The automotive industry has used plastics almost since the beginning. The lightness, flexibility, and many qualities of plastics make them ideal for the automotive industry, reducing cars’ overall weight and fuel consumption. Engineering plastics in this industry belong to the high-performance segment of non-renewable resources. These plastics exhibit higher properties than commodity plastics. Fortunately, unlike recycled commodity plastics, the super properties and high-performance characteristics make engineering plastics effectively reused after recycling. The substitution of these fossil-fuel-derived plastics adds to the solution of lightweighting, a much-needed solution to waste management, and solves industrial and ecological issues surrounding plastic disposal. All major vehicle manufacturers worldwide use bioplastics and bio-based plastics, including natural-fiber composites and engineering plastics reinforced with natural fibers. Changing the source of plastics to raw materials from renewable resources is the logical approach to sustainability. Thus, high-quality plastics, recycled plastics, bio-based plastics, and biodegradable plastics could be exploited from design, making sustainability an integral concept of mobility development. This review analyzes that switching from fossil-fuel- to renewable-sources-derived plastics is a step toward meeting the current environmental goals for the automotive industry, including electric cars.

For smart cities using clean energy, optimal energy management has made the development of electric vehicles more popular. However, the fear of range anxiety—that a vehicle has insufficient range to reach its destination—is slowing down the adoption of EVs. The integration of an auxiliary power unit (APU) can extend the range of a vehicle, making them more attractive to consumers. The increased interest in optimizing electric vehicles is generating research around range extenders. These days, many systems and configurations of extended-range electric vehicles (EREVs) have been proposed to recover energy. However, it is necessary to summarize all those efforts made by researchers and industry to find the optimal solution regarding range extenders. This paper analyzes the most relevant technologies that recover energy, the current topologies and configurations of EREVs, and the state-of-the-art in control methods used to manage energy. The analysis presented mainly focuses on finding maximum fuel economy, reducing emissions, minimizing the system’s costs, and providing optimal driving performance. Our summary and evaluation of range extenders for electric vehicles seeks to guide researchers and automakers to generate new topologies and configurations for EVs with optimized range, improved functionality, and low emissions.

This article presents a perspective on the potential use of microalgae oils in the production of metal working fluids (MWFs) used for minimum quantity lubrication (MQL) operations. The generalities of MQL operations and requirements of MWFs, and current advances in the development of the most promising microalgae oils with high contents of saturated, monounsaturated, and polyunsaturated fatty acids were reviewed and discussed. The analysis of data, discussions, and conclusions of numerous studies published recently and combined with the experience of the multidisciplinary team of authors strongly suggest that microalgae oils do indeed have great potential as sustainable and eco-friendly base oils for producing semi-synthetic MWFs, soluble oils and straight cutting fluids for MQL operations. Additionally, gaps and challenges focused on the use of agro-industry wastewater in microalgae production, green harvesting and oil extraction methods, and replacement of toxic additives in MWFs by green nanoparticles and biopolymers were identified and highlighted for achieving massive microalgae oil-based MWFs production and truly green machining processes.

Electric vehicles must improve their electric drive system efficiency and effectively use their limited energy to become a viable means of transportation. As such, these technologies have undergone substantial improvements from their initial conception. More efficient powertrains, together with improved storage technologies, have enabled more extended autonomy. However, from an engineering perspective, these systems are still a key area of research and optimization. This work presents a powertrain optimization methodology, developing energy savings and improving the performance of the electric vehicle by focusing on the differential. The proposed methodology includes a study of the dynamics of the electric vehicle and the generation of a mathematical model that represents it. By simulating the vehicle and varying the final ratio of the differential, a significant optimization for energy savings is obtained by developing a standardized driving cycle. In this case, NEDC, WLTC-2, and WLTC-3 test cycles are used. The results show that a short ratio improves performance, even if this implies a larger torque from the prime mover. Depending on the operating cycle used, an energy-saving between 3% and 8% was registered. An extended energy autonomy and an increment in the life-cycle of the batteries are expected in real driving scenarios.

The continuous expansion of the vehicle fleet contributes to escalating emissions, with the transportation sector accounting for approximately 21% of CO₂ emissions, based on 2023 data. Focused on reducing emissions and reliance on fossil fuels, the study observes the shift from internal combustion vehicles to electric and hybrid models since 2017. Despite advancements, these vehicles still lack optimal efficiency and suffer from limited range, deterring potential buyers. This article aims to evaluate the range-extending technologies for electric vehicles, emphasizing efficiency, low pollution, and integration compatibility. An algorithm incorporating equations representing mechanical or electrical component curves is developed for Extended-Range Electric Vehicles, facilitating insight into potential range extender behavior. The core objectives of this study involve optimizing the entire powertrain system to ensure peak efficiency. Experimental tests demonstrate that integrating an auxiliary power unit enhances range, with an internal combustion engine generator configuration extending the travel distance by 35.35% at a constant speed. Moreover, with the use of an Equivalent Consumption Minimization Strategy control, the distance traveled increases up to 39.28% on standard driving cycles. The proposed methodology, validated through practical implementations, allows for comprehensive energy analyses, providing a precise understanding of vehicle platform performance with integrated range extenders.

Improving energy efficiency in manufacturing processes is a critical global concern for the industry. Manufacturers strive to enhance energy efficiency across all manufacturing operations to remain competitive globally, aiming to reduce production times without compromising product quality. While there has been significant research characterizing energy efficiency and surface roughness in conventional processes like turning or milling, studies on unconventional manufacturing techniques are limited. This study focuses on optimizing a wire electrical discharge machining (WEDM) process to minimize energy consumption while maintaining surface roughness. Various cutting parameters, such as pulse on-time, pulse off-time, servo voltage, wire tension, wire speed, and wire voltage, were evaluated. Experiments were conducted using Taguchi’s methodology with a $L_{27}$ orthogonal array, employing AISI D2 steel plates of 19 mm and 25 mm thickness as the machining material. The research identified that optimal parameters for reducing energy consumption and improving surface roughness included a pulse on-time of 10 s, pulse off-time of 11 s, servo voltage of 44 V, wire tension of 50 g-force, wire speed of 7 m per minute, and wire voltage of 9 volts. This combination led to an 8% reduction in energy consumption and a 1% enhancement in surface roughness compared to baseline values.