Optimization of Electric Powertrains Based on Scalable Cost and Performance Models

The authors provide a copious literate review on powertrain design optimization for electric vehicle (EV) powertrains. The review shows a gap in the state of science regarding the consideration of all customer relevant requirements. Existing approaches either focus on performance and energy consumption or concentrate on vehicle dynamics. Based on this insight, the authors analyze customer requirements and derive all vehicle properties that are influenced by the powertrain concept. They find that costs, longitudinal performance, lateral dynamics, off-road capabilities and energy consumption are key vehicle properties. The powertrain concept affects all these properties and thus determines the satisfaction of customer requirements. Subsequently the authors describe a vehicle simulation model that represents all predefined customer requirements in dependence on the powertrain concept design.

Investigation into the energy consumption in electric vehicles (EVs) plays a pivotal role in determining their autonomy and assessing the electric system performance across diverse operational scenarios. This study focuses on the concept of energy regeneration, encompassing the recovery and storage of kinetic mechanical energy during braking or descent in EVs. Employing control systems in power electronics becomes necessary to establish a seamless workflow across operational quadrants to ensure efficient energy regeneration in an electric machine functioning as both a motor and a generator. To seamlessly integrate new technologies into practical applications, it is essential to conduct thorough evaluations in laboratories prior to deployment. This paper introduces an experimental platform specifically designed to analyze energy consumption and storage in EVs by emulating their powertrains in a controlled laboratory environment. The platform comprises key components for emulating the powertrain of a single-motor electric vehicle with single-axle traction, including a power converter configured in two quadrants, an energy storage system, a primary rotating electric machine, and a mechanically coupled point load torque (another motor). This paper provides a detailed guide on implementing such a laboratory and for facilitating the testing of diverse motor technologies and controllers under varied operational conditions. This comprehensive approach allows for the assessment of electromechanical system efficiency, focusing on both energy recovery and comprehensive control of electric power converters. Validation tests conducted under urban conditions and on steep terrains demonstrate the effectiveness of the platform in analyzing the energy efficiency of both the induction machine and the power controller.

The paper presents a number of advanced solutions on electric machines and machine-based systems for the powertrain of electric vehicles (EVs). Two types of systems are considered, namely the drive systems designated to the EV propulsion and the power split devices utilized in the popular series-parallel hybrid electric vehicle architecture. After reviewing the main requirements for the electric drive systems, the paper illustrates advanced electric machine topologies, including a stator permanent magnet (stator-PM) motor, a hybrid-excitation motor, a flux memory motor and a redundant motor structure. Then, it illustrates advanced electric drive systems, such as the magnetic-geared in-wheel drive and the integrated starter generator (ISG). Finally, three machine-based implementations of the power split devices are expounded, built up around the dual-rotor PM machine, the dual-stator PM brushless machine and the magnetic-geared dual-rotor machine. As a conclusion, the development trends in the field of electric machines and machine-based systems for EVs are summarized.

The production of energy for traction in classical vehicles is performed by petrol or oil combustion. The consequence is green gas production. Paper deals with different power trains of electric hybrid and electric vehicles. Electric hybrid vehicles diminish the fuel consumption by giving to the internal combustion engine (ICE) better working conditions with respect to ICE revolutions and demanded power. The kinetic braking energy recovery is an important feature too. Electric vehicles are usually called “green vehicles”. It is true that they do not produce green gas on places where they are driving but it is also true that their traction energy has to be produced with another energy technology used in electric plants. The efficiency of the vehicle powertrain is important. The energy for transportation by vehicles in the world is great. Therefore it is very important what energy production technology for this traction purposes will be used.

This paper investigates the design of a series-parallel hybrid electric powertrain that includes an electric variable transmission (EVT) and two mechanical gears that connect the EVT to the rest of the powertrain. The EVT is implemented as a dual rotor electric machine (EM), which from a design perspective can be studied as two separate EMs. The goal is to optimize the size of the two EMs and the two mechanical gears, while minimizing fuel consumption, subject to performance requirements on top vehicle speed and acceleration time. A practical optimization methodology is proposed that decouples the multi-objective problem into three different control subproblems: a slow dynamic subproblem for fuel economy, a fast dynamic subproblem for acceleration performance and a static optimization subproblem for the top speed performance. Efficient dynamic programming formulations are presented to solve the two dynamic subproblems. Two different scenarios are discussed and analyzed, where the first one presents the influence of the EMs’ sizes on the vehicle performance and the second one delivers near optimal configurations of the EVT powertrain for different gear ratios. A case study is also carried out to compare the sizing results between the proposed method and an existing benchmark method, showing that the two EMs could be reduced by 45% and 11.87% respectively, while powertrain performance could still be maintained at the same level.

Compound-structure permanent-magnet synchronous machine (CS-PMSM) system is a hybrid electric vehicle (HEV) power train concept. Six typical topologies of CS-PMSM are proposed. The comprehensive research based on the radial-radial flux CS-PMSM is presented in this paper. The method of magnetic decoupling is analyzed. The electromagnetic performance is investigated by finite-element method (FEM) and satisfactory results are obtained. The cooling system is designed and the thermal performance is evaluated by FEM and experiments. A special controller suitable for this kind of machine is designed. The CS-PMSM system is validated by simulation and experiment, which provides a reference for the potential application.

With the increasing adoption of electric vehicles (EVs), optimizing lithium-ion battery capacity is critical for overall powertrain performance. Recent studies have optimized battery capacity in isolation without considering interactions with other powertrain components. Furthermore, even when the battery is considered within the full powertrain, most works have only modeled the electrical behavior without examining thermal or ageing dynamics. However, this fails to capture systemic impacts on overall performance. This study takes a holistic approach to investigate the effects of battery capacity optimization on convergence of the full EV powertrain. A battery multiphysics model was developed in MATLAB/Simulink, incorporating experimental data on electrical, thermal, and ageing dynamics and interactions with other components. The model was evaluated using real-world WLTP and Artemis driving cycles to simulate realistic conditions lacking in prior works. The findings reveal significant impacts of battery optimization on total powertrain performance unaccounted for in previous isolated studies. By adopting a system-level perspective and realistic driving cycles, this work provides enhanced understanding of interdependent trade-offs to inform integrated EV design.

Optimization of Power Train and Control Strategy of a Hybrid Electric Vehicle for Maximum Energy Economy

Effective powertrain design for the emerging electric vehicle market is a complex, multidisciplinary problem. As such, engineers may often use formal decomposition-based optimisation strategies to partition the problem into more manageable subproblems and then integrate their solutions to obtain an optimal system design. Sometimes, these strategies yield decision variables that consist of highly-discretised functional data which must be reduced to enable efficient, practical optimisation. Reduced representation methods such as Proper Orthogonal Decomposition (POD) can help achieve this goal, but the effectiveness of POD in terms of design solution accuracy and optimisation efficiency is dependent on its interaction with the optimisation strategy. Therefore, this paper investigates the impact of a tuning parameter within POD on solution accuracy and optimisation efficiency in the context of decomposition-based electric vehicle powertrain design.

Background: The use of electric vehicles is expected to increase day by day. The operating conditions of the rotary shaft seals used in the powertrain of electric vehicles are more challenging than those of internal combustion engines. The maximum operating temperature of seal used in electric vehicles is 150℃ and the maximum operating speed is 16,000RPM. It is impossible for a standard seal with a garter spring not to leak under these operating conditions, which has led us to turn to alternative designs. Objective: The objective of starting this study is to develop a new generation rotary shaft seal to be used in electric vehicles with finite element analysis (FEA) and optimization. Methods: During this study, finite elements, optimization and geometry development methods were used. First of all, alternative spiral knurled seal that can operate at high speeds was designed in this study. Secondly, our alternatively designed seal was tested to determine lifetime. Results: When we checked the results coming from test machines, the first design seal had approximately 5g of leakage at the end of 7 days. In the examinations made after the experiment, it was observed that the spirals were deleted at the end of 7 days. A finite element model of the first designed seal was created and radial load control was performed. When the radial load value obtained from the finite element model and the experimental radial load value are compared, it is seen that there is a deviation of around 4.3%. In the light of these data, the accuracy of the FEA model created in the Abaqus has been proven. The created finite element model was optimized within the boundary conditions with the help of Isight. A prototype of the optimized design seal was produced and a life-time test was carried out. The prototype seal of the optimized design had approximately 4g of leakage after 13 days under the same test conditions. Since the lifetime requested by the customer is 10 days, the optimization made on the seal is considered appropriate. The lifetime of the seal was approximately 95% improved. Conclusion: As a result, a new generation rotary shaft seal that can be used in electric vehicles, which is the aim of our study, has been developed. The prototype rotary shaft seal has been validated according to DIN 3761 specification.

The induction switched reluctance machine (ISRM) is a novel electric machine that integrates the switched reluctance machine (SRM) with rotor inductive conductors to enhance performance in electric vehicle (EV) powertrain applications. In this topology, the rotor conductors act as a magnetic shield, diverting magnetic flux and preventing magnetic field lines from penetrating the rotor body. By engineering this design, short magnetic flux paths are created in both the stator and rotor of the electric machine. Since its recent introduction, the ISRM represents an emerging technology in the early stages of development. Similar to conventional SRMs, the ISRM can take on various topologies with different stator and rotor pole numbers. Minimizing rotor copper loss is a critical consideration in the ISRM design process. This paper examines two distinct ISRM topologies (12/10 and 12/8), and their characteristics are analyzed using the finite element method. Simulation results, including power density, torque density, efficiency, and copper loss, are presented and compared. Finally, the optimal ISRM topology is proposed for hybrid electric powertrains.

The electric vehicle (EV) market has grown over the last few years and even though electric vehicles do not currently possess a high market segment, it is projected that they will do so by 2030. Currently, the electric vehicle industry is looking to resolve the issue of vehicle range, using higher battery capacities and fast charging. Energy consumption is a key issue which heavily effects charging frequency and infrastructure and, therefore, the widespread use of EVs. Although several factors that influence energy consumption of EVs have been identified, a key technology that can make electric vehicles more energy efficient is drivetrain design and development. Based on electric motors’ high torque capabilities, single-speed transmissions are preferred on many light and urban vehicles. In the context of this paper, a prototype electric vehicle is used as a test bed to evaluate energy consumption related to different gear ratio usage on single-speed transmission. For this purpose, real-time data are recorded from experimental road tests and a dynamic model of the vehicle is created and fine-tuned using dedicated software. Dynamic simulations are performed to compare and evaluate different gear ratio set-ups, providing valuable insights into their effect on energy consumption. The correlation of experimental and simulation data is used for the validation of the dynamic model and the evaluation of the results towards the selection of the optimal gear ratio. Based on the aforementioned data, we provide useful information from numerous experimental and simulation results that can be used to evaluate gear ratio effects on electric vehicles’ energy consumption and, at the same time, help to formulate evolving concepts of smart grid and EV integration.

The current legislation requires the increasing levels of vehicle powertrain electrification or hybridization to fulfill the limits of green-house gas emissions. Parallel hybrid electric vehicle (HEV) powertrain topologies are among the frequently used layouts, because of their easy applicability on an existing conventional powertrain by the addition of hybrid modules with mild, full, or plug-in capability. A more “HEV-tailored” approach merges a dedicated hybrid transmission (DHT), an ICE, a gearbox, and one or more electric motors more closely together, reducing HEV powertrain’s mechanical complexity and costs. The current paper investigates a multi-mode HEV with a DHT and two electric machines in optional electric serial or parallel operating modes. Great challenge for the multi-mode HEV topology with DHT is the component sizing: ICE, electric machines, and battery with optimized capacity, and yet fulfilling several roles. On one hand, satisfactory responsiveness on a dynamic driving demands (vehicle acceleration capabilities, top speed etc.). On the other hand, energy consumption achieving better levels than standard parallel HEV topologies. The other challenge for a multi-mode HEV powertrain – similarly as for all HEV powertrains – is a development and optimization of a powertrain supervisory control, based on energy management strategy. These challenges – overall DHT layout, component sizing, and energy management – closely interact and, therefore, must be optimized together. The paper addresses all these challenges using multi-parametric optimization toolchain, that combines a parametric HEV model, energy management strategy, and optimization software. The optimization software includes various optimization strategies: genetic algorithms, gradient based methods, or their combinations. The parametric HEV model is built in GT-Suite 0D/1D/3D multi-physics CAE system simulation software, that also includes different energy management strategies, either locally or globally optimal, considering the whole driving cycle. The toolchain is then used to evaluate the optimal component sizing for two different vehicle classes and fuel economy in a homologation driving cycle and in some real-world driving scenarios. All results are compared to in-house benchmark method.

The innovative powertrain concept of twin-drive- transmission has two identical electric machines and two separate sub-transmissions with two gear ratios. To increase the driving range, an additional internal combustion engine is used as a range extender. Thus the vehicle can get the traction force in pure electric mode as well as in parallel and series hybrid modes. For this powertrain concept, an interior permanent magnet synchronous machine was designed and constructed. The electrical machine was measured on the test bench. The measured efficiency of the prototype E- machine with a commercial inverter is shown in this paper. The energy consumption of the vehicle is affected by the efficiency of the E-machines, especially in pure electric driving mode. The ohmic losses, which are the main losses in the E- machine, depend on the temperature of the stator winding. Thus by applying the thermal management of the two E-machines to the operation strategy of the twin drive, it is possible to select a proper driving strategy in pure electric driving for minimized energy consumption. Simulated and partially measured results with the proposed and the original operation strategy in pure electric driving mode are compared in this paper.

Electrifying the transport sector requires new possibilities for power electronics converters to attain reliable and efficient charging solutions for electric vehicles (EVs). With the continuous development in power electronics converters, the desire to reduce gasoline consumption and to increase the battery capacity for more electric range is achievable for EVs in the near future. The main interface between the power network and EV battery system is a power electronics converter, therefore, there is a considerable need of new power converters with low cost and high reliability for the advance charging mechanism of EVs. The rapid growth in power converter topologies brings substantial opportunities in EV charging process. In view of this fact, this paper investigates the significant aspects, current progress, and challenges associated with several power converters to suggest further improvements in charging systems of EVs. In particular, an extensive analysis of front-end as well as back-end converter configurations is presented. Moreover, the comparative properties of resonant converter topologies along with other DCDC converters are discussed in detail. Additionally, isolated, and non-isolated topologies with soft switching techniques are classified and rigorously analyzed with a view to their respective issues and benefits. It is foreseen that this paper would be a valuable addition and a worthy source of information for researchers exploring the area of power converter topologies for charging solutions of EVs.