Conventional Powertrain Research Articles

Comparison of conventional and electric passenger aircraft for short-haul flights – A life cycle sustainability assessment

Due to the increasing demand for flights, the aviation sector will become one of the main emitters of harmful emissions such as carbon dioxide (CO2) and nitrogen oxides (NOx) in the long term. Especially short-haul flights are particularly critical because of the high kerosene consumption per passenger kilometer traveled. To counteract this development, the Flightpath 2050 strategy aims to reduce CO2 emissions by 75% and NOx emissions by 90% until 2050. To achieve these ambitious reduction goals, radical technological transitions are required. A promising strategy for short-haul flights is the deployment of battery-electric powertrains, which replace conventional jet engines. In addition, sustainable aviation fuels (SAFs) can replace fossil kerosene as energy carriers without changing the powertrain configuration and offer further reduction potentials. However, both solutions can be associated with negative environmental and socio-economic impacts along the life cycle. Therefore, this article aims to analyze the potentials of powertrain transition and alternative energy carriers to make the air transport system more sustainable. A well-to-wake life cycle sustainability assessment is conducted to analyze the environmental and socio-economic impacts of an electric powertrain and SAFs compared to a conventional powertrain powered by fossil kerosene. The assessment results indicate that especially the electric powertrain offers huge reduction potentials. Besides, the results also show that SAFs can reduce the environmental impacts of conventional aircraft in the short term. Therefore, both solutions will be required to achieve the short- and long-term reduction goals of Flightpath 2050.

Agile Powertrain Development: Considerations to Incorporate Agile Principles

Pressure to increase effectiveness and efficiency drives the product development process. The software industry has been using agile development approaches due to their advantages when coping with uncertainties and simultaneously increasing value. Therefore, the following work deals with the considerations of agile powertrain development. In order to identify important conditions for the incorporation of agile principles into powertrain development, semistructured interviews were conducted with experts from an engineering company. Having identified agile development challenges, advantages, and principles, the next step is comparing agile principles with the current principles of conventional powertrain development. Furthermore, a basic understanding of the powertrain development process regarding the incorporation of agile principles is established, the main attributes of powertrain development are investigated, and the key disciplines involved are identified. Finally, a model is created to assess whether the application of an agile or conventional development approach is more suitable.

Use of EGR e-pump for Dual-Mode Dual-Fuel engines in mild hybrid architectures

Highway transport sector is still expected to be dominated by internal combustion engines in the future, especially due to limitations in the introduction and applicability of full electrification for heavy-duty propulsive systems. Nonetheless, this sector is still under the objectives imposed in the roadmap towards carbon neutrality. For this, engine efficiency and low-emission combustion modes must be improved, and the introduction of synthetic fuels, low electrification levels and devices for engine optimization and energy management have proven to be a great advance towards these objectives. This work studies the application of an EGR e-pump for energy recovery and combustion optimization on a powertrain running on Dual-Mode Dual-Fuel combustion mode as a substitute of a complex dual route EGR system. The results include the evaluation of the impact of using energy recovery devices on combustion performance and emissions levels, as well as a numerical evaluation of driving conditions considering a medium-duty application in the transport sector under different driving scenarios. The results point out that the inclusion of the EGR e-pump can contribute to mitigate the drawbacks of removing the complex dual route system in terms of equivalent fuel consumption without greater impact in terms of emissions. Additionally, its application in mild hybrid platforms can promote a significant improvement in CO2 emissions, especially for urban areas (20% compared to a conventional powertrain based on HP EGR).

Degradation-Conscious Equivalent Consumption Minimization Strategy for a Fuel Cell Hybrid System

The design of an energy management strategy is critical to improving the fuel efficiency of a vehicle system with an alternative powertrain system, such as hybrid electric vehicles or fuel cell electric vehicles. In particular, in fuel cell electric vehicles, the energy management strategy should consider system degradation and fuel savings because the hardware cost of the fuel cell system is much higher than that of a conventional powertrain system. In this paper, an easily implantable near-optimal energy management controller is proposed. The proposed controller distributes power generation between the fuel cell and the battery to simultaneously minimize system degradation and fuel usage. The controller is designed to consider the degradation cost and fuel cost in the framework of the equivalent consumption minimization strategy concept. The proposed controller was validated with a fuel cell electric vehicle model in MATLAB/Simulink (MathWorks, Natick, MA, USA). The proposed control strategy showed significant overall cost reduction compared to a thermostat control strategy and a conventional Equivalent Consumption Minimization Strategy (ECMS) strategy.

EVALUATION OF PLUG-IN PARALLEL HEV TOPOLOGIES USING OPTIMAL CONTROL METHODS AND VEHICLE DYNAMICS SIMULATION


 
 
 
 Hybrid electric vehicle (HEV) powertrains with parallel topologies are among the frequently used layouts, because of their easy applicability on an existing conventional powertrain, by the addition of hybrid modules with mild, full, or a plug-in capability. This paper investigates three of such parallel HEV topologies: P2, P3, and P4; all in a plug-in variant, to find-out which one performs best. Apart from the topology consideration, one of the other common questions or challenges in HEV development is the ICE concept selection. To address it, the paper combines the three HEV topologies with three technologically different internal combustion engines, all with the same power outputs. Then, all the powertrain and ICE combinations are tested in homologation driving cycles and vehicle dynamics simulation test – different acceleration tests – giving a holistic methodology suitable for thorough HEV topology evaluation, identifying all possible hybridization benefits. To find the maximum CO2 potential, it is convenient to exclude the effect of the energy management control strategy on the CO2 result in a charge sustaining driving cycle; therefore, to use some optimal control method. For this task, the paper compares the Equivalent Consumption Minimization Strategy, that realizes a Pontryagin’s minimum principle against the Dynamic Programming optimal control method, which is based on Bellman’s principle of optimality. Both control methods are available as a part of GT-Suite 0D/1D/3D multi-physics CAE simulation software, that is used in our whole study.
 
 
 

Stirling system optimization for series hybrid electric vehicles

There have been many studies conducted to replace the conventional internal combustion engine (ICE) with a more efficient engine, due to increasing regulations over vehicles’ emissions. Throughout the years, several external combustion engines were considered as alternatives to these traditional ICEs for their intrinsic benefits, among which are Stirling machines. These were formerly utilized in conventional powertrains; however, they were not implemented in hybrid vehicles. The purpose of this study is to investigate the possibility of implementing a Stirling engine in a series hybrid electric vehicle (SHEV) to substitute the ICE. Exergy analysis was conducted on a mathematical model, which was developed based on a real simple Stirling, to pinpoint the room for improvements. Then, based on this analysis, other configurations were retrieved to reduce exergy losses. Consequently, a Stirling-SHEV was modeled, to be integrated as auxiliary power unit (APU). Hereafter, through an exergo-technological detailed selection, the best configuration was found to be the Regenerative Reheat two stages serial Stirling (RRe-n2-S), offering the best efficiency and power combination. Then, this configuration was compared with the Regenerative Stirling (R-S) and the ICE in terms of fuel consumption, in the developed SHEV on the WLTC. This was performed using an Energy Management Strategy (EMS) consisting of a bi-level optimization technique, combining the Non-dominated Sorting Genetic Algorithm (NSGA) with the Dynamic Programming (DP). This arrangement is used to diminish the fuel consumption, while considering the reduction of the APU’s ON/OFF switching times, avoiding technical issues. Results prioritized the RRe-n2-S presenting 12.1% fuel savings compared to the ICE and 14.1% savings compared to the R-S.

Machine Learning Approach for Constructing Wet Clutch Torque Transfer Function

<div class="section abstract"><div class="htmlview paragraph">A wet clutch is an established component in a conventional powertrain. It also finds a new role in electrified systems. For example, a wet clutch is utilized to couple or decouple an internal combustion engine from an electrically-driven drivetrain on demand in hybrid electric vehicles. In some electrical vehicle designs, it provides a means for motor speed reduction. Wet clutch control for those new applications may differ significantly from conventional strategy. For example, actuator pressure may be heavily modulated, causing the clutch to exhibit pronounced hysteresis. The clutch may be required to operate at a very high slip speed for unforeseen behaviors. A linear transfer function is commonly utilized for clutch control in automating shifting applications, assuming that clutch torque is proportional to actuator pressure. However, the linear model becomes inadequate for enabling robust control when the clutch behavior becomes highly nonlinear with hysteresis. The use of linear transfer function also leads to errors in powertrain simulation. This paper presents a machine learning approach to construct non-linear clutch torque transfer functions for robust powertrain control and simulation. Several regression methods are evaluated for accuracy and computational efficiency as compared to the conventional linear fitting approach. It is found that Gaussian Process Regression outperforms other approaches for accurately capturing non-linear clutch behavior during training. It also provides a confidence interval for predicted clutch torque. A simulation study is conducted for a hybrid powertrain system to illustrate the impact of the non-linear clutch transfer function on engine restart behavior, as compared to the conventional linear clutch model. The use of machine learning based regression method enables accurate representation of wet clutch behavior for improved simulation and robust control development.</div></div>

Commercial Viability Assessment and Planning of Safety-Critical Embedded SW of Electrified Road Vehicles

<div class="section abstract"><div class="htmlview paragraph">Recent extraordinary technological progress in the field of high-voltage-batteries has led an evolution in the automotive industry, resulting in vehicle manufacturers to shift from conventional powertrains towards electric ones. However, electrified road vehicles are amazingly complex. Today, the number of operations for a modern electric vehicle grew from millions to billions per second. This is mainly fueled by the electrification and safety requirements in addition to critical core functionalities. This emphasizes the importance of software development cost, effort, and production planning in the automotive industry. In this paper, in the framework of EU funded H2020 OBELICS project, a <i>detailed</i>-COCOMO approach is proposed for a manually coded safety-critical embedded SW for an electric vehicle not only to plan the project well in advance but also to assess its commercial viability using quantifiable cost metrics to make the process more objective and repeatable. In this context, a case study is given for a battery-management software using an algorithmic model. The case-study has demonstrated not only the planning requirements but also the impact of project type on effort and time estimation in each phase of the software lifecycle. The results have shown that inaccurate software project type estimation can lead an error of up to 16% in effort and 19% in development time according to the phase. It also shows that reliability, database size and complexity are the major contributors of the total time, effort and hence of the cost. The results have also demonstrated the impact of model-based design and automated code generation tools on planning for different phases of the V-cycle briefly.</div></div>

Experimental and theoretical studies on energy characteristics of hydraulic hybrids for thermal management

The development of fuel-efficient vehicles has increased along with the needs of consumers and the rise of environmental issues. Hybrid vehicles have become a popular alternative to conventional powertrains in the passenger vehicle market. Hydraulic hybrid vehicles have been applied to certain applications with clear benefits, such as high power density. To increase the base of academic knowledge, the energy characteristics of hydraulic hybrids were experimentally and theoretically studied for thermal management. First, measurement data for a series hydraulic hybrid system were collected by hardware in the loop test rig for different temperature conditions. The experimental results were compared for different thermal management conditions, thus showing the power consumption behaviors at different system temperatures. Also, a theoretical approach with thermodynamic properties was introduced for analyzing the energy characteristics of hydraulic hybrid systems. The theoretical results revealed possible explanations for the relationship between energy saving and thermal management for hydraulic hybrid systems. This study was worthy not only in that the experimental data itself worth as reference data for energy characteristics of hydraulic hybrid systems for thermal management, but also in that a novel theoretical approach for energy characteristics analysis was introduced, using energy and exergy analysis for the first time.

Drivability improvements obtained using a mild hybrid electrical system on a vehicle equipped with a manual gearbox

In order to fulfil the latest and future emission standards, all vehicles will need to be equipped with hybrid powertrains or advanced depollution systems. For low cost and entry level range of vehicles, in order to keep the production costs low, the simplest choice of hybridization is the mild-hybrid system with integrated starter-generator (ISG). This paper contains a model of a mild-hybrid electric vehicle equipped with a manual gearbox with focus on the drivability performance of the powertrain. The goal of this paper is to find out the drivability performances of a hybrid vehicle by simulation and to show the improvements compared to a similar vehicle equipped with a conventional powertrain.

Fuel consumption and emission improvements obtained using a mild hybrid electrical system on a vehicle equipped with a manual gearbox

The latest emission requirements for vehicles requires major improvement in vehicles fuel consumption and emission performance. For entry level range of vehicles, in order to keep the production costs low, the simplest choice of hybridization is the mild-hybrid system with integrated starter-generator (ISG). This paper contains a model of a mild-hybrid electric vehicle equipped with a manual gearbox and a model of conventional vehicle with focus on the emission performance. The goal of this paper is to find out the fuel consumption and emission of a mild hybrid electric vehicle by simulation and to show the improvements compared to a similar vehicle equipped with a conventional powertrain.

Modeling and Simulation of an Electric Vehicle with Independent Rear Motors to Estimate the Fuel Economy during EPA Drive Cycles

The “Car of the Future” project converted a 2015 rear-wheel drive (RWD) Subaru BRZ into a hybrid electric vehicle (HEV) with an intermediate milestone of a battery electric vehicle (BEV). BEV architecture required removal of the conventional powertrain components, such as internal combustion engine, transmission and differential, introduced an electric axle and battery. This intermediate BEV step provided a point at which the vehicle could be evaluated in its all electric operation with the absence of what was once critical components including its original powertrain and powertrain electronics. This step also ensures the electric components are working properly before more complexity is added to the system in building HEV. In our previous work, BEV Vehicle Technical Specifications (VTS) or requirements were developed and an electric axle was appropriately sized and selected to meet these requirements. After selecting the electrical axle with independent rear motors that will meet BEV performance requirements, Environmental Protection Agency (EPA) fuel economy rating of the BEV should be assessed. This paper presents a drive cycle analysis of the BEV vehicle using the EPA Urban Dynamometer Driving Schedule (UDDS) and Highway Fuel Economy Test (HWFET) drive cycles by means of dynamic modeling and simulation. In this study, the power required at the wheels, the efficiency of each motor and the energy required at the selected electrical axle were determined. In addition, the city, highway and combined miles per gallon equivalent (MPGe) fuel economy were determined.

Innovationswandel in der deutschen Kfz-Industrie: Eine Analyse mit der IW-Patentdatenbank

Social and political change necessitates corresponding innovations in motor vehicle technology. This paper analyses the nature of current technological progress in Germany's motor vehicle industry. Building on an existing methodology for gauging the extent of innovation, the authors present a new procedure for analysing patent performance in the electrified powertrain segment. From 2010 to 2018, the period under review, the total patent output of the motor vehicle industry in Germany increased by 35 per cent. At the same time, the total number of patent applications in Germany identified by the electric hybrid filter (EHF) introduced here increased by almost 125 per cent. Since 2015 there has been a clear shift between patent applications relating to conventional and to electrified powertrains: the proportion of the car industry's total patent output dealing with conventional powertrains has seen a sharp decline, while the share of patent applications based on electrified powertrains has expanded significantly. At Germany's three big car manufacturers, BMW, Daimler and the Volkswagen Group, electric powertrain patents already outnumbered those for its conventional counterpart in 2018. The same shift in innovatory activity has been apparent among the five largest suppliers of automotive components, although here the conventional powertrain still dominates. Aside from these eight automotive giants, which between them have filed 88 per cent of all recent patent applications concerned with electrified powertrains, there is very little patent activity in this field in Germany. Among the smaller suppliers, the transition to electrified powertrains actually seems to have stopped. While this is a serious challenge to their future viability, it also offers a great potential for making up lost ground.

Energy Efficient Torque Allocation Design Emphasis on Payload in a Light-Duty Distributed Drive Electric Vehicle

Light-Duty Electric Vehicle (LDEV) with a distributed drive powertrain provides several potential advantages in terms of flexibility, controllability and responsiveness over conventional powertrains. The precise distribution of driving and braking torque of such configuration is crucially vital for improving the overall performance and efficiency of the vehicles. This paper proposes a new torque allocation (TA) model emphasizing the wheel load variation due to the passenger occupancy payload. A light-duty vehicle model is developed along with the occupancy payload arrangement and a dynamic tire-road friction estimation method for the control system for wheel slip. This proposed TA algorithm uses offline optimization to derive the necessary transmissible torque to the driving wheels. Unlike conventional optimization, it adopts a set of predefined distribution coefficients. Therefore it can execute in a real time platform without high computation power and additional hardware requirements. The efficiency of the model is analyzed using Indian Urban Drive Cycle (IN-UDC). A comparative analysis using a traditional torque allocation model highlights the contributions of this novel torque allocation. The results obtained from various simulations demonstrate the effectiveness of the proposed new TA algorithm.

Solving Eco-Driving Problems Using Indirect Collocation Method and Smooth Representation

This letter discusses the eco-driving problem, considering both electric and conventional powertrains, and presents a pathway to solving it numerically using an indirect collocation method. Despite the low-order system dynamics, the piecewise fuel/efficiency map, gear shifting, and real-world traffic/road situations bring system discontinuities/switchings and pure state constraints into the problem formulation, which make the problem highly nonlinear and nontrivial to solve. This letter introduces smooth approximations to convert the original problem to an unconstrained (and penalized) smooth boundary-value problem. This approach eliminates the discussion of the switching structure and leads to a lightweight Newton-method-based solution procedure.

Electric torque assist and supercharging of a downsized gasoline engine in a 48V mild hybrid powertrain

48V systems enable not only mild hybrid functionalities such as recuperation or torque assist by a belt-driven starter generator (BSG), but also electrification of accessories and the engine boosting system. To maximize the powertrain efficiency, a proper layout of the electrified system and an optimized distribution of the electric power during transient operation is essential. In this study, a vehicle co-simulation of a conventional powertrain with a downsized turbocharged gasoline engine is extended by a 48V system with an electric compressor (eC) and a BSG. The control functions of the eC and BSG are based on a state-of-the-art vehicle application and calibrated for transient operating conditions. The engine model, which is built using a one-dimensional crank angle resolved approach in GT-POWER, has been validated with measurement data and is used to predict the interaction between the eC and the engine air path. The investigations using the simulation platform show that the 48V eC and the BSG can significantly improve the fuel effïciency if the electric energy consumption is initially neglected. However, when considering the electric energy consumption within the vehicle co-simulation, efficient operation is particularly depending on driver torque demand, the battery state-of-charge and charging effïciency. Hence, intelligent operating strategies are necessary to take advantage of the better torque response and improve fuel consumption at the same time.

Microsimulation of energy and flow effects from optimal automated driving in mixed traffic

This paper studies the energy and traffic impact of a proposed Anticipative Cruise Controller in a PTV VISSIM microsimulation environment. We dissect our controller into two parts: 1. the unconnected mode, active when following a human-driven vehicle, and 2. the connected mode, active when following another automated vehicle equipped with connectivity. Probabilistic constraints balance safety considerations with inter-vehicle compactness, and vehicle constraints for acceleration capabilities are expressed through the use of powertrain maps. Emergent highway traffic scenarios are then modeled using time headway distributions from empirical traffic data. To study the impact of automation over a range of demands of free-flow to stop-and-go, we vary vehicle flux from low to high and vary automated vehicle penetration from low to high. When examining all-human driving scenarios, network capacity failed to meet demand in high-volume scenarios, such as rush-hour traffic. We further find that with connected automated vehicles introduced, network capacity was improved to support the high-volume scenarios. Finally, we examine energy efficiencies of the fleet for conventional, electric, and hybrid vehicles. We find that automated vehicles perform at a 10%–20% higher energy efficiency over human drivers when considering conventional powertrains, and find that automated vehicles perform at a 3%–9% higher energy efficiency over human drivers when considering electric and hybrid powertrains. Due to secondary effects of smoothing traffic flow and reducing unnecessary braking, energy benefits also apply to human-driven vehicles that interact with automated ones. Such simulated humans were found to drive up to 10% more energy-efficiently than they did in the baseline all-human scenario.

An uncertainty analysis of the energy intensity of 37 materials used in automobile manufacturing: Statistical methods and recommendations

Life Cycle Inventories must meet the data quality requirements set out by the goal and scope of a Life Cycle Assessment. The literature on the timing of updating inventory data to meet the data quality requirements is almost non-existent. In this study, data were taken from publicly available reports (corporate, peer-reviewed or governmental), congresses, proceedings, technical papers, international databases and LCAs. Monte Carlo simulations were used to test for variance; regression analysis was used to determine correlation between time and energy intensity. Different conventional automobile power train configurations were examined along with lightweight versions. Monte Carlo simulations were programmed for each automobile power train configuration. Least absolute residuals methods were used to confirm whether the variance seen in simulations was due to time or to other factors such as uncertainty or scattered data. The Monte Carlo simulations identified the variation by material and quantified their significance. Least absolute regression analysis identified and confirmed which materials have a clearly delineated temporal relationship: rubber, polyethylene terephthalate, polypropylene, lead, copper, steel, recycled steel, aluminum and recycled aluminum. Consequently, recommendations are given for the time intervals for necessary data updates which, depending on the material in question, are between two and five years.

Transmotor-Based Powertrain for High-Performance Electric Vehicle

This article presents a Transmotor-based powertrain in order to improve the performance of the powertrain on electric vehicles. In the proposed powertrain, the maximum torque can be available at a larger speed range. This feature leads to three notable improvements that enhance the powertrain performance and efficiency. First, higher gradeability is achievable at any vehicle speed that enables maintaining the desired speed at a higher road grade. Furthermore, acceleration and deceleration (regenerative braking) are significantly improved, in comparison to the conventional powertrain, without increasing the powertrain electrical rating. Finally, the efficiency can be improved due to the effective kinetic energy recovery at higher speeds. Numerical simulations and emulation tests are presented to demonstrate the above improvements.

Comparative Study of Powertrain Hybridization for Heavy-Duty Vehicles Equipped with Diesel and Gas Engines

This article describes a study that aimed to estimate the fuel-saving potential possessed by the hybridization of conventional powertrains intended for heavy-duty vehicles based on diesel and natural gas fueled engines. The tools used for this analysis constitute mathematical models of vehicle dynamics and the powertrain, including its components, i.e., the engine, electric drive, transmission, and energy storage system (ESS). The model of the latter, accompanied by experimental data, allowed for an analysis of employing a supercapacitor regarding the selection of its energy content and the interface between the traction electric drive and the ESS (in light of the wide voltage operating range of supercapacitors). The results revealed the influence of these factors on both the supercapacitor efficiency (during its operation within a powertrain) and the vehicle fuel economy. After implementation of the optimized ESS design within the experimentally validated vehicle model, simulations were conducted in several driving cycles. The results allowed us to compare the fuel economy provided by the hybridization for diesel and gas powertrains in different driving conditions, with different vehicle masses, taking into account the onboard auxiliary power consumption.