Browse Topic: Regenerative braking
With the growing trend of electric vehicles (EVs) incorporating regenerative braking systems, many compact SUVs, including hybrids and EVs, still utilize drum brakes on the rear wheels to strike a balance between cost, performance, and durability. Drum brake squeal remains a complex and persistent challenge in the field of vehicle noise, vibration, and harshness (NVH). This issue stems from dynamic instability caused by time–dependent friction forces. Traditional linear modal analysis has been used to study the mechanisms behind drum brake squeal, focusing on harmonic vibrations in large–scale models. However, these methods often fail to accurately correlate with real world behavior due to the presence of extra, non-physical modes. To address this, time–domain analysis approaches have been explored, incorporating detailed friction models and contact mechanics. These methods consider different root causes for high and low–frequency squeal and have shown promising results in accurately predicting brake squeal behavior when validated against experimental data.
As the brain and the core of the electric powertrain, the traction inverter is an essential part of electric vehicles (EVs). It controls the power conversion from DC to AC between the electric motor and the high-voltage battery to enable effective propulsion and regenerative braking. Strong and scalable inverter testing solutions are becoming more essential as EV adoption rises, particularly in developing nations like India. In India, traditional testing techniques that use actual batteries and e-motors present several difficulties, such as significant safety hazards, inadequate infrastructure, expensive battery prices, and a shortage of prototype-grade parts. This paper presents a comprehensive approach for traction inverter validation using the AVL Inverter TS™ system incorporating an advanced Power Hardware-in-the-Loop (PHiL) test system based on e-motor emulation technology. It enables safe, efficient, and reliable testing eradicating the need for actual batteries or mechanical loads. Testing across signal and power levels and the validation of both inverter hardware and software under real-world driving scenarios can be facilitated with proposed test system. Indian OEM challenges like reduction in battery development costs, ensuring high replication precision, and managing thermal and power instability in early-stage prototypes are primary focus areas for this test system. With the Inverter TS, various motor types (IM, EESM, PMSM), switching strategies, and SiC based 800V architectures with different control architectures can be emulated and validated, which can further be optimized for powertrain efficiency. Inverter efficiency maps can be derived and fast control strategy can be iterated which facilitates the the overall drivetrain optimization. This paper focus on how adopting such emulation test methodologies can help EV developers to overcome infrastructure gaps, reduce time-to-market, and enhance powertrain efficiency at a lower cost.
This study investigates an optimal control strategy for a battery electric vehicle (BEV) equipped with a high-speed motor and a continuously variable transmission (CVT). The proposed dual-motor powertrain model activates only one motor at a time, with Motor A routed through a CVT and Motor B through a fixed gear. To improve energy efficiency, two optimization methods are evaluated: a quasi-steady-state map-based approach and a dynamic programming (DP) method. The DP approach applies Bellman’s principle to derive the globally optimal CVT ratio and motor torque trajectory over the WLTC cycle. Simulation results demonstrate that the DP method significantly improves overall efficiency compared to traditional control logic. Furthermore, the study proposes using DP-derived maps to refine practical control strategies, offering a systematic alternative to conventional experimental calibration.
Increasing the mission capability of ground combat and tactical vehicles can lead to new concepts of operation that enhance safety and effectiveness of warfighters. High-temperature power electronics enabled by wide-bandgap semiconductors such as silicon carbide can provide the required power density to package new capabilities into space-constrained vehicles and provide features including silent mobility, boost acceleration, regenerative braking, adaptive cooling, and power for future protection systems and command and control (C2) on the move. An architecture using high voltage [1] would best satisfy the ever-increasing power demands to enable defense against unmanned aerial systems (UAS) and offensive directed energy (DE) systems for advanced survivability and lethality capabilities.
As the ICE vehicle changes into the EV, we can use regenerative brake. It can improve not only the energy consumption but also reduce the hydraulic brake usage. The less hydraulic brake usage mitigates the heat loading on the brake disc. From this reason, the lightweight brake can be used in the EV. However, when the lightweight brake is applied, the brake NVH can be increased. The optimization design of the lightweight brake should be done to prevent the brake NVH. In this paper, the optimal brake disc thickness and brake interfaces are determined by using of disc heat capacity analysis. The lightweight brake should be optimized by using of the brake squeal analysis. We can verify the results from both analysis and test. Finally, we can have the lightweight brake, which is competitive in terms of cost, weight and robust to the brake NVH.
The use of drum brakes in Battery Electric Vehicles (BEVs) offers numerous benefits, including energy efficiency, reduced brake dust emissions, and reliable performance under challenging weather conditions. The capability of regenerative braking reduces the friction brake application frequency in BEVs and therefore the brakes can be prone to corrosion and performance degradation especially considering conventional disc brake systems. The closed design of a drum brake prevents corrosion of the friction-components by sealing out water, dirt or snow. A common sealing concept is performed with a labyrinth between the gap of the rotating drum and the axle mounted backplate. A hermetical isolation of water and snow ingress into the drum cannot be achieved with this concept, so additional aerodynamic measures are necessary to deflect the air/water path and protect the inner brake components. Additionally, interfaces like wheel cylinders, electric park brake parts, brake shoe pins, and axle mountings can potentially lead to leaks on the backplate. This study highlights the impact of water/snow ingress on the example of a frozen parking brake during cold climate on-road testing. Through scientific investigation using the state-of-the-art fluorescence method, drum leakages were visualized, and the extent of water ingress was measured. Multiple multiphase CFD simulations supported the design phase of the aerodynamic measures. Subsequently, the vehicle was cooled down to -10 °C to simulate the cold climate test conditions. The frozen parking brake situation could be reproduced with this method, and beneficial aerodynamic and sealing measures were extrapolated to avoid the drum brake from freezing. The tests were conducted in the FKFS Thermal Wind Tunnel, a wind tunnel comprising a two-axle-dynamometer and water irrigation systems with UV illumination.
From humble Chevrolet Bolts to six-figure Lucid Airs, every EV can reverse its electric motors to slow the vehicle while harvesting energy for the battery, the efficient tag-team process known as regenerative braking. Today's EVs do this so well that traditional friction brakes, which clamp onto a spinning wheel rotor or drum, can seem an afterthought. Witness Volkswagen's decision to equip its ID.4 with old-fashioned rear drum brakes, with VW claiming drums reduce EV rolling resistance and offer superior performance after long periods of disuse.
Lithium-ion cells operate under a narrow range of voltage, current, and temperature limits, which requires a battery management system (BMS) to sense, control, and balance the battery pack. The state of power (SOP) estimation is a fundamental algorithm of the BMS. It operates as a dynamic safety limit, preventing rapid ageing and optimizing power delivery. SOP estimation relies on predictive algorithms to determine charge and discharge power limits sustainable within a specified time frame, ensuring the cell design constraints are not violated. This paper explores various approaches for real-time deployment of SOP estimation algorithms for a high-power lithium-ion battery (LIB) with a low-cost microcontroller. The algorithms are based on a root-finding approach and a first-order equivalent circuit model (ECM) of the battery. This paper assesses the practical application of the algorithm with a focus on processor execution time, flash memory and RAM allocation using a processor-in-the-loop (PIL) setup. The case study estimates the maximum power available for regenerative braking at high SOCs and compares predictions with experimental data. More specifically, deployments using single and double-precision floating numbers are compared, alongside different voltage estimation approaches. In addition, the bisection root-finding method is compared to the secant and Brent’s method. The different algorithms tested in this study do not significantly impact memory allocation. In terms of processor load, however, single-precision deployments are significantly more cost-effective than double-precision deployments, with a negligible discrepancy in the predicted output. Finally, the secant root-finding method reduces the execution time by two-thirds while retaining the same level of accuracy when compared to the bisection method.
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