Browse Topic: Vehicle drive systems
Letter from the Guest Editors
The multi-articulated vehicle uses distributed drive mode. Due to its large degree of freedom of movement and the large number of driving shafts, different torque distribution methods affect the operational stability of the vehicle, how to coordinate and distribute the torque of each driving motor has become an urgent problem to be solved. To improve drive stability of the multi-articulated vehicles, propose a layered torque allocation control strategy. The upper-layer sliding mode controller determines the required additional yaw moments of each car body based on the linear reference model, the controller is characterized by swift response and a strong ability to resist interference. The lower-level allocation module comprehensively considers the torque output limitations of the electric hub motors, the prevailing road adhesion state, and the corrective yaw moment constraints given by the upper layer, and constructs an optimization objective function centered on the uniformity and stability of tire load. The optimal distribution of driving forces for each wheel is completed by solving this function dynamically. To validate the strategy's effectiveness, a vehicle dynamics model is built in the multi-body dynamics software ADAMS/View. Using a joint simulation framework integrating ADAMS/View and MATLAB®/Simulink, the effect of the layered control strategy is evaluated in comparative simulation with uncontrolled situation under U-turn and single lane change conditions. The simulation outcomes demonstrate that, compared to uncontrolled situation, the yaw rate deviation of each car body under the torque layered control are significantly reduced, and the adhesion utilization rate of tire is also effectively controlled, thereby the driving stability is improved.
This study details the development and experimental validation of a high-fidelity one-dimensional (1D) simulation model for a two-speed transmission designed for off-road vehicles, such as tractors and backhoe loaders used in agricultural and civil engineering applications. The model, implemented in the AMESim platform from Siemens, integrates physics-based loss sub-models for all major components, including gears, bearings, seals, and fluid drag (churning) losses. After development, the model was rigorously validated against test bench data, with efficiency measurements taken across various speed, torque, and oil level combinations, demonstrating a strong correlation with experimental results. A detailed analysis enabled the quantification of the contribution of each loss mechanism, identifying the countershaft gears and input shaft bearings as the primary contributors. Furthermore, a Machine Learning (ML)–based calibration framework, employing Bayesian Optimization, was implemented to reduce discrepancies between simulation and experiment and to generate a synthetic dataset for the creation of fast-executing surrogate models. The study concludes that the proposed methodology constitutes an effective tool for efficiency analysis and optimization during early design stages, establishing a foundation for future integration with ML techniques and the development of digital twins.
The virtual development of Electric Drive Modules (EDMs) for Battery Electric Vehicles (BEVs) requires proven and predictive methodologies. One part of the development investigates the vibro-acoustic assessment for the low- and high-frequency ranges within the targeted operating range. The efficient use of such a methodology requires an understanding of the accuracy and validity of the achievable results, as well as the derivation of suitable improvement measures for goals that have not been achieved. The use of reference data from experimental investigations and a detailed root cause analysis (RCA), to directly link a specific response and behavior to the excitations, modal content, and transfer functions, is an essential and non-trivial part of the methodology development. This paper describes the development of such a methodology using the example of a new EDM virtual model for Noise, Vibration and Harshness (NVH) analysis, including the simulation approach, validation, and evaluation procedure. It discusses how RCA can be applied to different observed phenomena in EDM NVH behavior and detected deviations between the initial model and the measurements, the main influencing parameters, and the identified improvement potential for simulation models.
The ongoing efforts for reduction of the traffic-related greenhouse gas emissions and, at the same time, the mitigation of harmful pollutant emissions from vehicle exhaust emissions are important development tasks for the entire automotive industry worldwide according to demand to provide clean and efficient products. Further tightened fleet average FE standards and ultra-low limits for exhaust emissions require the continuous development of new propulsion system types. Due to the given reluctance of the end customer and corresponding low acceptance of fully electrified vehicles, especially in the commercial vehicle segment, new and innovative topologies are needed to meet regulatory requirements and maintain the high versatility of today’s dominating solutions. For further optimization of operating conditions with enhanced fuel efficiency, the technical strategy is also determined by uplifting the attractiveness of electric driving incl. the avoidance of areas with poor ICE efficiency and as well as the coverage of emission-critical operations by electric propulsion. In this context, the support provided by an electric drive on board the vehicle in a combined drive system is becoming increasingly important. This article discusses accordingly various platform strategies for hybridized Diesel powertrains in different sectors of commercial vehicle applications and delivers a comprehensive comparative analysis of different hybrid drive concepts. Specifically, several hybrid powertrain configurations that extend an electric drive platform (hybridized BEVs), such as series and parallel-series topologies, are compared with traditional parallel hybrid powertrain topologies based on internal combustion engines (ICE). The study focuses mainly on two different cornerstone applications: a large light commercial vehicle, ranging from 3,5 to 6,5 to. and a heavy-duty long-haul truck with 40…44 to. gross vehicle weight. It evaluates the advantages in terms of CO2 emissions and Diesel fuel savings and investigates the effects on emission controls aspects. In addition to technical comparisons, the paper addresses also regulatory demands and end customer merits, assessing the integrational effort and commonalities in components with pure ICE and battery electric topologies. Furthermore, it explores the additional impact of advanced operational strategies for Hybrid Diesel powertrains, incorporating insights from innovative observations from executed hybrid technology demonstrator vehicles.
After four decades of research and 3.5 year prototype testing campaign, Penn State's pericyclic transmission technology demonstrator, dubbed the 'Pericycler', has achieved its operating speed of 5,000 RPM at 17 HP. The characterization of this system by experimental efficiency and vibration represents a major milestone in pericyclic gear technology. A post-test inspection procedure was performed to analyze component wear and validate hypotheses on mesh behavior. This work concludes with structural, tribological, and instrumentation modifications to the Pericycler for future testing.
Full state feedback offers theoretically guaranteed multi-axis stability, making it superior to conventional PID controllers. There is however one drawback, a full state controller has a mathematical difficulty if the B matrix is not square and thus not invertible. This is the case for helicopters with 6 degrees of freedom and 4 inceptors. Variations of linear quadratic regulators are a work around, however complexity dramatically increases. Best would be a direct solution to the original problem. This is the breakthrough result of this paper. This paper documents an approach which removes the analysis roadblock by partitioning the 6 x 6 system "A" matrix into two groups of 4 x 4 matrices. The 4x4 matrices are individually stabilized with full state gain matrices. One matrix is designated “Driver Matrix” which provides actuator commands. The other matrix is designated "Reference Matrix" which provides references. The two matrices are coupled together by requiring that the driver matrix follow references generated by the reference matrix. With each matrix individually stabilized, the coupled combination is also stabilized. Computation of flight dynamics states (u, v, w, p, q, r) is shared between the matrices. Initial results are very encouraging, showing an originally sluggish, heavy lift helicopter having now concise decoupled responses to pitch and roll commands. Stability derivatives are recomputed during flight allowing coverage over the whole flight envelope. A handling qualities task has been defined to relocate a 40 ft standard seaborne container directed by a pilot in a ground control station. Cooper Harper ratings of this task have demonstrated favorable Level 1 handling qualities if use is made of an automated lateral repositioning command.
Toyota continues to shift gears out of sync with other OEMs when it comes to building and selling all-electric vehicles. After years of down-playing EV sales in favor of hybrids and PHEVs, Toyota is instead expanding its all-electric line-up of vehicles just as other automakers are canceling or scaling back multiple EV projects (see page X). Just don't go looking for a bunch of new bZ models on dealer lots. As part of this strategy, Toyota unveiled its largest EV yet, the 2027 Highlander, in February. Applying the name of a popular three-row SUV to what is now an electric-only model is surprising, but the new Highlander should have the performance figures to live up to the name. Toyota will sell two trims, the Limited and XLE, which both use a 95.8-kWh battery to provide an estimated 320 miles (515 km) of range and which can provide off-board power in emergency situations. Available with front- or all-wheel drive, the new Highlander will offer up to 338 combined system hp (252 kW) and 323 lb-ft (438 Nm). The vehicle will also boast seating for seven, more than 45 cu ft of rear storage (with the third-row seats folded down) and the latest versions of Toyota's infotainment and Safety Sense Systems. The Highlander will be assembled at Toyota Motor Manufacturing Kentucky while the battery modules will be assembled at the Toyota Battery Manufacturing North Carolina (TBMNC) Battery Plant and at partner suppliers in the U.S.
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 enhanced energy-efficiency, reduced component and system costs, and a cut-down in development time of EVs, enabled by digital-twin-based design methodologies. Beyond these performance gains, SmartCorners establishes the foundational principles of modularity, adaptability, and software integration that underpin the evolution toward SDVs. The role of thermal and cabin comfort control is completely different for EVs and internal combustion engine vehicles, with the latter using waste heat from the combustion of fossil fuels for cabin heating, ventilation, and cooling (HVAC). In EVs the required energy is directly taken from the traction battery and precise thermal and cabin comfort control affecting essential components of the vehicle but also the user-perceived driving experience. These project achievements highlight a critical bridge between innovation and electrification on component-level, and the holistic software-defined mobility systems of the future.
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 method is used to monitor SiC MOSFET temperature, the power loss computation of SiC MOSFET is a key factor. However, the existing loss calculation method assumes electric motors operate at high speed and power loss is computed/estimated with rms current. When the motor operates at low speed, the existing method is not practical because of a long fundamental period of phase current. The instantaneous power losses and hence the junction temperatures of the six power converter switches are not the same under such operating conditions. Hence, the junction temperature obtained with the loss computed from the rms current value does not reflect the actual device junction temperature, which may result in a failure of power device over-temperature (OT). This paper proposes a converter power device OT protection method under low motor speed to solve the above issues. The proposed method allows system cost and complexity reduction. It computes/estimates instantaneous loss and junction temperature for each individual power device of the power converter, which enables the OT detection at the motor low speed and/or imbalance phase operation. The paper presents the technical principle of the proposed instantaneous power loss and junction temperature estimation method, and OT protection for SiC MOSFET. Its model details, simulation, and experimental test results verify the new method.
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 are analyzed under varying operational parameters. The EDU design is then refined through multiple design iterations using the SPH method to enhance splashing characteristics and improve WF for critical components. This work demonstrates the effectiveness of the SPH method as a robust virtual prototyping tool for next-generation EDU lubrication system design.
The concept of the vehicle has changed as a result of many innovations over the last decade in the fields of connected, autonomous/automated, shared, and electric (CASE) technologies. At the same time, labor shortages in Japan are becoming more serious due to a decline in the working population. To help resolve these issues, a remote-controlled autonomous vehicle driving system called Telemotion has been developed that automates the movement of vehicles in production plants. This system is an autonomous driving and transportation system in which the recognition, judgment, and operation functions of driving are handled by a control system outside the vehicle that communicates wirelessly with the vehicle. This system utilizes artificial intelligence (AI) and other advanced technologies to realize safe unmanned autonomous driving, and is already in operation in production plants. Currently, efforts are under way to build a digital twin environment and conduct AI learning using computer graphics (CG) to configure the system and improve the accuracy of the AI models with the aim of expanding its use to other factories. Within this digital twin environment, it is possible to examine previous tasks by reproducing the vehicles, processes, cameras, and vehicle movements present at a production site. Utilizing this digital twin enabled a significant reduction in the labor required to implement the system.
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- and medium-power charging units adapted to household electrical networks. The paper contains an example of a three-phase charging device with adaptive power take-off for each phase, taking into account the instantaneous load of the network by household consumers. The paper considers the issues of implementing a positive energy balance of the BEV-charger-electric grid system using mobile energy storage devices based on the secondary use of car batteries.
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 are blown apart between the welds to form a 3D structure that is three times stiffer and twice as strong as a flat monolithic sheet of the same thickness. The composite dual bubble sheets can effectively reduce structural vibration. Damping materials, such as liquid-applied sound deadener (LASD), can be injected into the bubble sheet cavities to significantly improve its damping performance. Prototype bubble sheets have been designed, analyzed, and tested for an integrated inverter used in front-wheel-drive (FWD) electric drive unit for EV applications. Analysis and modal tests show a reduction of 10 to 15 dB at panel resonances with close to 30% reduction in mass. The bubble sheet panel is installed on an integrated inverter and tested in the electric drive unit. Sound power measurements confirm a reduction of up to 10 dB in inverter panel vibration.
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 mimics the sound of gear shifting is generated by controlling different pulse ratios at each shifting RPM zone. High switching orders are dropped between neighboring zones to boost lower frequencies for an enhanced dynamic driving experience. These new switching sound features have been validated through electric drive unit and electric vehicle tests. Jury tests confirm the new EV sound with switching orders is authentically generated from electric propulsion system and can be tuned by controlling the switching pulse ratio. This technology has been successfully implemented in the "Watts-to-Freedom" drive mode of the Hummer EV, providing enhanced EV sound feedback, and improving the driver's experience during high-acceleration events.
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