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Electric vehicles offer cleaner transportation with lower emissions, thus their increased popularity. Although, electric powertrains contribute to quieter vehicles, the shift from internal combustion engines to electric powertrains presents new Noise, Vibration, and Harshness challenges. Unlike traditional engines, electric powertrains produce distinctive tonal noise, notably from motor whistles and gear whine. These tonal components have frequency content, sometimes above 10 kHz. Furthermore, the housing of the powertrain is the interface between the excitation from the driveline via the bearings and the radiated noise (NVH). Acoustic features of the radiated noise can be predicted by utilising the transmitted forces from the bearings. Due to tonal components at higher frequencies and dense modal content, full flexible multibody dynamics simulations are computationally expensive.

The parameterization of the electrochemical pseudo-two-dimensional (P2D) model plays an important role as it determines the acceptance and application range of subsequent simulation studies. Electrochemical impedance spectroscopy (EIS) is commonly applied to characterize batteries and to obtain the exchange current density and the solid diffusion coefficient of a given electrode material. EIS measurements performed with frequencies ranging from 1 MHz down to 10 mHz typically do not cover clearly isolated solid state diffusion processes of lithium ions in positive or negative electrode materials. To extend the frequency range down to 10 μHz, the distribution function of relaxation times (DRT) is a promising analysis method. It can be applied to time-domain measurements where the battery is excited by a current pulse and relaxed for a certain period.

Modeling of lithium iron phosphate electrodes calls for appropriate extensions of established model approaches. An electrochemical pseudo two-dimensional and a single-particle model are enhanced to address the phase separating behavior of this material with a variable solid state diffusion model. A particle size distribution model tackles the heterogeneity of the electrode microstructure. Both models are embedded in a framework to describe multi-layer electrode designs featuring segregated material properties. The models are parameterized following literature replicating a good match with measured discharge curves at low, medium and high currents. A simplified version of the rigorous model shows the effort of reparameterization, the computational advantage of model order reduction techniques, the model accuracy and application scope.

The internal combustion engine contains several actuators to control engine performance and emissions. These are controlled within the engine ECU and follow a specific operating strategy to achieve objectives such as NOx reduction and fuel economy. However, these two goals are conflicting and a compromise is required. The operating state depends on system constraints such as engine speed, load, temperature levels, and aftertreatment system efficiency. This results in constantly changing target values to stay within the defined limits, especially the legal emission limits. The conventional approach is to use multiple operating modes. Each mode represents a specific compromise and is activated accordingly. Multiple modes are required to meet emissions regulations under all required conditions, which increases the calibration effort. This new control approach uses an artificial neural network to replace the conventional multiple mode approach.

This work elaborates the transferability of electrode diffusion coefficients gained from fitting procedures in frequency domain to an electrochemical battery model run in time domain. An electrochemical battery model of an NMC622 half-cell electrode is simulated with sinusoidal current excitations at different frequencies. The current and voltage signals are analyzed in frequency domain via Nyquist and Bode plots. The frequency domain analysis of time domain simulations is applied to assess the numerical convergence of the simulation and the sensitivity on particle diameter, electrode and electrolyte diffusion coefficients. The simulated frequency spectra are used to fit the electrode diffusion coefficient by means of different electrical equivalent circuit models and the electrochemical battery model itself. The fitted diffusion coefficients from the different electrical equivalent circuit models deviate by one order of magnitude from the a priori known reference data.

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.

Fast charging of batteries at cold conditions faces the challenge of promoting undesired cell degradation phenomena such as lithium plating. The occurrence of lithium plating is strongly related to local surface potentials and temperatures involving the scales of the electrode surface, the unit cell and the entire module or pack. A multi-scale, multi-domain model is presented, enhancing a Newman based unit cell model with consistent models for heat generation and lithium plating and integrating this 1D+1D approach into a thermal 3D model on module level. The basic equations are presented and three different plating models from literature are discussed. The thermal model is assessed in open-loop simulations and the different plating approaches are compared in charge/discharge simulations at different operating conditions. The full multi-scale, multi-domain model is applied as a virtual sensor for model-based control of fast charging at cold conditions.

The further increase in the efficiency of heavy-duty engines is essential in order to reduce CO2 emissions in the transport sector. This is also valid for the future use of alternative fuels, which can be CO2-neutral, but can cause higher total costs of ownership due to higher prices and limited availability. In addition to thermodynamic optimization, the reduction of mechanical losses is of great importance. In particular, there is a high potential in the piston bore interface, since continuously increasing cylinder pressures have a strong influence on the frictional and lateral piston forces. To meet these future challenges of increasing heavy-duty engine efficiency, AVL has developed a floating liner engine for heavy-duty applications based on its tried and tested passenger car floating liner concept.

Current developments in automotive industry such as hybrid powertrains and the continuously increasing demands on emission control systems, are pushing complexity still further. Validation of such systems lead to a huge amount of test cases and hence extreme testing efforts on the road. At the same time the pressure to reduce costs and minimize development time is creating challenging boundaries on development teams. Therefore, it is of utmost importance to utilize testing and validation prototypes in the most efficient way. It is necessary to apply high levels of instrumentation and collect as much data as possible. And a streamlined data pipeline allows the fleet managers to get new insights from the raw data and control the validation vehicles as well as the development team in the most efficient way. In this paper we will demonstrate a data-driven approach for validation testing.

Today’s automotive industry is changing rapidly towards environmentally friendly vehicle propulsion systems. All over the globe, legislative CO2 consumption targets are under discussion and partly already in force. Hybrid powertrain configurations are capable to lower fuel consumption and limit pollutant emissions compared to pure IC-Engine driven powertrains. Depending on boundary conditions a numerous of different hybrid topologies- and its control strategies are thinkable. Typical approach is to find the optimum hybrid layout and strategy, by performing certain technical design tasks in office simulation directly followed by vehicle prototype tests on the chassis dyno and road. This leads to a high number of prototype vehicles, overload on chassis dynos, time consuming road test and finally to tremendous costs. Our developed approach is using the engine testbed with simulation capabilities as bridging element between office and vehicle development environment.

Approaching engineering limits for the thermal design of battery modules requires virtual prototyping and appropriate models with respect to physical depth and computational effort. A multi-scale and multi-domain model describes the electrochemical behavior of a single battery unit cell in 1D+1D at the level of intra-cell phenomena, and it applies a 3D thermal model at module level. Both models are connected within a common vehicle simulation platform. The models are discussed with special emphasis on battery degradation such as solid electrolyte interphase layer formation, decomposition and lithium plating. The performance of the electrochemical model is assessed by discharge cycles and repeated charge/discharge simulations. The thermal module model is compared to CFD reference data and studied with respect to its grid sensitivity.

Grown interest in complex modern Hybrid Electric Vehicle (HEV) concepts has raised new challenges in the field of NVH. The switch between the Internal Combustion Engine (ICE) and the Electric Motor (EM) at low speeds produces undesirable vibrations and a sudden raise of noise levels that effects the sound quality and passenger comfort achieved by the close-to-silent electric powertrain operation. Starting the ICE in the most suitable driving situation to create a seamless transition between driving modes can be the key to minimize the NVH quality impact in driver and passenger’s perception in HEVs. To integrate this important aspect in the early stages of the development and design phase, simulation technologies can be used to address the customer acceptance. By analyzing NVH measurements, the different noise components of the vehicle operation can be separated into ICE-related noise, EM-related noise and driving noise.

The advancing electrification of the powertrain is giving rise to new challenges in the field of acoustics. Film capacitors used in power electronics are a potential source of high-frequency interfering noise since they are exposed to voltage harmonics. These voltage harmonics are caused by semiconductor switching operations that are necessary to convert the DC voltage of the battery into three-phase alternating current for an electrical machine. In order to predict the acoustic characteristics of the DC-link capacitor at an early stage of development, a multiphysical chain of effects has to be addressed to consider electrical and mechanical influences. In this paper, a new method to evaluate the excitation amplitude of film capacitor windings is presented. The corresponding amplitudes are calculated via an analytical strain based on electromechanical couplings of the dielectric within film capacitors.

Spark Ignited (SI) combustions engines in combination with different degrees of hybridization are expected to play a major role in future vehicle propulsion. Due to the combustion principle and the related thermodynamic efficiency, it is especially challenging to meet future CO2 targets. The layout and optimization of the overall system requires novel methods in the development process which feature a seamless transition between real and virtual prototypes. Herein, engine models need to predict the entire engine operating range in steady-state and transient conditions and must respond to all relevant control inputs. In addition, the model must feature true real-time capability. This work presents a holistic and modular modeling framework, which considers all relevant processes in the complex chain of physical effects in SI combustion.

To achieve future fleet CO2 emission targets, all powertrain types, including those with internal combustion engines, need to achieve higher efficiency. Next to others the reduction of friction is one contributor to increase powertrain efficiency. The piston bore interface (PBI) accounts for up to 50 % of the total engine friction losses [1]. Optimizations in this area combined with the use of low viscosity oil, which can reduce the friction of further engine sub-systems, will therefore have a high positive impact. To assess the friction of the PBI whilst considering cross effects of other relevant parameters for mechanical function (e.g. blow-by & wear) and emissions (e.g. oil consumption) AVL has established a holistic development method based around the AVL FRISC (FRIction Single Cylinder) engine with a floating liner measurement concept.

Meeting the particle number (PN) emissions limits in vehicle test sequences needs specific attention on each power variation event occurring in the internal combustion engine (ICE). ICE power variations arise from engine start onwards along the entire test drive. In hybrid systems, there is one further source for transient ICE response: each power shift between E-motor and ICE introduces gas flow variations with subsequent temperature response in the ICE and in the engine aftertreatment system (EAS). This bears consequences for engine out emissions as well as for the EAS efficiency and even for the durability of a catalytic converter. As system calibration engineers must decide on numerous actuator parameters, their decisions, finally, are crucial for meeting legislative limits under the boundary conditions given by the hybrid vehicle’s drive environment.

A growing development of hybrid or fully electrical drives increases the demand for an accurate prediction of noise and vibration characteristics of electric and electronic components. This paper describes the numerical and experimental investigation of noise emissions from power electronics, as one of the new important noise sources in electric vehicles. The noise emitted from the printed circuit board (PCB) equipped with multi-layer ceramic capacitors (MLCC) is measured and used for the calibration and validation of numerical model. Material properties are tuned using results from experimental modal analysis, with special attention to the orthotropic characteristic of the PCB glass-reinforced epoxy laminate sheet (FR-4). Electroacoustic excitation is pre-calculated using an extension of schematic-based EMC simulation and applied to the structural model. Structural vibrations are calculated with a commercial FEM solver with the modal frequency response analysis.

Future legislation scenarios as well as stringent CO2 targets, in particular under real driving conditions, will require the introduction of new and additional powertrain technologies. Beside the increasing electrification of the powertrain, it will be essential to utilize the full potential of the Internal Combustion Engine (ICE). There is clearly a competition of new and different ICE-Technologies [1] including VCR. VCR systems are expected to be introduced to a considerable number of next generation turbocharged Spark Ignited (SI) engines in certain vehicle classes. The implementation of Miller or Atkinson cycles is an essential criterion for increased geometric Compression Ratio (CR). The DUAL MODE Variable Compression System (VCS)TM enables a 2-stage variation of the connecting rod length and thus of the compression ratio (CR).

Most stringent emission legislations have been implemented in all major markets to improve air quality across the past years. This effects the product cost of the vehicles which is considered being critical and needs to be minimized. India suffers from bad air quality and countermeasures have been defined. One being the implementation of similar emission standards than EU VI. By doing so, India takes a large step going from the currently effective BS IV directly to BS VI. Emission reduction is currently mainly handled by the usage of EGR, thus no engine aftertreatment system has been applied. BS VI will require an aftertreatment (EAS) concept with several catalysts and corresponding control system. India is a very cost sensitive market and a carry over of solutions from the EU needs to be evaluated carefully and new approaches need to be found.

The paper focuses on an optimization methodology, which uses Design of Experiments (DoE) methods to define component parameters of parallel hybrid powertrains such as number of gears, transmission spread, gear ratios, progression factor, electric motor power, electric motor nominal speed, battery voltage and cell capacity. Target is to find the optimal configuration based on specific customer targets (e.g. fuel consumption, performance targets). In the method developed here, the hybrid drive train configuration and the combustion engine are considered as fixed components. The introduced methodology is able to reduce development time and to increase output quality of the early system definition phase. The output parameters are used as a first hint for subsequently performed detailed component development. The methodology integrates existing software tools like AVL CRUISE [5] and AVL CAMEO [1].