Powertrain Design Research Articles

Electric Vehicle Powertrains with Modular Battery Banks Tied to Multilevel NPC Inverters

Nowadays, the internal combustion engine in vehicles is being replaced by electric motors, giving way to the electric vehicle, which results in reduced environmental impact, higher efficiency and lower emission of greenhouse gases. The powertrain of an electric vehicle is its most prominent subsystem, with the batteries and traction inverter being key components. Thus, due to their relevance, advances in the design of both components are of paramount importance. In this paper, the potential benefits achieved through a powertrain design approach based on combining a modular battery bank with multilevel NPC traction inverter topologies were analyzed, in comparison to a conventional two-level powertrain design. Several aspects were analyzed: modularity, complexity, battery-pack state-of-charge balancing, inverter loss, motor ac voltage harmonic distortion, motor common-mode voltage and reliability. Particularly, from the comparison study developed under the selected design scenario, the proposed design approach, based on modular battery packs and multilevel technology, shows a potential reduction of up to 55% in inverter losses, up to 65% in motor ac-voltage total harmonic distortion, and up to 75% in rms common-mode voltage.

Design and Analysis of Modular Multilevel Reconfigurable Battery Converters for Variable Bus Voltage Powertrains

Larger battery packs, an efficient battery management system, highly efficient electromechanical conversion, and fast battery charging are the key factors for extending the drive range of electric vehicles and the expansion of electromobility. We present a novel highly stable modular multilevel powertrain design with a variable dc-bus voltage, active inner battery energy flow control, and reduced filter size. The underlying powertrain design replaces conventional hard-wired batteries by a modular multilevel architecture, thus modularizing the battery pack and increasing the energy efficiency, reducing the output filter size, and providing full control over the output voltage and energy flow of the battery cells. We analyse the large-signal stability of the proposed system and compare it to dc/dc-dc/ac conventional multiconverter powertrains, demonstrating better stability and lower filter requirements. Further, we experimentally evaluate the proposed system structure. In the experimental setup, we achieve stable converter operation with the output filter capacitor reduced by a factor of 24 and the filter inductor reduced by a factor of 17 compared to dc-dc-dc-ac reference system, thereby leading to a significant reduction of system cost, size, and weight.

Comparative Analysis of Single, Double and Quad Electric Vehicle Powertrain Systems

Electric vehicles offer a promising solution to solving environmental problems related to air pollution. The typical powertrain design of an electric vehicle includes a relatively high-speed-low-torque electric motor integrated with some mechanical system to transmit the output mechanical energy to the wheels, such as the gearbox, transmission and differential. Different drivetrain configurations with single, double and quad electric motors can be used in electric vehicles. In this study, it is aimed to compare the effects of different powertrain configurations on the acceleration performance, range and energy consumption of the electric vehicle. Single, dual and quad motor electric vehicle powertrain systems were simulated with MATLAB Simulink according to the New European Driving Cycle (NEDC). The Volvo XC40 Recharge electric car was used as the reference vehicle with the same vehicle characteristics, battery type/capacity and the same total power output by changing only the electric motor powertrain configurations. It has been determined that quadruple electric motor powertrain configuration has lower energy consumption, longer range and better acceleration performance than the single and double electric motor powertrain configurations.

Artificial Intelligence and Its Roles in the R&D of Vehicle Powertrain Products

Review Artificial Intelligence and Its Roles in the R&D of Vehicle Powertrain Products Quan Zhou , * , Ji Li , and Hongming Xu , * Birmingham CASE Automotive Research and Education Centre, University of Birmingham, Birmingham, B15 2TT UK * Correspondence: q.zhou@bham.ac.uk (Q.Z.); h.m.xu@bham.ac.uk (H.X.) Received: 5 October 2022 Accepted: 20 November 2022 Published: 25 December 2022 Abstract: Decarbonization requires global actions, and the transport sector is the main battlefield since it contributes more than 20% of CO 2 emissions. Vehicle electrification is an effective routine to reduce vehicle carbon emissions, but it increases the complexity of the vehicle systems, especially the powertrain systems. The rapid development of artificial intelligence (AI) is promoting the development of new automation technologies that can benefit the automotive industry. This paper reviews the key milestones of AI technology development for vehicle research and development (R&D) and highlights the advantage of AI-based methods in powertrain design and control. An outlook of future research directions will be discussed, and conclusions will be summarized.

Evaluation of the Role of Lubricant Additives in Emission Control

In the last several decades, emission regulations have become a significant driving force for vehicle technologies, from powertrain design to emission control. These technologies will experience continuous improvement and may require a paradigm shift to address more stringent emission regulations. As essential components of powertrain systems, fuel and lubricant additives have uniquely enabled powertrain performance and durability. This review focuses on the complex interactions between the fluids and the emissions control system. Investigations into the impact of fuel aromatic content on both primary and secondary emissions are discussed. This work provides the methodologies and context to evaluate the studies into the interactions between fluids and the emission system components. Research on lubricants interactions with particulate filters shows that the lubricant, when formulated appropriately, does not substantively degrade particulate filter performance. In fact, it was found that the lubricant additives can have positive impact on carbonaceous accumulation in the filter and improve particulate emissions. This work provides an overview and context for assessing the role of lubricant additives in the performance of the complete emission system. Understanding the full impact of the fluids, lubricant and fuel, and the powertrain hardware provides the foundation to design additives to deliver optimized performance for the vehicle with advanced emission control systems.

Aerodynamic and powertrain design of a novel VTOL configuration

This paper presents aerodynamic and powertrain system design of a new configuration of vertical take-off and landing (VTOL) unmanned aerial vehicles (UAVs). This configuration consists of the tandem wing and distributed motors, which is capable of fast take off at an inclined angle to the ground, adequate maneuverability at low airspeed and strong wind resistance. The aerodynamic design is optimized for maximum lift-drag (LD) ratio using engineering estimation method, which is validated and corrected by Computational Fluid Dynamics (CFD) simulation. A powertrain design tool is established by which the propellermotor system can reach high efficiency in both the hover mode and the cruise mode. Then three types of powertrain system are optimized and compared. In the end, the best preliminary design is derived with maximum endurance time.

Optimal design and power management control of hybrid biofuel–electric powertrain

This paper presents a multi-objective optimization procedure for a hybrid biofuel–electric vehicle (HBEV) powertrain design and fuzzy logic control. The vehicle concept is based on an electric drivetrain, while the battery is recharged by an onboard generator coupled to an ethanol-powered engine. The optimization procedure is done by the interactive adaptive-weight genetic algorithm method, aiming for the minimization of the fuel consumption, tailpipe emissions, powertrain size, and charging time, while the battery lifespan is improved. The powertrain parameters are defined as design variables, along with the membership functions, rules, and weights of the fuzzy logic controllers, responsible for the power split among the four in-wheel electric motors, the engine and generator operation. The optimization is done under the combination of four standard driving cycles combined in a 4 times loop, resulting in a 281.8 km path. As compared to a conventional vehicle with the same engine data, the best HBEV solution was able to save 17.78% fuel, while decreasing the emissions by 52.38% HC, 22.85% CO, and 28.57% NOx, considering a battery life expectation of 23,907 h. Moreover, this optimum HBEV was also evaluated under two combinations of real-world driving cycles, reaching fuel savings up to 30% and lower emissions as compared to the conventional vehicle in all analyzed scenarios. Finally, a cost analysis is performed to compare the proposed HBEV powertrain concept with other hybrid vehicle configurations presented in the literature.

Powertrain Design and Energy Management Strategy Optimization for a Fuel Cell Electric Intercity Coach in an Extremely Cold Mountain Area

Facing the challenge that the single-motor electric drive powertrain cannot meet the continuous uphill requirements in the cold mountainous area of the 2022 Beijing Winter Olympics, the manuscript adopted a dual-motor coupling technology. Then, according to the operating characteristics and performance indicators of the fuel cell (FC)–traction battery hybrid power system, the structure design and parameter matching of the vehicle power system architecture were carried out to improve the vehicle’s dynamic performance. Furthermore, considering the extremely cold conditions in the Winter Olympics competition area and the poor low-temperature tolerance of core components of fuel cell electric vehicles (FCEV) under extremely cold conditions, such as the reduced capacity and service life of traction batteries caused by the rapid deterioration of charging and discharging characteristics, the manuscript proposed a fuzzy logic control-based energy management strategy (EMS) optimization method for the proton exchange membrane fuel cell (PEMFC), to reduce the power fluctuation, hydrogen consumption and battery charging/discharging times, and at the same time, to ensure the hybrid power system meets the varying demand under different conditions. In addition, the performance of the proposed approach was investigated and validated in an intercity coach in real-world driving conditions. The experimental results show that the proposed powertrain with an optimal control strategy successfully alleviated the fluctuation of vehicle power demand, reduced the battery charging/discharging times of traction battery, and improved the energy efficiency by 20.7%. The research results of this manuscript are of great significance for the future promotion and application of fuel cell electric coaches in all climate environments, especially in an extremely cold mountain area.

The design of a new type coaxial multilayer rotor helicopter vehicle

Today’s small rotor helicopter vehicles mostly use electric motors and batteries as power sources. Most helicopter power configurations are either front powered or rear powered, causing the center of the helicopter to be offset. This kind of offset should be overcome by structural compensation or by adjusting the angle of attack of the blades, but some lift of the angle of attack will be sacrifice at the same time. This paper proposes a new type of electric helicopter powertrain design. The advantage of new type helicopter design is setting the centre of gravity at the centre position of helicopter. The main shaft of the helicopter through the power transmission method of the electric motor built into the internal gear of the star gear, which improves the design of the center offset of the helicopter. That is improved the flight stability of the helicopter. At the same time, in terms of power transmission, the motor power consumed by the primary gear power of the star gear, while the traditional helicopter power transmission method has three or four gear power losses. The new concept of electric motor with star gear structure proposed in this paper can effectively reduce the transmission power loss of the gear. In addition, the distributed power control system proposed in this paper also reduces the possibility of helicopter crash due to motor failure.

Impact of OEI requirement on parallel hybrid electric turboprop regional aircraft optimization

PurposeParallel hybrid electric (HE) propulsion retrofit is a promising alternative to reduce fuel burn of aircraft operating on short regional flights. However, if the batteries are depleted at the end of the mission, the hybrid powertrain designs with downsized gas turbines (GTs) and additional electric motors might not meet the one-engine inoperative (OEI) missed approach climb performance required by the certification. Alternatively, hybrid designs using the original full-size GT can perform one engine climb without electric assistance. This paper aims to evaluate the impact of overshoot climb requirements on powertrain design and performance comparing the two design approaches.Design/methodology/approachAn aircraft-level parametric mission analysis model is used to evaluate aircraft performance combined with an optimization framework including multiple constraints. An indirect approach using metamodels is used to optimize powertrain sizing and operation strategy.FindingsConsidering OEI climb requirements, no benefits were found using a design with downsized GTs. Equivalent fuel burns were found for hybrid designs that keep the original size GTs, but do not require electric energy for the OEI overshoot at the end of the mission. Then, it is recommended to size the GT to maintain the emergency climb capabilities with no electric assistance to ensure power availability regardless of remaining battery energy.Originality/valueThis work introduces a new perspective on parallel HE sizing with consideration for the dependency of power capability at aircraft level on the electric energy availability in case of critical mission scenarios such as overshoot climb at the end of the mission.

Analysis of hydrogen-powered propulsion system alternatives for diesel-electric regional trains

Non-electrified regional railway lines with typically employed diesel-electric multiple units require alternative propulsion systems to meet increasingly strict emissions regulations. With the aim to identify an optimal alternative to conventional diesel traction, this paper presents a model-based assessment of hydrogen-powered propulsion systems with an internal combustion engine or fuel cells as the prime mover, combined with different energy storage system configurations, based on lithium-ion batteries and/or double-layer capacitors. The analysis encompasses technology identification, design, modelling and assessment of alternative powertrains, explicitly considering case-related constraints imposed by the infrastructure, technical and operational requirements. Using a regional railway network in the Netherlands as a case, we investigate the possibilities in converting a conventional benchmark vehicle and provide the railway undertaking and decision-makers with valuable input for planning of future rolling stock investments. The results indicate the highest fuel-saving potential for fuel cell-based hybrid propulsion systems with lithium-ion battery or a hybrid energy storage system that combines both energy storage system technologies. The two configurations also demonstrate the highest reduction of greenhouse gas emissions compared to the benchmark diesel-driven vehicle, by about 25% for hydrogen produced by steam methane reforming, and about 19% for hydrogen obtained from electrolysis of water with grey electricity.

Multi-domain and Multi-scale model of a fuel cell electric vehicle to predict the effect of the operating conditions and component sizing on fuel cell degradation

One of the key challenges in the design of fuel cell vehicles arises from the need for the simultaneous optimisation of their efficiency and lifetime, which is, in particular, challenging when operating under transient operating conditions; further, the minimisation of costs and the use of critical materials should be considered. To enable a more detailed virtual exploration of the design space, this paper presents a high-fidelity multi-domain and multi-scale model of a fuel cell electric vehicle that is capable of modelling the coupled phenomena from the vehicle level to intra-fuel cell level with a mechanistically based fuel cell model. The high-fidelity multi-domain and multi-scale model of a fuel cell electric vehicle is based on consistent coupling of different domains, that is, mechanical, electrical, electrochemical, gas flow, thermal, and control, which are modelled with mechanistic governing equations coupled to empirical degradation models of electrochemical devices and solved with multirate solvers ensuring flux conservations and synchronization of time steps. Establishing a consistent model based causal interactions between different domains and the significantly different scales associated with the phenomena in these domains, which more consistently virtually replicates the phenomena in a real fuel cell electric vehicle, is crucial for evaluating the impact of the parameters from high scales on intra-fuel cell spatio-temporal characteristics impacting fuel cell degradation. The results demonstrate that the application of an experimentally validated multi-domain and multi-scale model of a fuel cell electric vehicle enables the virtual exploration of interactions considering the scale of vehicle characteristics and its driving pattern to the scale of intra-fuel cell spatio-temporal characteristics and its degradation early in the development stages of the fuel cell electric vehicle. Therefore, the proposed approach represents a valuable contribution to the virtualisation of the system-level design of powertrains of fuel cell electric vehicles and supports front loading in the development process.

Dual HESS electric vehicle powertrain design and fuzzy control based on multi-objective optimization to increase driving range and battery life cycle

This study presents a comprehensive multi-objective optimization approach for a dual HESS-based electric vehicle (EV) powertrain using the interactive adaptive-weight genetic algorithm (i-AWGA) method. The dual HESS EV concept aims to show the benefits of combining independent traction systems powered by their respective energy sources. Therefore, the main purpose of this optimization is to simultaneously maximize driving autonomy and battery lifespan and minimize HESS size, considering design variables from components such as batteries, electric motors, differential, and ultracapacitors. At the same time, three independent fuzzy logic controllers – which perform the power management control between the hybrid energy storage systems – are likewise optimized, tuning their parameters according to the applied constraints. The best trade-off solution, equipped with a 332.34 kg dual HESS mass, achieved a driving range of 285.56 km and a front battery life cycle of 36585 h. As compared to a similar EV powered by a single HESS and optimized under the same driving conditions, the dual HESS EV improved the ratio between the driving range and energy storage system’s overall mass by 3%, reaching a driving range 19.57% longer, and increasing the battery life by up to 22.88%.

Integrated topology and packaging optimization for conceptual-level electric vehicle chassis design via the component-existence method

Conventional vehicle architectures are undergoing significant transformation as automakers embrace electrification. With increased emphasis on lightweight structures design and efficient packaging of new electric powertrains, numerical tools are now essential to help solve these complex material and component distribution problems. To address these challenges, methods for integrated topology and packaging optimization (iTOPO) have been developed to couple these problem statements and form dynamic component-structure interactions. In this work, a component-existence approach is used for conducting iTOPO of self-contained electric vehicle chassis structures to demonstrate the benefits and scalability of this emerging methodology. Examples focus on incorporating simplified components for battery modules and electric motors within the underlying vehicle structure, integrating up to 43 components simultaneously in a 3D design domain. Here, discussion highlights the development of unique integrated layouts, methodology tunability, and practical insights of the formed component-structure interactions. iTOPO results are also compared to equivalent topology-only problems and show less than a 10% difference in compliance despite the addition of various complex integration requirements (e.g. multiple geometries, packaging symmetry).

Active damping control of HEVs using Ansys and Matlab/Simulink software

This paper presents Parallel Hybrid Electric Vehicles (HEVs) powertrain design as well as a motor-based control approach that is designed to control or reduce driveline oscillations by introducing a Proportional-Integral-Derivative (PID) controller and a Fuzzy logic sliding mode controller. Because the torque of the electric motor can be decreased or increased more quickly than that of the Internal Combustion Engine (ICE), the vibration increases significantly. To solve this problem, an electric motor control-based Active Damping Control (ADC) strategy is employed to assure smooth driveline function and provide seamless driving experience for the driver. First, the basic level modeling of a hybrid electric powertrain in Ansys Simplorer environment is created and the performance was studied during the certification drive cycle. Thus, the main components of the powertrain– traction motor, battery and ICE – are researched, and basic models were built. The components were developed based on the Ansys software by using an automotive system level behavioral HEV library with VHDL-AMS language built in Ansys Simplorer environment. In addition, comparison of both controllers was presented. The simulation results show that using the ADC reduces more than 30 % of the driveline oscillations, thereby improving the drivability of HEVs.

An enhanced hypotrochoid spiral optimization algorithm based intertwined optimal sizing and control strategy of a hybrid electric air-ground vehicle

Hybrid electric air-ground vehicles (HEAGVs) are deemed as promising transportations due to their great versatility, mobility, and environmental values. Capable of ground-driving, vertical-take-off-and-land, and near-ground flight, HEAGVs are competent to pass poor road conditions such as broken bridges or cliffs. As a crucial part of the HEAGV development, size of the power sources is hard to design owing to different characteristics of air-driving and ground-driving. Large power sources would result in increased fuel consumption and accelerating battery degradation, while small ones might lead to insufficient power supply. Thus, optimal sizing of the power sources is needed at the functional level of a HEAGV design. Moreover, at the performance level, the control strategy should be taken into account simultaneously, which significantly affects the sizing process. However, the intertwined optimal sizing and control strategy of HEAGV becomes difficult to address due to the expanded design space. Motivated by this, an efficient co-optimization strategy is presented for the studied HEAGV, intended to simultaneously find optimal sizing of the battery pack and turbine-generator pack and optimal logic threshold control parameters. The initial mass, fuel consumption, and battery degradation are chosen as optimization objectives to formulate an objective function. Then, a novel enhanced hypotrochoid spiral optimization algorithm (EHSOA) is proposed to address the intricated co-optimization problem. In this algorithm, an enhanced bi-considering mechanism is firstly proposed to avoid the optimization process being trapped in local optima. The co-optimization is implemented under an air-ground driving cycle. Results show that, compared to the initial design, the proposed strategy reduces initial mass, fuel consumption, and battery degradation by 5.08%, 26.10%, and 2.08%, respectively. Finally, the proposed EHSOA is demonstrated to be more qualified to solve the intricated co-optimization problem in comparison to other optimization algorithms. The proposed co-optimization strategy might provide theoretical insights for future HEAGV powertrain designs.

Li-Ion Battery-Based Hybrid Diesel-Electric Railway Vehicle: In-Depth Life Cycle Cost Analysis

In this study, the life cycle costs of railway projects involving hybrid diesel-electric vehicles are analysed. Specifically, the analysis focuses on the comparison of 3 lithium-ion battery technologies (NMC, LTO and LFP) and 8 energy management strategies (including rule-based and optimization-based strategies). In order to develop this analysis, a methodology that returns the life cycle cost of each proposed case is presented. The methodology includes the optimization of the diesel generator and lithium-ion battery sizing. A scenario based on a real railway line is introduced, and the obtained results are compared to a traditional diesel-electric railway vehicle to develop a techno-economical discussion. The best lithium-ion battery technologies are found to be LTO and NMC, and the most appropriated strategy a state-machine controller optimised by a genetic algorithm approach. The best case obtains a life cycle cost reduction of the 4.0% and diesel savings of the 13.7% compared to a traditional diesel-electric railway vehicle. The proposed analysis is claimed to be potentially helpful for the cost-optimal design and operation definition of powertrains for hybrid railway vehicles.

Decomposition-Based Integrated Optimal Electric Powertrain Design

This paper presents a decomposed co-design optimization framework for an electric vehicle powertrain equipped with a Continuously Variable Transmission (CVT). We jointly design the sizes of the powertrain components and the energy management strategy, considering the design and the dynamics of the transmission. Specifically, we divide the resulting nonlinear optimization problem into separate hierarchical optimization subproblems leveraging the concept of Analytical Target Cascading (ATC). Furthermore, we compare the proposed decomposition-based strategy with a centralized approach, in which we solve the same problem, and show that the method presented in this paper can be a potential alternative to a centralized optimization formulation for solving the large-scale, complex integrated plant and control system design. Finally, we compare the resulting performance of using a CVT on the vehicle total-cost-of-ownership with that equipped with a Fixed-Gear Transmission (FGT), which is what is commonly implemented in current electric vehicles. Our results show that by jointly optimizing the design of the transmission along with the control strategy, the CVT yields a lower energy consumption and total-cost-of-ownership compared to that of the FGT.

The Multi-Objective Optimization of Powertrain Design and Energy Management Strategy for Fuel Cell–Battery Electric Vehicle

Considering the limited driving range and inconvenient energy replenishment way of battery electric vehicle, fuel cell electric vehicles (FC EVs) are taken as a promising way to meet the requirements for long-distance low-carbon driving. However, due to the limitation of FC power ability, a battery is usually adopted as the supplement power source to fill the gap between the requirement of driving and the serviceability of FC. In consequence, energy management is essential and crucial to an efficient power flow to the wheel. In this paper, a self-optimizing power matching strategy is proposed, considering the energy efficiency and battery degradation, via implementing a deep deterministic policy gradient. Based on the proposed strategy, less energy consumption and longer FC and battery life can be expected in FC EV powertrain with optimal hybridization degree.

Systematic design and power management of a novel parallel hybrid electric powertrain for heavy-duty vehicles

A novel multi-degree-of-freedom parallel hybrid propulsion system with multi-gear for heavy-duty vehicles is proposed to optimize fuel economy, driving comfort, and dynamic performance. The system has a compact structure and high integration. The detailed design and the power flow of the parallel hybrid propulsion system are introduced. The full power system prototype is designed and assembled. The control methods for the driving torque compensation and energy management are investigated. The simulated results of the parallel hybrid propulsion system are presented. The propulsion system power is not interrupted during gear shifting with the torque compensation control. The jerk of the vehicle is also reduced during shifting. The internal combustion engine can work more efficiently in the hybrid propulsion mode with the equivalent consumption minimization strategy. The purpose of this paper is to provide a hybrid driving scheme for commercial vehicles.