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In this paper, a control strategy for state of charge (SOC) allocation using navigation data for Hybrid Electric Vehicle (HEV) propulsion systems is proposed. This algorithm dynamically defines and adjusts a SOC target as a function of distance travelled on-line, thereby enabling proactive management of the energy store in the battery. The proposed approach incorporates variances in road resistance and adheres to geolocation constraints, including ultra-low emission zones (uLEZ). The anticipated advantages are particularly pronounced during scenarios involving extensive medium-to-long journeys characterized by abrupt topological changes or the necessity for exclusive electric vehicle (EV) mode operation. This novel solution stands to significantly enhance both drivability and fuel economy outcomes.

During driving conditions, when it is needed to transition from Electric Vehicle (EV) to Hybrid Vehicle operation, synchronization of the engine with the shaft and transmission is essential to enable clutch engagement and, subsequently, providing engine power to the wheels. Challenges arise when the engine must generate power to move itself and cannot rely on electric motors for precision. Cost-effective hybrid vehicle propulsion architectures which utilize small 12V belt-starter generators (BSGs) to initiate engine activation are inherently affected. In these situations, a speed profile that balance rapid response and control effort while considering system limitations to mitigate undesirable overshoots and delays, is required. This paper presents a Linear Quadratic Integral (LQI) approach to formulate a speed reference profile that ensures optimal engine behavior.

To satisfy the stringent regulations for exhaust gas emissions from gasoline-powered vehicles, large amounts of Rh and Pd have often been employed in three-way catalysts (TWCs) as the main active components. On the other hand, Pt-based TWCs are not often used in gasoline vehicles because Pt is readily sintered by its exhaust gases at approximately 1000 °C [1, 2]. In general, Pt-based TWCs must be located away from large thermal loads to maintain the active sites for gas purification. Based on this background, we previously reported that employing a small amount of CeO2 calcined at 1000 °C (cal-CeO2) in Pt-based TWCs was one of the most effective approaches for improving the catalytic activity without increasing the amount of Rh and Pd [3]. The effect of cal-CeO2 was attributed to the higher redox performance and Pt dispersion derived from the strong interactions between Ce and Pt.

Amid rising demands for fuel efficiency and emissions reduction, enhancing the thermal efficiency of gasoline engines has become imperative, which requires higher efficiency combustion strategies and integrated optimized design to maximize the work output from fuel. In gasoline engine, both increasing the compression ratio and using lean burn mode improve the ratio of useful work output to the energy input effectively, which resulting in higher thermal efficiency. Although there is limited scope for increasing the compression ratio due to the higher sensitivity to knocking, especially under stoichiometric conditions, reduced sensitivity could be got with leaner mixture fill into cylinder, which can further increase the specific heat ratio and thermal efficiency.

The need for carbon-neutral transportation solutions has never been more pronounced. With the continually expanding volume of goods in transit, innovative and dependable powertrain concepts for freight transport are imperative. The green hydrogen-powered internal combustion engine presents an appealing option for integrating a reliable, non-fossil fuel powertrain into commercial vehicles. This study focuses on the adaptation of a single-cylinder diesel engine with a displacement of 2116 cm3 to facilitate hydrogen combustion. The engine, characterized by low levels of swirl and tumble, underwent modifications, including the integration of a conventional central spark plug, a custom-designed piston featuring a reduced compression ratio of 9.5, and a low-pressure hydrogen direct injection system. Operating the injection system at 25 bar hydrogen pressure, the resulting jet profiles were varied by employing jet forming caps affixed directly to the injector nozzle.

In order to improve the fuel economy for future high-efficiency spark ignition engines, the applications of advanced combustion strategies are considered to be beneficial with an overall lean and/or exhaust gas recirculation diluted cylinder charge. Stronger and more reliable ignition sources become more favorable under extreme lean/EGR conditions. Existing research indicates that the frequency of plasma restrikes increases with increased flow velocity and decreased discharge current level, and a higher discharge current can reduce the gap resistance and maintain the stretched plasma for a longer duration under flow conditions. An in-house developed current boost control system provides flexible control of the discharge current level and discharge duration. The current boost ignition system is based on a multi-coil system with a discharge current level of 180mA.

Ultra-lean combustion of GDI engine could achieve higher thermal efficiency and lower NOx emissions, but it also faces challenges such as ignition difficulties and low-speed flame propagation. In this paper, the sparked-spray is proposed as a novel ignition method, which employs the spark to ignite the fuel spray by the cooperative timing control of in-cylinder fuel injection and spark ignition and form a jet flame. Then the jet flame fronts propagate in the ultra-lean premixed mixture in the cylinder. This combustion mode is named Sparked-Spray Induced Combustion (SSIC) in this paper. Based on a 3-cylinder 1.0L GDI engine, a 3D simulation model is established in the CONVERGE to study the effects of ignition strategy, compression ratio, and injection timing on SSIC with a global equivalence ratio of 0.50. The results show it is easier to form the jet flame when sparking at the spray front because the fuel has better atomization and lower turbulent kinetic energy at the spray front.

As a novel ignition technology, pre-chamber ignition can enhance ignition energy, promote flame propagation, and augment turbulence. However, this technology undoubtedly faces challenges, particularly in the context of emission regulations. Of this study, the transient characteristics of combustion and emissions in a hybrid electric vehicle (HEV) gasoline engine with active pre-chamber ignition (PCI) under the first combustion cycle of quick start are focused. The results demonstrate that the PCI engine is available on the first cycle for lean combustion, such as lambda 1.6 to 2.0, and exhibit particle number (PN) below 7×107 N/mL at the first cycle. These particles are predominantly composed of nucleation mode (NM, <50 nm) particles, with minimal accumulation mode (AM, >50 nm) particles.

The growing demand to lower greenhouse gas emissions and transition from fossil fuels, has put methanol in the spotlight. Methanol can be produced from renewable sources and has the property of burning almost soot-free in compression ignition (CI) engines. Consequently, there has been a notable increase in research and development activities directed towards exploring methanol as a viable substitute for diesel fuel in CI engines. The challenge with methanol lies in the fact that it is difficult to ignite through compression alone, particularly in low-load and cold start conditions. This difficulty arises from methanol's high octane number, relatively low heating value, and high heat of vaporization, collectively demanding a considerable amount of heat for methanol to ignite through compression. Previous studies have addressed the use of a pilot injection in conjunction with a larger main injection to lower the required intake air temperature for methanol to combust at low loads.

In the context of carbon neutrality, ammonia is considered a zero-carbon fuel with potential applications in the transportation sector. However, its high ignition energy, low flame speed, and high natural temperature, indicative of low reactivity, make it challenging to be applied as a sole fuel in engines. In such a scenario, the use of another zero-carbon and highly reactive fuel, hydrogen, becomes necessary to enhance the combustion of ammonia. Furthermore, jet ignition, a method known for improving engine combustion performance, may also hold potential for enhancing the combustion performance of ammonia engines. To explore the applicability of jet ignition in engines, this study conducted experimental research on a single-cylinder engine. Two ignition methods were employed: passive jet ignition of premixed ammonia-hydrogen at a compression ratio of 11.5, and active jet ignition of pure ammonia using hydrogen jet flame at a compression ratio of 17.3.

This study focuses on evaluation of various fuels within a conventional gasoline internal combustion engine (ICE) vehicle and the implementation of advanced emissions reduction technology. It shows the robustness of the implemented technology packages for achieving ultra-low tailpipe emissions to different market fuels and demonstrates the potential of future GHG neutral powertrains enabled by drop-in lower carbon fuels (LCF). An ultra-low emission (ULE) sedan vehicle was set up using state-of-the-art engine technology, with advanced vehicle control and exhaust gas aftertreatment system including a prototype rapid catalyst heating (RCH) unit. Currently regulated criteria pollutant emission species were measured at both engine-out and tailpipe locations. Vehicle was run on three different drive cycles at the chassis dynamometer: two standard cycles (WLTC and TfL) at 20°C, and a real driving emission (RDE) cycle at -7°C.

Recent legislation banning the sale of new petrol and diesel vehicles in Europe from 2035 has shifted the focus of internal combustion engine research towards alternative fuels with net zero tailpipe emissions such as hydrogen. Research regarding hydrogen as a fuel is particularly pertinent to the so-called ‘hard-to-electrify’ propulsion applications, requiring a combination of large range, fast refuelling times or high-load duty cycles. The virtual design, development, and optimisation of hydrogen internal combustion engines has resulted in the necessity for accurate predictive modelling of the hydrogen combustion and autoignition processes. Typically, the models for these processes rely respectively on laminar flame speed datasets to calculate the rate of fuel burn as well as ignition delay time datasets to estimate autoignition timing. These datasets are generated using chemical kinetic mechanisms available in the literature.

Plug-in hybrid electric vehicles (PHEVs) have the capability to drive an appreciable fraction of their miles travelled on electric power from the grid, similar to battery-only electric vehicles (BEVs). However, unlike BEVs which cannot drive unless charged, PHEVs can automatically switch to gasoline power and operate similar to a regular (non-plug-in) hybrid electric vehicle (HEV). Though operating similar to HEV is already beneficial in terms of fuel economy, greenhouse gas (GHG) emissions and criteria pollutants compared to conventional internal combustion engine (ICE) vehicles, much of the attractiveness and allure of PHEVs comes from their capability to drive “almost like a BEV”, but without range anxiety about running out of battery charge.

An analytic first-order fuel consumption model is developed for FWD 2-motor HEV vehicles which on average achieve 36% EPA Combined efficiency. The premise of this paper is that this is primarily the result of new functionality specific to HEV. Detailed benchmarking data show that in such an HEV the engine not only provides traction power but simultaneously charges the battery. This combined operation of engine and electric powertrain is unique to HEV and is studied using their linear transfer functions. Charging by the engine enables extended electric driving at low traction power, which reduces engine running time and the associated overhead. The analysis predicts an engine duty cycle proportional to the traction power and inversely proportional to the engine output power: the electric driving is limited by the engine’s ability to deliver the required traction work.

As electrification of powertrains is progressing, diversification of hybrid powertrains increases. This generally imposes the challenge for a supervisory controller of how to optimally control the torque of the electric machine(s). Architectures, which have at least one belt driven electric machine, are an essential part of the portfolio. This paper describes a strategy on how to include the losses of the belt device in the determination of optimal electric machine torque command. It first depicts a physics-based method for controlling optimal electric machine torque command for systems without a belt connected electric machine. This method considers the constraints of the electric machine(s) as well as the power limitations from the electric devices, which supply power to the motors.

Radical greenhouse gases emissions reduction necessity is bringing deep evolution in mobility behaviors and is the core reason for a significant diversification of automotive powertrain technologies, making it more and more complex for customers to find the best suited technology. This paper proposes a customer-oriented approach that translates needs into technical requirements that can be used as choice guidelines. First, customers answer a small survey on their driving habits and the class of car they want. Real life driving cycles are then recorded, and Simulink simulations, based on lowest equivalent consumption calculations, allow to identify and size an ideal powertrain that can then become a benchmark for vehicle final selection.

This paper discusses the dependency between powertrain design and automated driving. The research questions are to what extent automated driving influences the powertrain design and how energy and fuel consumption is affected in comparison to customer driving. For this investigation a concept study is carried out for a D-segment vehicle and multiple powertrain topologies, ranging from non-electrified to plug-in hybrids and battery electric vehicles. In order to answer the research questions, the used development process and the methods for optimizing the drive system are presented accordingly, taking into account all vehicle requirements, the drive system and the components and their interactions with each other. This work focuses on two automated driving functions developed at the Institute of Automotive Engineering of the Technische Universität Braunschweig. The functions are an “automated valet parking” and a “highway pilot”.

Reference velocity (i.e. the absolute velocity of vehicle center of gravity) is a key parameter for vehicle stability control functions as well as for the powertrain control functions of hybrid electric vehicle (HEV). Most reference velocity estimation methods employ the vehicle kinematic and tire dynamic equations to construct high order linear or nonlinear model with a set of parameters and sensor measurements. When using those models, delicate algorithm should be designed to prevent the estimates from deviating along with the increase of nonlinearity, modeling error and noise that introduced by high order, parameter approximation, and sensor measurements, respectively. Alternatively, to improve the function robustness and calibration convenience, a straightforward online estimation method is developed in the paper by using a second-order powertrain dynamic model that only need a small set of vehicle parameters and sensor values.

This paper presents a feedback control strategy to minimize noise during dog clutch engagement in a hybrid transmission. The hybrid transmission contains an internal combustion engine(ICE) and 2 electric motors in P1 and P3 configurations. For efficiency during driving, at high vehicle speeds ICE is connected to wheels, via the dog clutch, hence shifting the vehicle from series to parallel hybrid mode. It is shown by experimental results that if the speed difference between the two sides of the dog clutch is below a certain level the engagement will be without clonk noise. In this paper the designed state feedback Linear Quadratic Integral (LQI) control provides the synchronization torque request to the P1 motor, hence matching the speed of one side of dog clutch with the other under the disturbance from combustion torque of the engine.

In torque converters, a lockup clutch is used for direct torque transfer from the engine to the gearbox. Nowadays, earlier lockup engagement is necessary to reduce fuel consumption. It introduces noise and vibration issues in the transmission that are solved by clutch slipping. However, the clutch experiences much heat because of earlier engagement, which needs to be adequately dissipated by ATF oil. To overcome this issue, multi-plate clutches are commonly used for efficient torque transfer and clutch slipping. On the other side, packaging space for torque converters is reducing at the vehicle level, especially in hybrid vehicles, which reduces the efficient cooling of clutches. So, accurate modeling of clutch slipping is necessary to improve the clutch performance and durability of the product. Clutch slipping is a transient phenomenon that involves conjugate heat transfer and rotational flow modeling. There are different ways to model clutch slipping in CFD simulations.