Powertrain Technologies Research Articles

Decarbonizing the European Automobile Fleet: Impacts of 1.5 °C-Compliant Climate Policies in Germany and Norway

This paper focuses on assessing the impact of different policy measures, in particular different vehicle taxation schemes, on the composition of the fleet of newly registered cars in Norway and Germany. For this purpose, a fleet turnover model was extended by an economic model for predicting tax-induced market penetration of different powertrain technologies. The economic model determines a cost-optimal powertrain portfolio of the newly registered passenger cars based on financial and non-financial aspects. Model evaluation was performed for the case of Norway and Germany by means of reference scenarios that map the current taxation and non-financial preferences, such as range anxiety. The reference scenario in both cases overestimates the role of ZEVs, but is able to reflect the differences in regionalities (driven mainly by the taxation). Considering disutility costs leads to a shift away from ZEVs. Among the considered non-financial preferences, range anxiety has the strongest influence. The optimization framework is a valuable predictor of qualitative statements regarding the impact of tax measures on the fleet composition of newly registered passenger cars.

Strategic flexibility in shifting to electrification: a real options reasoning perspective on Toyota and Nissan

This paper addresses commitment versus flexibility in the face of uncertainties about the electrification of vehicle powertrain technologies. A real options reasoning perspective is employed to analyse the potential option structures and underlying logic behind the strategies of Toyota and Nissan. The case analyses indicate that the Japanese carmakers have (compound) options to expand their electrified powertrain portfolios and switch battery sources. The findings also suggest that the stability of powertrain design rules serves as a foundation of real options and that carmakers' approaches to balancing the commitment to, and flexibility for, particular strategic actions are influenced by the nature of the uncertainties. Further, firms' perceptional and behavioural biases over uncertainties will affect the execution or abandonment of the options.

Predicting the effect of electric and hybrid-electric aviation on acoustic pollution

Abstract In the quest for the reduction of noise pollution, novel hybrid-electric or fully-electric power-trains promise to provide a substantial contribution. Especially closer to airfields, where acceptability issues tend to limit air operations with conventional fuel-burning engines, such novel power-trains allow to fly terminal maneuvers with a dramatically reduced impact on pollution. Considering the General Aviation (GA) field, where such new types of propulsion are more likely to gain a significant market share thanks to their favorable characteristics for this weight category, the reduction of the noise impact on ground may increase the infrastructural value of smaller airfields, often located in densely populated areas. This in turn would help in making novel power-train technologies economically advantageous at a system level. Despite these evident advantages, a methodology to quantify noise emissions of a novel type of power-train has not been identified yet – a fundamental step towards the assessment of the potential contribution of hybrid-electric or fully-electric aircraft to the global scenario of future aviation. This work introduces and discusses a possible procedure to provide such estimation. While mainly focused on the field of propeller-driven GA aircraft, the procedure presented herein can be easily scaled to cope with the specific features of heavier categories.

Strategic flexibility in shifting to electrification: a real options reasoning perspective on Toyota and Nissan

This paper addresses commitment versus flexibility in the face of uncertainties about the electrification of vehicle powertrain technologies. A real options reasoning perspective is employed to analyse the potential option structures and underlying logic behind the strategies of Toyota and Nissan. The case analyses indicate that the Japanese carmakers have (compound) options to expand their electrified powertrain portfolios and switch battery sources. The findings also suggest that the stability of powertrain design rules serves as a foundation of real options and that carmakers' approaches to balancing the commitment to, and flexibility for, particular strategic actions are influenced by the nature of the uncertainties. Further, firms' perceptional and behavioural biases over uncertainties will affect the execution or abandonment of the options.

Analysis and testing of electric car incentive scenarios in the Netherlands and Norway

Past and future electric vehicle sales shares in the Netherlands and Norway are analysed with the Powertrain Technology Transition Market Agent Model. This system dynamics model was expanded to include the leading Norwegian car market and updated with recent data on policy incentives. Three model validation tests are discussed: the reproduction of past behaviour from 2010 till 2017, policy sensitivity, and feedback loop knock-out analysis. Findings point in the direction that regulation on emission targets for manufacturers are necessary for a transition away from new sales of fossil fuel-based vehicles. Only strong incentives resulted in large sales shares of zero emission vehicles in the Netherlands and Norway.

Methodical Comparison of Alternative Powertrain Technologies for Long-Distance Mobility Using Germany as an Example

The main barriers to the wide acceptance of electric vehicles, such as the limited driving range or the high acquisition costs, are to be countered by various technology alternatives for the powertrain of the future. Promising developments include improved battery technologies, fuel cell technologies or a constant power supply of the vehicle while driving, for example through dynamic inductive charging. In this context, a holistic technology comparison would contribute to a comprehensive and understandable information situation by making the heterogeneous technological concepts comparable with regard to different evaluation criteria. Therefore, this work describes the basic assumptions of the proposed holistic comparison of alternative powertrain technologies for long-distance mobility. Relevant framework conditions are structured and a procedure for the evaluation of infrastructure expenditures is shown. Building on this, a selection of key performance indicators is defined and explained. The proposed KPI framework is applied to a passenger car in the economic area Germany. The results show that by using electrified roadways, ecological as well as economic advantages against other alternative powertrain designs can be derived.

A multicriteria methodology for estimating consumer acceptance of alternative powertrain technologies

A multicriteria methodology for estimating consumer acceptance of vehicles with alternative powertrain technologies is presented. The approach is based on the non-compensatory ELECTRE TRI method and compares hybrid, plug-in hybrid, and electric vehicles to conventional models. Criteria considered are ownership costs and restrictions to vehicle use, which apply mainly to electric vehicles. The methodology is applied to a case study of 94 vehicles of different market segments and alternative powertrains. The analysis is carried out per segment and considers two driver profiles, city and all-purpose, and a baseline scenario for all cases. Output is tested for statistical significance, with powertrain technology as disaggregating factor, and a sensitivity analysis on the base scenario is also carried out, as well as a comparison with results derived by a compensatory multicriteria method (TOPSIS). Results show that conventional vehicles are the top choice for the small vehicles segment, due to lower purchase prices and higher use flexibility. For medium sized vehicles, all powertrain technologies are competitive for city drivers, whereas for all-purpose drivers, use restrictions for electric vehicles make these less attractive. The baseline scenario and sensitivity analysis highlight that opting for an electric vehicle depends strongly on the driver's use flexibility needs. As such, an electric vehicle can be either very attractive or outright unusable, regardless of financial considerations. It is also seen that plug-in hybrids do not present any significant advantage, as compared to other, non-electric choices, due to their higher purchase prices.

The Effect of Reducing Electric Car Purchase Incentives in the European Union

The importance of electric car purchase incentives is starting to be questioned. The objective of this paper is to explore the potential effect of reducing or removing electric car purchase public subsidies in the European Union. To this end, the system dynamics Powertrain Technology Transition Market Agent Model is used. The size and timing of purchase incentives for this technology in European countries are investigated under eight scenarios and sensitivity analysis performed. The simulations suggest that, in the short-run, the electric car market share is higher when the subsidies remain in place. In the medium-run, a purchase subsidy scheme granting €3000 for plug-in hybrid electric cars and €4000 for battery electric cars over the period 2020–2024 yields the fastest electric car market uptake of all the scenarios considered. We conclude that, though the current evolution of the battery price is favorable, electric car purchase subsidies remain an effective policy measure to support electro-mobility in the next years.

Do technical improvements lead to real efficiency gains? Disaggregating changes in transport energy intensity

Fuel economy standards are a key measure to increase the rate of efficiency improvements in passenger cars. The fuel consumption of vehicles can be improved in three ways: incremental technical efficiency improvements within powertrain technologies, market shifts to more efficient types of powertrains and by limiting increases in the size and performance of vehicles. This study quantifies the effect of each of these three drivers on the fuel consumption of British vehicles between 2001 and 2018 using driver-reported data on real-world fuel consumption. Analysis shows the introduction of EU fuel economy standards in 2008/09 had little effect on the rate of real technical efficiency improvements in British vehicles. Instead of adopting technical improvements at a higher rate or limiting the size and power of vehicles, these results suggest vehicle manufacturers met emissions standards by increasing the divergence between laboratory tests and real-world fuel consumption. This study adds to the growing literature calling for official test procedures to be representative of real-world driving.

Optimal sizing and adaptive energy management of a novel four-wheel-drive hybrid powertrain

Hybrid powertrain technology must be applied to sport utility vehicles (SUVs) to meet stringent fuel economy and emissions standards. As an essential attribute of SUV, four-wheel-drive (4WD) offers flexible torque arrangement and results in safe and powerful driving under off-road conditions. In this paper, we propose a novel compound 4WD hybrid powertrain by adding an extra output shaft to a conventional power-split hybrid electric vehicle. By connecting two output shafts to the front and rear axles, this hybrid powertrain could deliver the engine power to four wheels simultaneously, while maintaining the electrical continuously variable transmission (ECVT) function. The dynamics, modeling and system characteristics of the compound 4WD hybrid powertrain are presented firstly. Using an integrated optimization framework to optimize components’ sizes, the proposed 4WD hybrid powertrain indicates 36.22% and 13.82% fuel economy improvements than conventional 4WD SUV in city and highway cycles, respectively. Since it is difficult to implement the DP in real-time controller, we present an adaptive equivalent consumption minimization strategy (A-ECMS), whose equivalent factor (EF) is constrained by its theoretical extremum. Finally, simulation results show A-ECMS achieves better fuel economy than regular ECMS.

Energy saving potentials of modern powertrains utilizing predictive driving algorithms in different traffic scenarios

In this article, we analyze the interaction between powertrain technology, predictive driving functionalities, and inner-city traffic conditions. A model predictive velocity control algorithm is developed that utilizes dynamic traffic data as well as static route information to optimize the future trajectory of the considered ego-vehicle. This controller is then integrated into a state-of-the-art simulation environment for automated driving functionalities to calculate energy saving potentials for vehicles with a conventional gasoline engine powertrain and a P3-hybrid powertrain configuration as well as for a battery electric vehicle based on real driving measurements. The comparison of these powertrains under various traffic conditions shows that all three technologies profit from predictive driving functionalities. The determined reduction in energy demand ranges from 15% to more than 40%, but it is highly dependent on the boundary conditions and the selected powertrain technology. Specifically, it is shown that electrified powertrains can profit the most when the time-gap to the preceding vehicle is maintained at a high level. For a conventional powertrain, this effect is less pronounced and can be attributed to the efficiency characteristics of gasoline engines. It can be concluded that the development of advanced predictive driving functionalities requires microscopic simulation of inner-city traffic to achieve optimum results with regard to energy consumption.

Real World Fuel Consumption and Emissions From LDVs and HDVs

Real world emission and energy consumption behavior from vehicles is a key element for meeting air quality and greenhouse gas (GHG) targets for any country. While CO2 fleet targets for vehicles are defined on basis of standardized test procedures, in real driving conditions manifold parameters show large variabilities. Main differences are Driving cycle Vehicle loading and driving resistances Ambient temperature levels, start conditions and trip length Gear shift behavior of the drivers Power demand from auxiliaries Fuel quality For the upcoming update of the Handbook Emission Factors for Road Transport (HBEFA 4.1) we have performed analysis, measurements and simulations to elaborate real world energy consumption values for 2-wheelers, passenger cars (PC), light commercial vehicles (LCVs) and heavy duty vehicles (HDVs), so called emission factors (EF). EFs show fuel consumption or emission level in [g/km] and [#/km] for fuel, gaseous exhaust gas components and also for the particle number (PN). EFs are provided for a lot of different traffic situations covering stop & go up to highway for different road gradient categories. EFs are different for each vehicle category and for each powertrain technology and emission standard (from EURO 0 gasoline PC to EURO VI HDV with CNG engine). To produce the EFs, vehicle tests from chassis dyno and from on-board measurements were collected in all European labs to set up models for all vehicle segments in the passenger cars and heavy duty emission model (PHEM). The models for PC and LCVs were based on weight and road load data available from the type approval test, the worldwide harmonized light vehicles test procedure (WLTP), and then calibrated in a stepwise approach to consider all influences in real world driving. Finally, the results for new vehicle fleet fuel consumption values were compared with data from the fuel consumption monitoring data base. For HDVs, the models are based on data from the development of the HDV CO2 determination method (Regulation (EU) 2017/2400, “VECTO”). The methods and also the results in terms of differences between real world and type approval for loading, road load, energy consumption and emission levels are described in this paper.

Strategic intentions to the diffusion of electric mobility paradigm: The case of internal combustion engine vehicle

The automobile industry is currently undergoing a profound change. Stringent emission standards coupled with issues of climate change and technological advances in alternative powertrain technologies are forcing the industry to set new strategic courses. While the electric vehicles are not yet profitable, their growing market share and advancement in battery technology will pose a considerable substitution risk for incumbent firms. Incumbent firms can react to this changed environment by implementing one of the three generic strategies, which are “exit”, “switch” and the “sailing ship effect” (SSE). Prior research has documented SSE as an explanatory factor for continuous improvement in conventional propulsion technology in light of facing a major technology transition towards electric mobility. To further contribute to the discussion on patterns of strategic intention, we propose an additional perspective on strategic action pattern in response to technological competition threat. To this end, the underlying pace of ICEV (internal combustion engine vehicle) technology development and its evolutionary technology path were examined by employing a patent-based analysis framework. The findings show that although the ICEV technology has entered into maturity stage, a complete departure from conventional combustion engines is not in sight for the next few decades. Moreover, we provide empirical evidence for a mimicry-based technological evolution pattern in the field of ICEV. This study can provide valuable insight for R&D managers and policy makers seeking to facilitate the transition from conventional vehicles to zero-emission vehicles.

Estimation of CO2 Emissions of Internal Combustion Engine Vehicle and Battery Electric Vehicle Using LCA

In order to reduce vehicle emitted greenhouse gases (GHGs) on a global scale, the scope of consideration should be expanded to include the manufacturing, fuel extraction, refinement, power generation, and end-of-life phases of a vehicle, in addition to the actual operational phase. In this paper, the CO2 emissions of conventional gasoline and diesel internal combustion engine vehicles (ICV) were compared with mainstream alternative powertrain technologies, namely battery electric vehicles (BEV), using life-cycle assessment (LCA). In most of the current studies, CO2 emissions were calculated assuming that the region where the vehicles were used, the lifetime driving distance in that region and the CO2 emission from the battery production were fixed. However, in this paper, the life cycle CO2 emissions in each region were calculated taking into consideration the vehicle’s lifetime driving distance in each region and the deviations in CO2 emissions for battery production. For this paper, the US, European Union (EU), Japan, China, and Australia were selected as the reference regions for vehicle operation. The calculated results showed that CO2 emission from the assembly of BEV was larger than that of ICV due to the added CO2 emissions from battery production. However, in regions where renewable energy sources and low CO2 emitting forms of electric power generation are widely used, as vehicle lifetime driving distance increase, the total operating CO2 emissions of BEV become less than that of ICV. But for BEV, the CO2 emissions for replacing the battery with a new one should be added when the lifetime driving distance is over 160,000 km. Moreover, it was shown that the life cycle CO2 emission of ICV was apt to be smaller than that of BEV when the CO2 emissions for battery production were very large.

Life cycle (well-to-wheel) energy and environmental assessment of natural gas as transportation fuel in Pakistan

Consumers and organizations worldwide are searching for low-carbon alternatives to conventional gasoline and diesel vehicles to reduce greenhouse gas (GHG) emissions and their impact on the environment. Natural gas as an alternative transportation fuel has made significant inroads in the light and heavy duty vehicles market over the last fifteen years. In a sustainable development view, both vehicle emissions and energy supply chain analysis from well-to-wheel must be addressed. The aim of this research is to provide a Well-to-Wheel (WtW) assessment of energy consumptions and GHG emissions for 25 combinations of automotive fuel and matching powertrain systems, with a special focus on the natural gas pathways. Although several well-to-wheel studies available in literature are comprehensive in relation to developed countries’ conditions, it is problematic to apply the results to developing countries fuel markets, since the local fuel conditions and respective vehicle powertrain technologies are considerably different. This study deal with a comparative well-to-wheel analysis of natural gas, diesel and gasoline fuels looking at the Pakistanis situation but the models and approaches for this study can be applied to other countries having similar characteristics, as long as all the assumptions are well defined and modified to find a substitute automotive energy source and establish an energy policy in a specific region. The well-to-tank step was made using the GREET model, developed by the U.S. Argonne National Laboratory while tank-to-wheel analysis was performed using AVL Cruise, a commercially-available backward vehicle simulator. Later both stages were integrated in a well-to-wheel stage where relevant indexes were proposed and discussed. The results indicate that natural gas vehicles are 5–17% and 23–36% less fuel efficient, depending on the engine technology employed as compared to gasoline and diesel powertrain, respectively. Natural gas appears as an environmental efficient pathway regarding GHG emissions, especially compared to gasoline. In addition, using 20-year GWPs instead of 100-year GWPs increases WtW GHG emissions by 19–26% for natural gas pathways.

Evaluation of the Life Cycle Costs for urban buses equipped with conventional and hybrid drive trains

The life cycle cost (LCC) methodology provides understanding of economic aspects of urban buses equipped with different types of propulsion. The LCC analysis delivers the sum of costs related to the acquisition, operation, repair and maintenance disposal as well as the costs for the each bus power train technology. The method allows to take into account all costs for the whole vehicle’s life cycle and creates a recondition for precise information database for decision making. In addition to the economic factors LCC can be extended to environmental aspects such as greenhouse gases emissions. The environmental impacts of the vehicle lifetime may be presented in monetary values. The paper presents the Life Cycle Cost analysis undertaken for urban buses fitted with conventional, series hybrid and parallel hybrid drives. Provided LCC analysis includes the economic and environmental aspects. The paper also delivers the evaluation of the total air pollutant emissions for all stages of lifetime of the each analysed urban bus. The results show that the hybrids have slightly lower life cycle cost than conventional bus. Moreover, hybrid buses were found to have lower life cycle environmental impacts.

Vehicle energy consumption estimation using large scale simulations and machine learning methods

Vehicle energy consumption and powertrain operations for future vehicle powertrain technologies are predicted through full-vehicle simulations using Autonomie, a simulation tool developed at Argonne National Laboratory. Over 1 million vehicles, with different powertrain types (conventional and numerous electrified powertrains) and component technologies (advanced engines, batteries, electrical machines, light weighting) are simulated for outputs including vehicle fuel economy and cost. Despite the ability of Autonomie to predict fuel economy given various combination of vehicle inputs, the full-vehicle simulation is very time-consuming. It takes approximately 84 h to simulate for 33,060 vehicles even using distributed computing on a cluster of 128 worker nodes. Moreover, Autonomie is unable to populate a continuous output space through simulation since it only yields outputs with discrete values instead of an input-output relation.This paper proposes a novel large-scale learning and prediction process (LSLPP) via machine learning approaches to answer the need for a continuous space of vehicle fuel economy and a more efficient simulation process. By learning in a supervised fashion to discover structures in data, the machine learning approaches seek to train a model that can explain the data with which we can perform prediction over unseen data. As such, we are able to accomplish analytic continuation on the current discrete space of simulation results. In addition, we present a random-sampling-based numerosity reduction algorithm incorporated in LSLPP that reduces simulation runs and improves efficiency of data procurement. We analytically derive a theoretical bound in order to guarantee the effectiveness of our algorithm. We also compare random sampling to stratified sampling and suggest sampling strategies. A user-friendly tool is developed to support the process. Our experimental results confirm that the proposed LSLPP is able to greatly accelerate prediction and analysis of vehicle fuel economy. The output of this study is used by the US government to evaluate the impact of its R&D funding on energy security and CO2 emission as well as for the setting of Corporate Average Fuel Economy (CAFE) standards.

A Dynamic Fleet Model of U.S Light-Duty Vehicle Lightweighting and Associated Greenhouse Gas Emissions from 2016 to 2050.

Substituting conventional materials with lightweight materials is an effective way to reduce the life cycle greenhouse gas (GHG) emissions from light-duty vehicles. However, estimated GHG emission reductions of lightweighting depend on multiple factors including the vehicle powertrain technology and efficiency, lightweight material employed, and end-of-life material recovery. We developed a fleet-based life cycle model to estimate the GHG emission changes due to lightweighting the U.S. light-duty fleet from 2016 to 2050, using either high strength steel or aluminum as the lightweight material. Our model estimates that implementation of an aggressive lightweighting scenario using aluminum reduces 2016 through 2050 cumulative life cycle GHG emissions from the fleet by 2.9 Gt CO2 eq (5.6%), and annual emissions in 2050 by 11%. Lightweighting has the greatest GHG emission reduction potential when implemented in the near-term, with two times more reduction per kilometer traveled if implemented in 2016 rather than in 2030. Delaying implementation by 15 years sacrifices 72% (2.1 Gt CO2 eq) of the cumulative GHG emissionmitigation potential through 2050. Lightweighting is an effective solution that could provide important near-term GHG emission reductions especially during the next 10-20 years when the fleet is dominated by conventional powertrain vehicles.

Global development of emissions reduction strategies from light duty vehicles

The automotive industry (especially the LDV sector) is currently under unprecedented pressure from a wide range of factors particularly in terms of environmental performance and fuel consumption. Long-established test procedures are changing and standards are becoming much harder to meet, necessitating changes in R&D methods, strategies and calibrations, fuels and – crucially – powertrains. This paper examines the current situation regarding regulation of emissions rules and the impact on powertrains used in new vehicles across the world. Powertrain technologies which can help to overcome challenges are mentioned and key trends are analysed. Finally, some brief comments are offered on what the next few years hold for the automotive industry.

The evolution of world class manufacturing toward Industry 4.0: A case study in the automotive industry

In order to increase the level of global competitiveness and improve the performance of production system, a large number of manufacturing companies have implemented world class manufacturing (WCM) approach, which has developed based on the third industrial revolution and the need for mass production. The evolution in production equipment and communication technologies, and the demand of markets for personalized mass production, have forced manufacturing companies to transform their production systems and prepare for a revolution. This revolution, known as Industry 4.0 (I4.0), or the digital transformation, has been introduced as a new type of organization of manufacturing systems that is more flexible and agile, and is based on using large amounts of information and data in the decision-making process. One of the main characteristics of this concept is decentralization, which allows different subsystems to make decisions autonomously in order to have self-organization systems. There are some important differences between the principles of WCM and I4.0. World class manufacturing is mainly based on continuous improvement and cost reduction, without a global vision for profit optimization. Industry 4.0 is mainly based on using all accessible information and data of systems and making decentralized decisions, but it also involves a global vision and a systemic approach to global profit optimization. However, achieving these objectives takes a very long time, and the challenges are numerous. As with all projects, for a transformation project to succeed, it is very important to define the transition phase and the way to change and introduce these new principles. This paper presents part of our research project, in collaboration with the Fiat Powertrain Technologies company, concerning the transformation of their production system toward the factory of the future. We highlight the design principles of I4.0 and the potential of the WCM system for transformation and achieving development of the characteristics of I4.0. We focus on five of the principal technical pillars of WCM and the steps in their development, and present some modifications in adoption of the design principles of I4.0. An example of change in the professional maintenance pillar of WCM is also presented.