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Electric vehicles (EVs) are becoming increasingly recognized as an effective solution in the battle against climate change and reducing greenhouse gas emissions. Lithium-ion batteries have become the standard for energy storage in the automobile industry, widely used in EVs due to their superior characteristics compared to other batteries. The growing popularity of the Vehicle-to-grid (V2G) concept can be attributed to its surplus energy storage capacity, positive environmental impact, and the reliability and stability of the power grid. However, the increased utilization of the battery through these integrations can result in faster degradation and the need for replacement. As batteries are one of the most expensive components of EVs, the decision to deploy an EV in V2G operations may be uncertain due to the concerns of battery degradation from the owner’s perspective.

Improving passenger safety inside vehicle cabins requires continuously monitoring vehicle seat occupancy statuses. Monitoring a vehicle seat’s occupancy status includes detecting if the seat is occupied and classifying the seat’s occupancy type. This paper introduces an innovative non-intrusive technique that employs capacitive sensing and an occupancy classifier to monitor a vehicle seat’s occupancy status. Capacitive sensing is facilitated by a meticulously constructed capacitance-sensing mat that easily integrates with any vehicle seat. When a passenger or an inanimate object occupies a vehicle seat equipped with the mat, they will induce variations in the mat’s internal capacitances. The variations are, in turn, represented pictorially as grayscale capacitance-sensing images (CSI), which yield the feature vectors the classifier requires to classify the seat’s occupancy type.

In the ever-evolving landscape of automotive technology, the need for robust security measures and dependable vehicle performance has become paramount with connected vehicles and autonomous driving. The Unified Diagnostic Services (UDS) protocol is the diagnostic communication layer between various vehicle components which serves as a critical interface for vehicle servicing and for software updates. Fuzz testing is a dynamic software testing technique that involves the barrage of unexpected and invalid inputs to uncover vulnerabilities and erratic behavior. This paper presents the implementation of fuzz testing methodologies on the UDS layer, revealing the potential vulnerabilities that could be exploited by malicious entities. By employing both open-source and commercial fuzzing tools and techniques, this paper simulates real-world scenarios to assess the UDS layer’s resilience against anomalous data inputs.

Reducing criteria pollutants while reducing greenhouse gases is an active area of research for commercial on-road vehicles as well as for off-road machines. The heavy duty on-road sector has moved to reducing NOx by 82.5% compared to 2010 regulations while increasing the engine useful life from 435,000 to 650,000 miles by 2027 in the United States (US). An additional certification cycle, the Low Load Cycle (LLC), has been added focusing on part load operation having tight NOx emissions levels. In addition to NOx, the total CO2 emissions from the vehicle will also be reduced for various model years. The off-road market is following with a 90% NOx reduction target compared to Tier 4 Final for 130-560 kW engines along with greenhouse gas targets that are still being established. The off-road market will also need to certify with a Low Load Application Cycle (LLAC), a version of which was proposed for evaluation in 2021.

Thermal barrier coatings (TBCs) have long been studied as a potential pathway to achieve higher thermal efficiency in spark ignition engines. Researchers have studied coatings with different thicknesses and thermophysical properties to counteract the volumetric efficiency penalty associated with TBCs in spark ignition. To achieve an efficiency benefit with minimal charge heating during the intake stroke, low thermal inertia coatings characterized by their larger temperature swings are required. To study the impact of low thermal inertia coatings in spark ignition, coatings were applied to the cylinder head, piston crown, intake and exhaust valve faces, and intake and exhaust valve backsides. Tier III EEE E10 certification gasoline was used to keep the experiments relevant to the present on-road vehicles. This study is aimed at analyzing durability of the coatings as well as efficiency and emissions improvements.

Rotary valve technology can provide increased flow area and higher discharge coefficients than conventional poppet valves for internal combustion engines. This increase in intake charging efficiency can improve the power density of four-stroke internal combustion engines, particularly at high engine speeds, where flow is choked through conventional poppet valves. In this work, the valvetrain of a light duty single cylinder spark ignition engine was replaced with a rotary valve train. The impact of this valvetrain conversion on performance and emissions was evaluated by comparing spark timing sweeps with lambda ranging from 0.8 to 1.1 at wide open throttle. The results indicated that the rotary valvetrain increased the amount of air trapped at intake valve closing and resulted in a significantly faster burn duration than the conventional valvetrain.

Catalytic converters, which are commonly used for after-treatment in SI engines, exhibit poor performance at lower temperatures. This is one of the main reasons that tailpipe emissions drastically increase during cold-start periods. Thermal inertia of turbocharger casing prolongs the catalyst warm-up time. Exhaust enthalpy management becomes crucial for a turbocharged direct injection spark ignition (DISI) engine during cold-start periods to quickly heat the catalyst and minimize cold-start emissions. Thermal barrier coatings (TBCs), because of their low thermal inertia, reach higher surface temperatures faster than metal walls, thereby blocking heat transfer and saving enthalpy for the catalyst. The TBCs applied on surfaces that exchange heat with exhaust gases can increase the enthalpy available for the catalyst warm-up.

The application of power electronic converters (PEC) in electric vehicles (EVs) has increased immensely as they provide enhanced controllability and flexibility to these vehicles. Accordingly, the interest in developing innovative and sustainable technologies to ensure safe and reliable operation of PECs has also risen. One of the most difficult challenges experienced during the development of reliable PECs is the design of proper thermal management systems for controlling the junction temperature and reducing the thermal cycling of power semiconductors. The addition of Active Thermal Control (ATC) can mitigate these concerns. Moreover, the performance of the thermal management system can be enhanced further by the integration of active cooling methods. An active cooling system consumes external energy for circulating cooling air or liquid within the PECs.

Drive cycles are a core piece of vehicle development testing methodology. The control and calibration of the vehicle is often tuned over drive cycles as they are the best representation of the real-world driving the vehicle will see during deployment. To obtain general performance numerous drive cycles must be generated to ensure final control and calibration avoids overfitting to the specifics of a single drive cycle. When real-world driving cycles are difficult to acquire methods can be used to create statistically similar synthetic drive cycles to avoid the overfitting problem. This subject has been well addressed within the passenger vehicle domain but must be expanded upon for utilization with tracked off-road vehicles. Development of hybrid tracked vehicles has increased this need further. This study shows that turning dynamics have significant influence on the vehicle power demand and on the power demand on each individual track.

In the United States and worldwide, 38,824 and 1.35 million people were killed in vehicle crashes during 2020. These statistics are tragic and indicative of an on-going public health crisis centered on automobiles and other ground transportation solutions. Although the long-term US vehicle fatality rate is slowly declining, it continues to be elevated compared to European countries. The introduction of vehicle safety systems and re-designed roadways has improved survivability and driving environment, but driver behavior has not been fully addressed. A non-confrontational approach is the evaluation of driver behavior using onboard sensors and computer algorithms to determine the vehicle’s “mistrust” level of the given operator and the safety of the individual operating the vehicle. This is an inversion of the classic human-machine trust paradigm in which the human evaluates whether the machine can safely operate in an automated fashion.

Since 1989, ISO has published procedures for developing and testing public information symbols (ISO 9186), while the SAE standard for in-vehicle icon comprehension testing (SAE J2830) was first published in 2008. Neither testing method was designed to evaluate the comprehension of symbols in modern vehicles that offer digital instrument cluster interfaces that afford new levels of flexibility to further improve drivers’ understanding of symbols. Using a driving simulator equipped with an eye tracker, this study investigated drivers’ understanding of six automotive symbols presented on in-vehicle displays. Participants included 24 teens, 24 adults, and 24 senior drivers. Symbols were presented in a symbol-only, symbol + short text descriptions, and symbol + long text description conditions. Participants’ symbol comprehension, driving performance, reaction times, and eye glance times were measured.

The recently concluded partnership for advancing combustion engines (PACE) was a US Department of Energy consortium involving multiple national laboratories focused on addressing key efficiency and emission barriers in light-duty engines. Generation of detailed experimental data and modeling capabilities to understand and predict cold-start behavior was a major pillar in this program. Cold-start, as defined by the time between first engine crank and three-way catalyst light-off, is responsible for a large percentage of NOx, unburned hydrocarbon, and particulate matter emissions in light-duty engines. Minimizing emissions during cold-start is a trade-off between achieving faster three-way catalyst light-off, and engine out emissions during that period. In this study, engine performance, emissions, and catalyst warmup potential were monitored while the engine was operated using a single direct injection (baseline case) as well as a two-way-equal-split direct injection strategy.

With increasingly stringent regulations mandating the improvement of vehicle fuel economy, automotive manufacturers face growing pressure to develop and implement technologies that improve overall system efficiency. One such technology is an automatic (auto) stop-start feature. Auto stop-start reduces idle time and reduces fuel use by temporarily shutting the engine off when the vehicle comes to a stop and automatically re-starting it when the brake is released, or the accelerator is pressed. As mandated by the U.S. Congress, the U.S. Environmental Protection Agency (EPA) is required to keep the public informed about fuel saving practices. This is done, in partnership with the U.S. Department of Energy (DOE), through the fueleconomy.gov website. The “Fuel-Saving Technologies” and “Gas Mileage Tips” sections of the website are focused on helping the public make informed purchasing decisions and encouraging fuel-saving driving habits.

Renewable fuels, such as the alcohols, ammonia, and hydrogen, have a high autoignition resistance. Therefore, to enable these fuels in compression ignition, some modifications to existing engine architectures is required, including increasing compression ratio, adding insulation, and/or using hot internal residuals. The opposed-piston two-stroke (OP2S) engine architecture is unique in that, unlike conventional four-stroke engines, the OP2S can control the amount of trapped residuals over a wide range through its scavenging process. As such, the OP2S engine architecture is well suited to achieve compression ignition of high autoignition resistance fuels. In this work, compression ignition with wet ethanol 80 (80% ethanol, 20% water by mass) on a 3-cylinder OP2S engine is experimentally demonstrated. A load sweep is performed from idle to nearly full load of the engine, with comparisons made to diesel at each operating condition.

To achieve carbon neutrality by 2060, the Chinese government has put effort into decarbonizing the transportation sector. Consequently, China elaborated a new energy vehicle strategy promoting the production of electric vehicles and expanding into hydrogen (H2) vehicle technologies including fuel cell electric vehicles and H2 internal combustion engine vehicles. The Transportation Energy Analysis Model (TEAM) projects the market penetration as well as energy demand and greenhouse gas emissions in China up to 2050. By integrating the Monte Carlo simulation, this study tests the robustness of TEAM and investigates the key parameters that will shape passenger vehicle sales and emissions in the future. The results show that fuel cell cost, H2 price, and battery cost are the most sensitive parameters for H2 vehicle technologies.

China's plug-in electric vehicle (PEV) market with stocks at 7.8 million is the world's largest in 2021, and it accounts for half of the global PEV growth in 2021. The PEV market in China has dramatically evolved since the pandemic in 2020: over 20% of all new PEV sales are from China by mid-2022. Recent features of PEV market dynamics, consumer acceptance, policies, and infrastructure have important implications for both the global energy market and manufacturing stakeholders. From the perspective of demand pull-supply push, this study analyzes China's PEV industry with a market dynamics framework by reviewing sales, product and brand, infrastructure, and government policies from the last few years and outlooking the development of the new government’s 14th Five-Year Plan (2021-2025).

Spark ignition knock is highly sensitive to changes in intake air temperature. Hot surface temperatures due to ceramic thermal barrier coatings increase knock propensity by elevating the incoming air temperature, thus mitigating the positive impacts of low heat transfer losses by requiring spark retard to avoid knock. Low thermal inertia coatings (i.e. Temperature swing coatings) have been proposed as a means of reducing or eliminating the open cycle charge heating penalty of traditional TBCs through a combination of low thermal conductivity and low volumetric heat capacity materials. However, in order to achieve a meaningful gain in efficiency, a significant fraction of the combustion chamber must be coated. In this study, a coated piston and intake and exhaust valves with coated combustion faces, backsides, and stems are installed in a single-cylinder research engine to evaluate the effect of high coated fractions of the combustion chamber in a knock-sensitive architecture.

Formal verification plays an important role in proving the safety of autonomous vehicles (AV). It is crucial to find errors in the AV system model to ensure safety critical features are not compromised. Model checking is a formal verification method which checks if the finite state machine (FSM) model meets system requirements. These requirements can be expressed as linear Temporal logic (LTL) formulae to describe a sequence of states with linear Temporal properties to be satisfied. NuSMV is a dedicated software for performing model checking based on Temporal logic formulae on FSM models. However, NuSMV does not provide model-based design. On the other hand, Stateflow in MATLAB/SIMULINK is a powerful tool for designing the model and offers an interactive Graphical User Interface (GUI) for the user/verifier but is not as efficient as NuSMV in model checking.

Testing any new safety technology of Autonomous Vehicles (AV) and Advanced Driver Assistance Systems (ADAS) requires simulation-based validation and verification. The specific scenarios used for testing, outline incidences of accidents or near-miss events. In order to simulate these scenarios, specific values for all the above parameters are required including the ego vehicle model. The ‘criticality’ of a scenario is defined in terms of the difficulty level of the safety maneuver. A scenario could be over-critical, critical, or under-critical. In over-critical scenarios, it is impossible to avoid a crash whereas, for under-critical scenarios, no action may be required to avoid a crash. The criticality of the scenario depends on various parameters e.g. speeds, distances, road/tire parameters, etc. In this paper, we propose a definition of criticality metric and identify the parameters such that a scenario becomes critical.

In this study the volume and hardness were measured for thermoplastics and thermosetting resins with diesel containing up to 30% of the following blend stocks: biodiesel, renewable diesel, n-undecane, dibutoxymethane, 1-octanol, hexyl hexanoate, and 2-nonanone. Thermoplastics included polyphenylene sulfide (PPS), polyethylene terephthalate (PET), polytetrafluoroethylene (PTFE), polyvinylidene fluoride (PVDF), polyoxymethylene (POM), polybutylene terephthalate (PBT), polypropylene (PP), high density polyethylene (HDPE), nylons, acetals, polyetherimide (PEI), polyetheretherketone (PEEK), a PET co-polymer, polyphthalamides (PPAs), polyarylamide (PARA) and ethylene tetrafluoroethylene (ETFE). Three thermosetting resins were also evaluated. The material specimens were exposed to the test fuels under ambient conditions for 16 weeks.