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Faced with one of the greatest challenges of humanity – climate change – the European Union has set out a strategy to achieve climate neutrality by 2050 as part of the European Green Deal. To date, extensive research has been conducted on the CO2 life cycle analysis of mobile propulsion systems. However, achieving absolute net-zero CO2 emissions requires the adjustment of the relevant key performance indicators for the development of mobile propulsion systems. In this context, research is presented that examines the ecological and economic sustainability impacts of a hydrogen-fueled mild hybrid vehicle, a hydrogen-fueled 48V hybrid vehicle, a methanol-fueled 400V hybrid vehicle, a methanol-to-gasoline-fueled plug-in hybrid vehicle, a battery electric vehicle, and a fuel cell electric vehicle. For this purpose, a combined Life-Cycle Assessment (LCA) and Life-Cycle Cost Assessment was performed for the different propulsion concepts.

As the market for electric vehicles grows, so does the demand for appropriate charging infrastructure. The availability of sufficient charging points is essential to increase public acceptance of electric vehicles and to avoid the so-called “charging anxiety”. However, the charging stations currently installed may not be able to meet the full charging demand, especially in areas where there is a general lack of grid infrastructure, or where the fluctuating nature of charging demand requires flexible, high-power charging solutions that do not require expensive grid extensions. In such cases, the use of mobile charging stations provides a good opportunity to complement the existing charging network. This paper presents a prototype of a mobile charging solution that is being developed as part of an ongoing research project, and discusses different use cases.

Noise, vibration and harshness (NVH) is one of the most important performance evaluation aspect of electric motors. Among the different causes of the NVH issues of electrical drives, the high-frequency spatial and temporal harmonics of the electrical drive system is of great importance. To reduce the tonal noise of the electric motors, harmonic injection methods can be applied. However, a lot of the existing related work focuses more on improving the optimization process of the parameter settings of the injected current/flux/voltage, which are usually limited to some specific working conditions. The applicability and effectivity of the algorithm to the whole frequency/speed range are not investigated. In this paper, a multi-domain pipeline of harmonic injection controller design for a permanent magnet synchronous motor (PMSM) is proposed.

The European Commission is going to publish the new Euro7 standard shortly, with the target of reducing the impact on pollutant emissions due to transportation systems. Besides forcing internal combustion engines to operate cleaner in a wider range of operating conditions, the incoming regulation will point out the role of On-Board Monitoring (OBM) as a key enabler to ensure limited emissions over the whole vehicle lifetime, necessarily taking into account the natural aging of involved systems and possible electronic/mechanical faults and malfunctions. In this scenario, this work aims to study the potential of data-driven approaches in detecting emission-relevant engine faults, supporting standard On-Board Diagnostics (OBD) in pinpointing faulty components, which is part of the main challenges introduced by Euro7 OBM requirements.

Prevailing automotive development focus shifts towards passenger-centric development of vehicle systems. Comparative to autonomous driving development, the challenge evolves to describe all relevant driving situations with the necessary information and context to be able to develop and optimize vehicle systems to actual driving situations. The situational description or scenario, i.e., context or ambiance in which a vehicle is located, represents a fundamental factor in consideration of system behavior and respective system optimization opportunities. The challenge to solve the respective automotive engineering problems for nonlinear multidimensional parameter spaces or mixed integer classification problems is to describe and limit the possible solution space by suitable methodologies. Conventional methods prove inadequate solution as they can only be applied with significant financial resources and engineering time efforts, as known by autonomous driving system development.

Plug-In Hybrid Vehicles (PHEV) have been of significant importance recently to comply with future CO2 and pollutant emissions limit. However, performance of these vehicles is closely related to the energy management strategy (EMS) used to ensure minimum fuel consumption and maximize electric driving range. While conventional EMS concepts are developed to operate in wide range of scenarios, this approach could potentially compromise the fuel consumption benefit due to the omission of route and traffic information. With the advancements in the availability of real-time traffic, navigation and driving route information, the EMS can be further optimized to extract the complete potential of a PHEV. In this context, this paper presents application of predictive energy management (PEM) functionalities combined with information such as live traffic data to reduce the fuel consumption for a P1/P3 configuration PHEV vehicle.

Gasoline particulate filters (GPF) have become a standard aftertreatment component in Europe, China, and since recently, India, where particulate emissions are based on a particle number (PN) standard. The anticipated evolution of regulations in these regions towards future EU7, CN7, and BS7 standards further enhances the needs with respect to the filtration capabilities of the GPFs used. Emission performance has to be met over a broader range in particle size, counting particles down to 10nm, and over a broader range of boundary conditions. The requirements with respect to pressure drop, aiming for as low as possible, and durability remain similar or are also enhanced further. To address these future needs new filter technologies have been developed. New technologies for uncatalyzed GPF applications have been introduced in our previous publications.

The ever-tightening regulation norms across the world emphasize the magnitude of the air pollution problem. The decision to leapfrog from BS4 to BS6 – with further reduction in emission limits -showed India’s commitment to clean up its atmosphere. The overall cycle emissions were reduced significantly to meet BS6 targets [1]. However, the introduction of RDE norms in BS6.2 [1] demanded further reduction in emissions under real time operating conditions – start-stop, hard acceleration, idling, cold start – which was possible only through strategies that demanded a cost effective yet robust solutions. The first few seconds of the engine operation after start contribute significantly to the cycle gaseous emissions. This is because the thermal inertia of the catalytic converter restricts the rate at which temperature of the catalyst increases and achieves the desired “light-off” temperature.

India is the world’s largest two-wheeler (2Wh) market. With the proportion of its middle class rapidly rising, 2Wh sales and the resulting emissions, are expected to grow exponentially. The decision to leap-frog from BSIV to BSVI emission norms shows India’s commitment to clean up its atmosphere. As of now, the regulation mandates Gaseous Pollutant (CO, HC, NOx) emission limits for all 2Whs and a particulate limit (PM & PN) for 2Whs powered by Direct Injection (DI) engines. Most of the 2Whs manufactured in India are powered by gasoline engines using the Port Fuel Injection (PFI) technology, and hence by definition particulate emission limits do not apply to them. Particulates when inhaled - especially of the ultrafine sizes capable of entering the blood stream - pose a serious health risk. This was the primary motivation to investigate the particulate emission levels of the 2Whs, which as on date, do not come under the purview of BSVI regulation.

Pre-ignition in a boosted spark-ignition engine can be triggered by several mechanisms, including oil-fuel droplets, deposits, overheated engine components and gas-phase autoignition of the fuel-air mixture. A high pre-ignition resistance of the fuel used mitigates the risk of engine damage, since pre-ignition can evolve into super-knock. This paper presents the pre-ignition propensities of 11 RON 89-100+ gasoline fuel blends in a single-cylinder research engine. Albeit the addition of two high-octane components (methanol and reformate) to a toluene primary reference fuel improved the pre-ignition resistance, one high-RON fuel experienced runaway pre-ignition at relatively low boost pressure levels. A comparison of RON 96 blends showed that the fuel composition can affect pre-ignition resistance at constant RON.

The study was aimed at assessing the impact of fuel quality on the PN10 and PN23 emissions. A total of 6 fuels having different level of ethanol, renewable components, additives, and aromatic hydrocarbons were tested on the test vehicle. In the first phase of the study, the emission tests were conducted removing the GPF present in the original aftertreatment system to measure the direct impact of different fuels on the tailpipe particle emissions. The emission results showed that heavy aromatics components lead to a significant increase in particle emissions while the fuel with renewable components and E20 emit less PN comparing to the E10 reference fuel. However, those fuel impacts became very small with a GPF present due to a high filtration efficiency independent of fuel type.

One of the main challenges in internal combustion engine design is the simultaneous reduction of all engine pollutants like carbon monoxide (CO), total unburned hydrocarbons (THC), nitrogen oxides (NOx), and soot. Low-temperature combustion (LTC) concepts for compression ignition (CI) engines, e.g., premixed charged compression ignition (PCCI), make use of pre-injections to create a partially homogenous mixture and achieve an emission reduction. However, they present challenges in the combustion control, with the usage of in-cylinder pressure sensors as feedback signal is insufficient to control heat release and pollutant emissions simultaneously. Thus, an additional sensor, such as an ion-current sensor, could provide further information on the combustion process and effectively enable clean and efficient PCCI operation.

Dual three-phase permanent magnet synchronous machines (DTP-PMSM) are becoming increasingly popular in automotive electric powertrains due to their reduced phase currents and fault tolerance. The unique advantages of specific phase shift angles (such as 0°, 30°, 60°, etc.) between dual three-phase windings have been extensively studied. In this paper, the current and torque harmonics induced by the inverter are analyzed and the corresponding harmonics suppression strategy are proposed for a DTP-PMSM with different phase shift angles. In addition, this paper analyzes the effect of the phase shift angle between the dual three-phase windings on the torque ripple and phase losses, and proposes a novel optimal phase shift angle 80°. First, a mathematical vector space decomposition (VSD) model for a DTP-PMSM with arbitrary phase shift angles is derived.

The heavy duty (HD) Eu VII regulations, going into effect starting 2027, has aggressive particle number (PN) emissions limits under extended operating conditions compared to existing Eu VI framework. In addition to the proposed hot-start PN limit of 2.0E+11 #/kWh, which is a >65% reduction vs. Eu VI E, the particle size cut-off is being extended from 23nm+ to 10nm+ while also including nearly all field operating conditions such as regeneration events, wider ambient boundaries etc. The tighter limits coupled with a work-based window approach to evaluate emissions is driving the need for the next generation of ultra-high filtration efficiency (FE), diesel particulate filter (DPF) technologies. The current study evaluates the FE performance of different DPF solutions under development, over a range of challenging on-road conditions characterized by frequent high temperature events which are not actively triggered.

Sub-23nm particles emission from the light-duty vehicle is widely discussed now and possible to be counted into the next stage emission legislation, such as Euro7. In this article, 16 China6 gasoline vehicles were tested over the WLTC and two surrogate RDE lab cycles for particulate number (PN) emission, the difference between PN23 (particle size >23nm) and PN10 (particle size>10nm) emission was analyzed. Testing results showed that the average PN10 emission increased 59% compared to PN23, which will bring great challenges for those vehicles to meet the future regulation requirement if sub-23nm particle is counted. The sub-23nm particles emission was proportional to the PN23 particles emission and generated mostly from the cold start or the transient engine conditions with rich combustion. Compared to the proposal of Euro 7, PN10 emission from some tested vehicles will need further two orders of magnitude reduction.

As the official proposal for emission regulation Euro 7 has been released by European Commission, PN above 10nm is taken into consideration for the ultrafine particulate emissions control. The challenges of GPF filtration efficiency emerge for the light-duty manufactures to meet the future emission standards. In the present study, a China 6 compliant vehicle was tested to reveal its performance over the China 6 standards and potential to meet the upcoming Euro 7. Three GPF product types (Gen 1, Gen 2, and concept Gen 3) were mounted to the tested vehicle. WLTC tests were conducted on chassis dynamometer in laboratory as well as a self-designed aggressive cycle (“Base Cycle”) tests. To explore the GPFs performance for PN emissions above 10nm against the proposed limit 6.0E11 #/km, PN emission above 10nm were measured in our laboratory tests for both engine out and tailpipe as well as the PN emission above 23nm.

Modern automotive development evolves beyond artificial intelligence for highly automated driving, and toward an interconnected manifold of data-driven development processes. Widely used analytical system modelling struggles with rising system complexity, invoking approaches through data-driven system models. We consider these as key enablers for further improvements in accuracy and development efficiency. However, literature and industry have yet to thoroughly discuss the relevance and methods along the vehicle development cycle. We emphasize the importance of data-driven system models in their distinct types and applications along the developing process, from pre-development to fleet operation. Data-driven models have proven in other works to be fast approximators, of high accuracy and adaptive, in contrast to physics-based analytical approaches across domains.

Simultaneous reduction of engine pollutants (e.g., CO, THC, NOx, and soot) is one of the main challenges in the development of new combustion systems. Low-temperature combustion (LTC) concepts in compression ignition (CI) engines like premixed charged compression ignition (PCCI) make use of pre-injections to create a partly homogenous mixture. In the PCCI combustion regime, a direct correlation between injection and pollutant formation is no longer present because of long ignition delay times. In LTC combustion systems, the in-cylinder pressure sensor is normally used to help the combustion control. However, to allow the control of PCCI engines, new sensor concepts are investigated to obtain additional information about the PCCI combustion for advanced controller structures. In LTC combustion systems like gasoline-controlled autoignition (GCAI) concepts, the application of ion current sensors enables additional monitoring of the combustion process with real-time capability.

Renewable fuels, such as bio- and e-fuels, are of great interest for the defossilization of the transport sector. Among these fuels, methanol represents a promising candidate for emission reduction and efficiency increase due to its very high knock resistance and its production pathway as e-fuel. In general, reliable simulation tools are mandatory for evaluating a specific fuel potential and optimizing combustion systems. In this work, a previously presented methodology (Esposito et al., Energies, 2020) has been refined and applied to a different engine and different fuels. Experimental data measured with a single cylinder engine (SCE) are used to validate RANS 3D-CFD simulations of gaseous engine-out emissions. The RANS 3D-CFD model has been used for operation with a toluene reference fuel (TRF) gasoline surrogate and methanol. Varying operating conditions with exhaust gas recirculation (EGR) and air dilution are considered for the two fuels.

China 6 (CN6) emission legislation for light duty vehicles was published in 2016, which introduced real driving emissions (RDE) requirements for new type-approval content. Nitrogen oxides (NOx) and particle number (PN) of RDE test are required to be monitored and reported from July 2020 in CN6a phase, fulfilled from July 2023 in CN6b phase. To meet the PN limitation of CN6 RDE, the optimized engine combustion and advanced emission control system like gasoline particle filter (GPF) are encouraged. Compared to traditional vehicle platform emission compliance which could be done in lab, much more vehicle development and validation efforts are expected on the open road for RDE compliance. High cost and complexity are expected to conduct a complete validation test matrix covering all the RDE critical boundary conditions on the open road.