike electromechanical steering systems, steer-by-wire systems do not have a mechanical coupling between the wheels and the steering wheel. Therefore, a synthetic steering feel has to be generated to supply the driver with the necessary haptic information. In this paper, the authors analyze two approaches of creating a realistic steering feel. One is a modular approach that uses several measured and estimated input signals to model a steering wheel torque via mathematical functions. The other approach is based on an artificial neural network. It depends on steering and vehicle measurements. Both concepts are optimized and trained, respectively, to best fit a reference steering feel obtained from vehicle measurements. To carry out the analysis, the two approaches are evaluated using a simulation model consisting of a vehicle, a rack actuator, and a steering wheel actuator. The research shows that both concepts are able to adequately model a desired steering feel.