Browse Topic: Electric drives
The transition to software-defined vehicles (SDVs) necessitates a paradigm shift in both control strategies and vehicle architecture. The EU-funded R&D project SmartCorners addresses this challenge by developing integrated, modular, and scalable smart corner systems (SCS) that combine in-wheel motor (IWM)-based propulsion, brake blending, active suspension system, and steer-by-wire functionality in one module. These SCS can be retrofit or smoothly integrated into the highly adaptable skateboard chassis architecture of modern electric vehicles (EVs), enabling scalable deployment across diverse vehicle types. The central approach of this paper is the utilization of artificial intelligence (AI) and machine learning (ML) to implement multi-layer, data-driven control strategies, facilitating real-time actuation, fault mitigation, and user-centric EV architecture. The SmartCorners project strives to demonstrate significant enhancements, including improved real-world driving range due to
Reducing the high-voltage BEV to a household level of 120-240 volts is considered in the paper as an effective means of solving the problems of electrical safety, maintenance and minor repairs of an electric vehicle in household conditions, and distributed power supply of BEV within walking distance for the driver. The analysis of the low-voltage electric drive is performed under the assumption that the battery has a nominal voltage of 200 volts. The issues of transforming a high-voltage machine (400 volts) into a low-voltage one (200 volts) by switching the stator phase sections from serial to parallel connection without changing the overall and energy characteristics are considered. It is shown that a two-motor unit with induction machines with a capacity of 50 kilowatts can provide 100 kilowatts in long-term and up to 200 kilowatts in peak modes. The paper considers the issues of implementing a low-voltage inverter and modern trends in distributed power supply for BEVs based on low
Thermal and lubrication management is critical for the performance characteristics of Electric Drive Units (EDUs) in electrified powertrains. Accurate assessment of lubrication flow, particularly in terms of wetting behavior and churning losses, is essential for optimizing EDU performance across various driving conditions. This study presents a comprehensive numerical investigation of lubrication flow behavior within an EDU using an advanced Smoothed Particle Hydrodynamics (SPH) method. The mesh-free SPH approach provides significant advantages in modeling intricate oil dynamics, such as oil splashing, and the behavior of oil in contact with rotating components. The primary focus of this study is to investigate the phenomena of oil splashing, wetting behavior characterized by the Wetting Fraction(WF), and churning losses within the gearbox environment. Key flow characteristics such as oil distribution, particle trajectories, torque resistance due to fluid drag, and oil volume fraction
Inverters are typically integrated into electric drive units for electric vehicles (EVs) to reduce packaging size and cost. However, coupled vibrations from the electric motor and gears are transmitted to the inverter, which can become a dominant noise source due to its large radiative panel. Metal panels are required for electromagnetic interference (EMI) compliance, yet these covers usually lack sufficient stiffness or damping for noise control. Adding ribs and applying damping treatments result in excessive mass, cost, and packaging challenges. A new bubble sheet panel design has been developed to enhance the structural strength and damping performance of the inverter cover while significantly reducing its mass. A thin sheet of aluminum is welded onto the cover in an optimized pattern that enhances stiffness and damping performance while accommodating packaging requirements. The welding pattern can include logos or artistic designs to improve the panel’s appearance. The metal sheets
Conventional inverter control uses a fixed switching frequency, which leads to high-pitched switching noise in electric vehicles (EVs) that does not vary with vehicle speed. Although EVs are much quieter than traditional internal combustion engine (ICE) vehicles, some EV owners complain about the lack of dynamic driving sound feedback. A new patented technology has been developed to enhance EV sound quality by dynamically controlling the inverter switching frequencies. This technology generates dynamic propulsion sound with new "switching order" features at multiple harmonics, with the pitch proportional to vehicle speed. A constant pulse ratio between the switching frequency and the electric motor RPM is implemented to control the switching order. This reduces switching losses during low-speed operation and provides boosted acoustic feedback to the driver during acceleration, which enhances driving experience during sports driving. Furthermore, a special "EV shifting" sound that
Monitoring power device temperature in an electric vehicle propulsion drive converter is extremely important to achieve full power delivery within the maximum power capability envelope. Usually, on-die temperature sensors are installed on Si-IGBT power devices in electric vehicle propulsion drive converters to enable monitoring device temperature and achieve over-temperature protection. Currently, SiC MOSFET is a promising power device in power converters of electric drives because of its lower loss, higher switching speed, higher voltage capability, and higher junction temperature limit in comparison with the widely used Si-IGBT. However, SiC MOSFET is a more expensive device, installation of an on-die temperature sensor on SiC MOSFET will significantly increase its cost and complexity. So presently, there is no junction temperature sensor installed in SiC MOSFET due to which there is great difficulty protecting SiC MOSFET from over temperature. When a junction temperature estimation
As already well-understood/enormous engineering practices, the inverter AC-side NVH phenomena/mechanisms/measures for motor-equipped vehicle, are already pretty clear. In addition to inverter AC side–induced NVH issues, DC ripple induced by PE switching leads to NVH issues manifesting on the capacitor, inductor, and conductor in terms of reverse piezoelectricity, electrostriction, magnetostriction, Laplace force, and so forth. These DC-side NVH issues are already literally analyzed by a couple of literatures, and mechanisms/measures are explored/applied to electric drive development. And yet, the phenomenon that a pulsating magnetic field inside a battery pack induced by DC current ripple off PE switching brings noise at switching frequency inside the vehicle cabin is newly captured/analyzed by our research, and that has been barely searched during the literature survey. This newly discovered phenomenon is the pivotal point in this paper. Although the noise features like the
This research provides a unique contribution to the field of in-wheel motor drive electric vehicles (EVs) by addressing the challenges associated with the use of permanent magnet synchronous motors (PMSMs) for traction. These motors, integrated into the unsprung masses, increase the rotational inertia of the wheels, reducing ride smoothness on uneven roads. To mitigate this issue, we present an optimal Kalman filter for a magnetorheological (MR) control suspension system that correlates road inputs between the front and rear wheels. This filter significantly improves the estimation accuracy of state variables by incorporating the vertical motion of the motor, along with potential enhancements from wheelbase preview. To determine the most suitable coil spring types for use with MR dampers, we used the WDW-600 computer-controlled electronic universal testing machine to evaluate three coil spring types: constant pitch (model A), variable pitch (model B), and conical spring (model C). To
When developing specialist and performance EVs, the challenge goes far beyond selecting an off-the-shelf powertrain. Each manufacturer brings unique performance targets, packaging constraints, and integration requirements. And add on the fact that no two platforms look the same. Powered by Everrati, our B2B division, engages directly with leading customers globally, capturing what they truly need from electric powertrains. Two areas emerge consistently as the most complex and variable: the electric drive unit (EDU) and the battery system.
The automotive industry has undergone significant transformation with the adoption of electric vehicles (EVs). However, the inadequate driving range is still a major limitation and to tackle range anxiety, the focus has shifted to energy management strategies for optimal range under different driving conditions. Developing an optimal energy management algorithm is crucial for overcoming range anxiety and gaining a competitive edge in the market. This paper introduces Dynamic Energy Management Strategy (DEMS) for electric vehicles (EVs), designed to optimize battery usage and extend the driving range. Utilizing vehicle digital twin model, DEMS estimates energy consumption across Eco, Normal, and Sports driving modes by analyzing vehicle velocity profiles and pedal inputs. By calculating actual battery consumption and identifying excess power usage, DEMS operates in a closed loop to periodically assess the power gap based on real-time vehicle conditions, including HV components like the
The increasing adoption of electric vehicles (EVs) has intensified the demand for advanced elastomeric materials capable of meeting stringent noise, vibration and harshness (NVH) requirements. Unlike internal combustion engine (ICE) vehicles, EVs lack traditional masking noise generated by the powertrain. In the automotive industry, the dynamic stiffness of elastomers in internal combustion engines has traditionally been determined using hydraulic test rigs, with test frequencies limited to a maximum of 1,000 Hz. Measurements above this frequency range have not been possible and are conducted only through computerized FE or CAE calculation models. Electric drive systems, however, generate distinct tonal noise components in the high-frequency range up to 10,000 Hz, which are clearly perceptible even at low sound pressure levels. Consequently, the dynamic stiffness characteristics of elastomers up to 3,000 Hz are critical for optimizing NVH performance in EVs. This study focuses on high
Vehicle electrification has introduced new powertrain possibilities, such as the use of four independent in-wheel motors, enabling the development of control strategies that enhance vehicle safety and drivability. The development of a model capable of simulating vehicle behavior is fundamental for control system design. A high-fidelity model takes into account several parameters, such as vehicle ride height, track width, wheelbase, and others, making it possible to evaluate the vehicle’s behavior and allowing for prior validation of the design, thus contributing to improved vehicle safety and performance. In this context, this study presents a lateral dynamic model of a Formula 4WD vehicle with in-wheel motors, enabling the simulation and analysis of the vehicle’s behavior in cornering maneuvers. To achieve this, the complete lateral model is developed using MATLAB Simulink as the platform, incorporating the semi-empirical Hans Pacejka tire model, calculating yaw moment, and analyzing
Horse Powertrain revealed more information about its all-in-one hybrid powertrain, the Future Hybrid System, at IAA Mobility 2025 in Munich in September. The new details involve a 1.5-L, four-cylinder unit with integrated engine, motor, and transmission that was designed to replace an EV's front electric drive module to convert that EV into a hybrid, PHEV, or range-extended EV. Horse Powertrain revealed two variants of the Future Hybrid System (FHS) in Munich. The first, called Performance, is 740 mm (29 in) wide and uses two motors in a P1 + P3 configuration, with one each on the engine output and transmission output shafts. The second, the Ultra-Compact, is 650 mm (26 in) wide and is designed to sit between the engine and transmission. The 1.5-L engine, a dedicated hybrid transmission, and a full suite of power electronics for hybrid use are used in both versions. The company said an even smaller version - by 70 mm (3 in) - with three cylinders is being investigated.
Direct current (DC) systems are increasingly used in small power system applications ranging from combined heat and power plants aided with photovoltaic (PV) installations to powertrains of small electric vehicles. A critical safety issue in these systems is the occurrence of series arc faults, which can lead to fires due to high temperatures. This paper presents a model-based method for detecting such faults in medium- and high-voltage DC circuits. Unlike traditional approaches that rely on high-frequency signal analysis, the proposed method uses a physical circuit model and a high-gain observer to estimate deviations from nominal operation. The detection criterion is based on the variance of a disturbance estimate, allowing fast and reliable fault identification. Experimental validation is conducted using a PV system with an arc generator to simulate faults. The results demonstrate the effectiveness of the method in distinguishing fault events from normal operating variations. The
An important characteristic of battery electric vehicles (BEVs) is their noise signature. Besides tire and wind noise, noise from auxiliaries as pumps, the electric drive unit (EDU) is one of the major contributors. The dynamic and acoustic behavior of EDUs can be significantly affected by production tolerances. The effects that lead to these scatter bands must be understood to be able to control them better and thus guarantee a consistently high quality of the products and a silent and pleasant drive. The paper discusses a simulation driven approach to investigate production tolerances and their effect on the NVH behavior of the EDU, using high precision transient multi-body dynamic analysis. This approach considers the main effects, influences, and the interaction from elastic structures of electric motor and transmission with accurate gear contact models in a fully coupled way. It serves as virtual end of line test, applicable in all steps of a new EDU development, by increasing
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