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Browse AllThis specification covers a corrosion-resistant steel in the form of investment castings homogenized and solution and precipitation heat treated to 180 ksi (1241 MPa) tensile strength.
Growing population in Indian cities has led to packed roads. People need a quick option to commute for both personal trips and business needs. The 2-3 Wheel Combination Vehicle is a new, modular solution that switches between a two-wheeler (2W) and a three-wheeler (3W). Hero has designed SURGE S32 to be a sustainable and flexible transportation option. It is world’s first class changing vehicle. The idea is to use a single vehicle for zipping through city traffic, making deliveries, or earning an income. Manufactured to deal with the challenges of modern life, this dual-battery convertible vehicle can easily transform from a two-wheeler to a three-wheeler and vice versa within three minutes. The Surge S32 is a versatile vehicle that replaces the need for multiple specialised vehicles. By lowering the number of vehicles on the road, it decreases road congestion, reduces emissions, and improves livelihoods. It powers by electricity, ensuring sustainability in all aspects. The current
During parking conditions of vehicles, the state of the battery is uncertain as it goes through the relaxation process. In such scenarios, the battery voltage may exceed the functional safety limits. If we cross the functional safety limits, it is hazardous to the driver as well as the occupant. In this case, relaxed voltage plays a crucial role in identifying the safe state of the battery. To estimate the relaxed cell voltage there are methods such as RC filter time constat modeling and relaxation voltage error method. The problem with these solutions is the waiting time and accuracy to determine the relaxation voltage. In this manuscript, a solution is proposed which ensures the above problem is reduced. To achieve the reduction of relaxation voltage estimation time, a python sparse identification of nonlinear dynamics (PySindy) is used which identifies and fits an equation model based on observing the battery characteristics at different SOC and temperatures. The implementation is
India's electric 2-wheeler (E2W) market has witnessed fast growth, driven by lucrative government policies. The two-wheeler segment dominates the Indian automotive market, accounting for the largest share of total sales. Consequently, the manufacturers of 2-wheelers are developing new electric vehicles (EV) tailored for the Indian market. However, the Indian EV market has witnessed multiple fire accidents in recent years, raising safety concerns among consumers and industry stakeholders. These incidents highlight key weakness in battery thermal management systems (BTMS), particularly during charging. Most existing E2W BTMS relies on passive (natural) air cooling, which has been associated with fire incidents due to its inefficiency in heat dissipation, particularly during charging in India's high-temperature environment. Therefore, it is imperative to build thermally viable and economical BTMS for the growing E2W vehicles with fast charging capability. FEV is actively developing the
Tire noise reduction is important for improving ride comfort, especially in electric vehicle due to lack of engine noise and majority of the noise generated in-cabin is from tire-road interaction. Therefore, the tire tread pattern contribution is one of the important criteria for NVH performance apart from other structurally generated noise and vibration. In this work a GUI-based pitch sequence optimization tool is developed to support tire design engineers in generating acoustically optimized tread sequences. The tool operates in two modes: without constraints, where the pitch sequence is optimized freely to reduce tonal noise levels; and with constraints, where specific design rules are applied to preserve pattern consistency and manufacturability. The key point to be considered in this pitch sequence is that it should be reducing the tonal sound and equally spread i.e., the same pitch cannot be concentrated on one side which may lead to non-uniformity. So, the restriction is that
When the flow of fluid within a high-pressure line is abruptly halted, pressure pulsations are generated. This phenomenon is known as the water hammer effect. This may lead to significant stress and, in the worst-case scenario, results in various types of failures within the highly pressurized system. Similar issues are observed in diesel high pressure fuel line where pressure is well above 1600 bar. Due to multiple injections on-off events, pressure pulsation gets created inside high pressure fuel lines (HPFL) which leads to problems such as high strain on high pressure fuel lines, mechanical damage, uneven fuel injected quantity, vibration beyond specification limits for rail pressure sensors or in worst case extreme noise. This is due to high pressure pulsation which occurs when fluid/fuel natural frequency resonates with structural HPFL natural frequency. In this work, A comparative FEA analysis is conducted to evaluate strain in two distinct high-pressure fuel lines, with pressure