The proper functioning of automotive brake pads is of utmost importance to ensure the safety of passengers. Therefore, brake pad materials must be chosen with utmost precision and care to ensure their optimal functioning for long durations. Through a thorough literature review, it is found that the materials used currently for this purpose pose multiple discrepancies. Therefore, it is imperative to shift our focus towards nanomaterials, as they are one of the essential novel materials in this field. This study discusses the multiple constituents used in commercial brake pads, their role in improving and stabilizing their operation, and their desired properties to achieve optimal functioning. Parallelly, this study also reviews some of the potential organic and carbon nanomaterials that could prove to provide tough competition to currently utilized materials for brake pad applications. From this review, the major future commercial brake pad materials obtained include the likes of banana peel powder, crab shell powder, coconut fibers, stark corn fibers, metal oxide composites, metal nitride composites, multiwalled carbon nanotubes, and hybrid nanocomposites. These materials are studied on the basis of their performance under high-frictional force applications and analyzed by considering their mechanical, chemical, thermal, and tribological properties. Carbon nanotube-based composites showed improved tribological and braking performances making them more attractive than the materials in commercially available brake pads. In addition to these, the effects of usage of such nanomaterials on the environment and health are reviewed, in order to understand the feasibility of utilization of nanomaterials in automotive brake pad applications. From this analysis, this work suggests that there are a variety of nanomaterials that prove to be capable of automotive brake pad applications and, with further research and technological developments, would prove to be an asset to the automotive brake pad industry.

Future mobility is expected to be sustainable in terms of energy production, consumption, and vehicle emissions. Embedded intelligent systems are playing a crucial role in the electrification of vehicles, their autonomy and implementation. Though electric vehicle technology is expected to lead the automotive powertrain architecture in the coming decades, various barriers currently hinder their acceptance into the automotive market. These barriers are generally categorized into battery technology, vehicle performance, charging infrastructure, consumer behavior, and government support. Hence, a detailed analysis of these barriers, especially for developing countries with minimal electric vehicle penetration is an area of concern. This article investigates the barriers and infers the comparative order of resolution for each barrier based on its priority to be identified and overcome. As consumers are the major influencers of electric vehicle demand and acceptance, barrier analysis is carried out based on their opinions. Using a Consumer Perception Survey, this article determines the influence of each barrier on potential users of electric vehicles. Fuzzy Stepwise Weight Assessment Ratio analysis and TOPSIS are implemented to allocate evaluation factors to each sub-barrier to obtain the hierarchy of priority. Furthermore, this article highlights the policies and schemes implemented in developed countries and correlates them with their electric vehicle population. The article sheds light on different measures to be taken in developing countries such as India to mitigate barriers and bridge gaps. The outcome of the literature review and consumer perception survey shows that the major factors affecting electric vehicle implementation in developing countries are the lack of charging infrastructure and high overall cost. Therefore, it is realized that such developing countries must introduce more schemes and incentives on infrastructural and operational costs to promote EV growth.

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This study aims to achieve optimal regenerative braking performance in the form of a reduced decline in battery SOC for a BLDC electric machine with peak torque of 10 Nm for use in electric two-wheelers. This is conducted via a comparison of control algorithms based on Direct Look-up table, Fuzzy Logic and their combination with PID control. The whole vehicle model and the energy recovery control strategies are designed using MATLAB Simulink by benchmarking the design with the parameters of the Ola Electric S1. A physical motor-dynamometer test bench is utilised to obtain a complete motor operating range to derive a realistic efficiency map that is used in the model. WLTP Class 2 and NYCC standard drive cycles are implemented for vehicle simulation. Two live-recorded driving patterns are also used to validate the model to analyse the adaptability of the control strategies. After obtaining the required motor speed, torque values and the range by matching the theoretical drive cycle profile, the control strategy is further optimised using the PID auto-tuning toolbox in Simulink. Using physical testbench data, the effect of various regenerative braking control strategies on overall vehicle performance is more accurately realised. The Fuzzy PID control strategy exhibits the most optimal gains in terms of energy recovery for electric two-wheelers, allowing for the highest battery SOC levels of 41.88% and average motor regenerative torque of 7.25 Nm for the standard drive cycles. An analogous trend is observed for the on-road driving pattern as Fuzzy PID provides highest battery SOC and average motor regenerative torque of 48.34% and 7.5 Nm respectively. For the driving scenarios aforementioned, this provides a 17% and 44% increase in SOC respectively when compared to a non-regenerative braking-based system.

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