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The paper presents a robust adaptive control technique for precise regulation of a port fuel injection + direct injection (PFI+DI) system, a dual fuel injection configuration adopted in modern gasoline engines to boost performance, fuel efficiency, and emission reduction. Addressing parametric uncertainties on the actuators, inherent in complex fuel injection systems, the proposed approach utilizes an indirect model reference adaptive control scheme. To accommodate the increased control complexity in PFI+DI and the presence of additional uncertainties, a nonlinear plant model is employed, incorporating dynamics of the exhaust burned gas fraction. The primary objective is to optimize engine performance while minimizing fuel consumption and emissions in the presence of uncertainties. Stability and tracking performance of the adaptive controller are evaluated to ensure safe and reliable system operation under various conditions.

Planning for charging in transport missions is vital when commercial long-haul vehicles are to be electrified. In this planning, accurate range prediction is essential so the trucks reach their destinations as planned. The rolling resistance significantly influences truck energy consumption, often considered a simple constant or a function of vehicle speed only. This is, however, a gross simplification, especially as the tire temperature has a significant impact. At 80 km/h, a cold tire can have three times higher rolling resistance than a warm tire. A temperature-dependent rolling resistance model is proposed. The model is based on thermal networks for the temperature at four places around the tire. The model is tuned and validated using rolling resistance, tire shoulder, and tire apex temperature measurements with a truck in a climate wind tunnel with ambient temperatures ranging from -30 to 25 °C at an 80 km/h constant speed.

Net-Zero emission ambitions coupled with availability of oxygenated fuels like ethanol encouraged the Government towards commercial implementation of fuels like E20. In this background, a study was taken up to assess the impact of alcohol blended fuels on performance and emission characteristics of a BS-VI complaint motorbike. A single cylinder, 113-cc spark ignition, ECU based electronic fuel injection motorbike was used for conducting tests. Pure gasoline (E0), 10% ethanol-gasoline (E10), 20% ethanol-gasoline (E20) and 15% methanol-gasoline (M15) blends meeting respective IS standards were used as test fuels. The oxygen content of E10, E20 and M15 fuels were 3.7%, 7.4% and 8.35% by weight respectively. Experiments were conducted following worldwide motorcycle test cycle (WMTC) as per AIS 137 standard and wide-open-throttle (WOT) test cycle, using chassis dynamometer.

The present study aims to determine the comparative performance evaluation in terms of fuel economy (kmpl) and wide open throttle (WOT) power derived from set of different blends of high octane gasoline fuel(s) i.e., Neat Gasoline (E0), E10 & E20 (With different dosages of additives) in high compression ratio (HCR) motorcycle on chassis dynamometer facility. With the Government of India focus on use of alcohol as co-blend of gasoline with the endeavour to save foreign exchange and also to reduce greenhouse gases (GHG) emissions. The commercially available blended fuels, E10 & E20, have high research octane number (RON, 92-100) and as per the available literature high RON fuel have the better anti-knocking tendencies thereby lead to higher fuel economy. There are various routes to formulate high octane fuel (refining technologies, additive approach & ethanol blending route) in the range of 92-100 octane number which are currently commercialized in Indian market.

Recently, as part of the effort to enhance fuel efficiency and reduce costs for eco-friendly vehicles, the R-gearless system has been implemented in the TMED (P)HEV system. Due to the removal of the reverse gear, a distinct backward driving method needs to be developed, allowing the Electronic Motor (e-Motor) system to facilitate backward movement in the TMED (P)HEV system. However, the capability of backward driving with the e-Motor is limited because of partial failure in the high-voltage system of an R-gearless system. Thus, we demonstrate that it is possible to improve backward driving problems by applying a new fail-safe strategy. In the event of a high-voltage battery system failure, backward driving can be achieved using the e-Motor with constant voltage control by the Hybrid Starter Generator (HSG), as proposed in this study.

In 2022 in the UK, the transport sector was the largest single contributing sector to greenhouse gas emissions, responsible 34% of all territorial carbon dioxide emissions [1]. In the UK there is growing uptake in zero emission powertrain technologies, with the most promising variants based on battery electric or hydrogen fuel cell electric configurations. Given the limited number of fuel cell electric buses currently in operation in Europe, vehicle models and simulations are one of the few methods available to estimate energy consumption and provide the necessary increased confidence in operating range. This paper investigates the impact of route characteristics, thermal demand and coefficient of performance of different heat source configurations on the operational energy consumption of fuel cell electric buses. Using a MATLAB/Simulink model, the total energy demand of a vehicle operating in different route/elevation profiles is considered.

Given the growing interest in improving the efficiency of the bus fleet in public transportation systems, this paper presents an analysis of the energy consumption of a battery electric bus. During the experimental campaign, a battery electric bus was loaded using sand payloads to simulate the passenger load on board and followed another bus during regular service. Data related to the energy consumed by various bus utilities were published on the vehicle’s CAN network using the FMS standard and sampled at a frequency of 1 Hz. The collected experimental data were initially analyzed on a daily basis and then on a per-route basis. The results reveal the breakdown of energy consumption among various utilities over the course of each day of the experiment, highlighting those responsible for the highest energy consumption.

In recent years, the burgeoning applications of hydrogen fuel cells have ignited a growing trend in their integration within the transportation sector, with a particular focus on their potential use in multi-rotor drones. The heightened mass-based energy density of fuel cells positions them as promising alternatives to current lithium battery-powered drones, especially as the demand for extended flight durations increases. This article undertakes a comprehensive exploration, comparing the performance of lithium batteries against air-cooled fuel cells, specifically within the context of multi-rotor drones with a 3.5kW power requirement. The study reveals that, for the specified power demand, air-cooled fuel cells outperform lithium batteries, establishing them as a more efficient solution.

The powertrain electrification is currently not only taking place in public road mobility vehicles, but is also making its way to the racetrack, where it’s driving innovation for developments that will later be used in series production vehicles. The current development focus for electric vehicles is the balance between driving power, range and weight, which is given even greater weighting in racing. To redefine the current limits, IAV developed a complete e-powertrain for a racing MX motorcycle and integrated it into a real drivable demonstrator bike. The unique selling point is the innovative direct phase-change cooling (PCC) of the three-phase e-motor and its power electronics, which enables significantly increased continuous power (Pe = 40 kW from 7,000 rpm to 9,000 rpm) without thermal power reduction. The drive unit is powered by a replaceable Lithium-Ion round cell battery (Ubat,max = 370V) with an energy storage capacity of Ebat = 5 kWh.

A 300 mile-range automotive battery pack is comprised of many individual cells connected in series/parallel to make up the required voltage, energy, and power. The cell groupings can take the form of parallel strings of series cell groups (S-P), series string of parallel cell groups (P-S), or a hybrid of the two. Though the different battery configurations deliver identical output voltage and energy, they exhibit varying cell level behaviors due to differing electrical structure, particularly when cell imbalance occurs. In this work, we explore the relative merits of various cell grouping configurations using a model-based approach. The emphasis of the study is to evaluate the impact of electrical variation between cell-to-cell, originating from cell manufacturing process variation, battery assembly (laser tab bonding) process variation or from normal operation, on the performance of the battery pack. A first-order equivalent circuit model is used to represent a lithium-ion cell.

The Battery Performance and Cost Model (BatPaC), developed by Argonne National Laboratory, is a versatile tool designed for lithium-ion battery (LIB) pack engineering. It accommodates user-defined specifications, generating detailed bill-of-materials calculations and insights into cell dimensions and pack characteristics. Pre-loaded with default data sets, BatPaC aids in estimating production costs for battery packs produced at scale (5 to 50 GWh annually). Acknowledging inherent uncertainties in parameters, the tool remains accessible and valuable for designers and engineers. BatPaC plays a crucial role in National Highway Transportation Traffic Safety Administration (NHTSA) regulatory assessments, providing estimated battery pack manufacturing costs and weight metrics for electric vehicles. Integrated with Argonne's Autonomie simulations, BatPaC streamlines large-scale processes, replacing traditional models with lookup tables.

In order to study the influence of engine silicone oil fan clutch on the performances of engine cooling system under different control strategies, a model of engine cooling system for light truck is established. The working characteristics of the silicone oil clutch and the measured performance parameters of the cooling system components are taken into account in our proposed model. Modeling methods for different silicone oil fan control strategies are also given. Using the established model, the performance parameters under different vehicle speeds, such as coolant temperature of engine outlet and power consumption of cooling fan, are calculated and analyzed. The in-suite measurement of the engine cooling system is carried out to get the temperatures of engine coolant inlet and outlet from engine ECU. The model is validated by the comparison between the calculation and the measured results.

To reduce the heating energy consumption of electric vehicles in winter, a switching control strategy for multiple heating modes formed by three heat sources, including air, motor waste heat, and positive temperature coefficient (PTC) heaters, is designed. Firstly, an integrated thermal management system (ITMS) simulation model for the heat pump air conditioning system, battery thermal management system, and motor thermal management system is established based on the AMESim software. Secondly, the influence of ambient temperature and motor outlet coolant temperature on the heating performance of three cabin heating modes is studied. Specifically, the three cabin heating modes include the pure motor waste heat source heat pump mode, the pure air-source heat pump mode, and the dual heat source heat pump mode with waste heat source and air source. Based on the analysis results, the opening and closing strategies for the three cabin heating modes are discussed.

The significance of thermal management performance in electric vehicles (EVs) has grown considerably, leading to increased complexity in thermal systems and a rapid rise in safety and quality-related concerns. The present real-vehicle-based development methods encounter several constraints in their approach when dealing with highly complex systems. Huge number of verification and validation work To overcome these limitations and enhance the thermal system development process, a novel virtual development environment established using the XiLS (X in the Loop Simulation) methodology. This XiLS methodology basically based on real-time coupling between physical thermal system hardware and analytical models for the other systems of vehicle. To control vehicle model and thermal system, various options were realized through hardware, software and model for VCU (Vehicle control unit) and TMS (Thermal management system) control unit.

The National Highway Traffic Safety Administration (NHTSA) plays a crucial role in guiding the formulation of Corporate Average Fuel Economy (CAFE) standards, and at the forefront of this regulatory process stands Argonne National Laboratory (Argonne). Argonne, a U.S. Department of Energy (DOE) research institution, has developed Autonomie—an advanced and comprehensive full-vehicle simulation tool that has solidified its status as an industry standard for evaluating vehicle performance, energy consumption, and the effectiveness of various technologies. Under the purview of an Inter-Agency Agreement (IAA), the DOE Argonne Site Office (ASO) and Argonne have assumed the responsibility of conducting full-vehicle simulations to support NHTSA's CAFE rulemaking initiatives. This paper introduces an innovative approach that hinges on a large-scale simulation process, encompassing standard regulatory driving cycles tailored to various vehicle classes and spanning diverse timeframes.

Rubber isolators are widely used under random vibrations. In order to predict their fatigue life, a study on the fatigue analysis methodology for rubber isolators is carried out in this paper. Firstly, taking a mount used for isolating air conditioning compressor vibrations as studying example, accelerations versus time of rubber isolator at both sides are acquired for a car under different running conditions. The acceleration in time domain is transformed to frequency domain using the Fourier transform, and the acceleration power spectral density (PSD) is the obtained. Using the PSD as input, fatigue test is carried for the rubber isolator in different temperature and constant humidity conditions. A finite element model of the rubber isolator using ABAQUS is established for estimating fatigue life, and model validity is verified through static characteristic testing. Dynamic responses of the rubber isolator at frequency domain are calculated if a unit load is applied.

Energy management of battery electric vehicle (BEV) is a very important and complex multi-system optimisation problem. The thermal energy management of a BEV plays a crucial role in consistent efficiency and performance of vehicle in all weather conditions. But in order to manage the thermal management, it requires a significant number of temperature sensors throughout the car including high voltage batteries, thus increasing the cost, complexity and weight of the car. Virtual sensors can replace physical sensors with a data-driven, physical relation-driven or machine learning-based prediction approach. This paper presents a framework for the development of a neural network virtual sensor using a thermal system hardware-in-the-loop test rig as the target system. The various neural network topologies, including RNN, LSTM, GRU, and CNN, are evaluated to determine the most effective approach.

The design of lightweight vehicle structures has become a common method for automotive manufacturers to increase fuel efficiency and decrease carbon emission of their products. By using aluminum instead of steel, manufacturers can reduce the weight of a vehicle while still maintaining the required strength and stiffness. Currently, Resistance Spot Welding (RSW) is used extensively to join steel body panels but presents challenges when applied to aluminum. When compared to steel, RSW of aluminum requires frequent electrode cleaning, higher energy usage, and more controlled welding parameters, which has driven up the cost of manufacturing. Due to the increased cost associated with RSW of aluminum, Refill Friction Stir Spot Welding (RFSSW) is being considered as an alternative to RSW for joining aluminum body panels. RFSSW consumes less energy, requires less maintenance, and produces more consistent welding in aluminum as compared to RSW.

The wear of the piston ring-cylinder liner system in gasoline engines is inevitable and significantly impacts fuel economy. Utilizing a custom-built linear reciprocating tribometer, this study assesses the wear resistance of newly developed engine cylinder coatings. The custom device offers a cost-effective means for tribological evaluation, optimizing coating process parameters with precise control over critical operational factors such as normal load and sliding frequency. Unlike conventional commercial tribometers, it ensures a more accurate simulation of the engine cylinder system. However, existing research lacks a comprehensive comparative analysis and procedure to establish precision limits for such modified devices. This study evaluates the custom tribometer's repeatability compared to a commercial wear-testing instrument, confirming its potential as a valuable tool for advanced wear testing on engine cylinder samples.

As part of Nissan’s strategy of electrification and the shift to smart technologies, our powertrain department has two main pillars: zero emissions and ICE Evolution. As a core unit of ICE Evolution, we have developed a brand new 3.5L V6 Twin turbocharged gasoline engine for Nissan’s next generation full-size flagship SUV to deliver luxury and toughness at the highest level. This brand-new engine will be applied to vehicles in all corners of the world and must have strong performance in every corner. More specifically, it has to meet the latest emissions and fuel efficiency regulations, have strong power performance beyond expectation, and provide reliable drivability on rough roads and deserts. To achieve these requirements, the new engine is incorporating many cutting-edge technologies.