Improvement of an EVT-based HEV using dynamic programming

Automotive engineers and researchers have proposed different Series-Parallel Hybrid Electric Vehicle SP-HEV topologies. The Toyota Hybrid System (THS) is the most known SP-HEV based vehicle, but alternative solutions such as Electric Variable Transmission (EVT) have been also proposed. Efficient comparison between these different solutions is a key point in order to estimate the added value of each topology. This paper presents the application of optimal control to two series-parallel hybrid architectures for efficiency assessment purpose. The dynamic programming method is applied to the THS as well as to a virtual hybrid vehicle with an EVT. The way to take into account the supplementary degree of freedom provided by the decoupling of wheels and engine in both topologies is presented. The optimal fuel consumptions are then compared on different driving cycles and bring out an over consumption of the EVT topology. Then, a parametric study shows that inserting an appropriate gear ratio on the ICE shaft can improve the EVT efficiency that becomes close to the THS efficiency

Convex modeling for optimal battery sizing and control of an electric variable transmission powertrain

Hybrid Electric Vehicles are being considered a convenient intermediate product in the conversion process from conventional to pure electric vehicles, due to their compromise on cost, fuel consumption, and driving range. Convex modeling steps for the problem of optimal battery sizing and energy management of a plug-in hybrid electric vehicle with an electric variable transmission are presented. Optimal energy management was achieved by a switched model control, with driving modes identified by the engine on/off state. In pure electric mode, convex optimization was employed to find the optimal torque split between two electric machines, to maximize powertrain efficiency. In hybrid mode, optimization was carried out in a bilevel program. One level optimizes speed of a compound unit that includes the engine and electric machines. Another level optimizes the power split between the compound unit and the battery. The proposed method is used to minimize the total cost of ownership of a passenger vehicle for a daily commuter, including costs for battery, fossil fuel and electricity

Electrical variable transmission for hybrid off-highway vehicles

The push for less emissions has driven transportation towards electrification. The electrical variable transmission is a promising emerging component that has proven to be successful in passenger vehicles and is being considered in this paper for off-highway vehicles. By electromagnetically coupling the internal combustion engine with the wheels, allowing independent rotation, the engine is kept in its optimal operating range. This paper benchmarks the electrical variable transmission to one of the most successful hybrid topologies: the Toyota hybrid system. Flanders Make’s Hybrid Electric Drivetrain CoDesign framework is being used to ensure optimal control decisions for both. Results show that the electrical variable transmission may reduce fuel consumption by 30% and total cost of ownership by 10%

Design of Power Split Hybrid Powertrains with Multiple Planetary Gears and Clutches.

Fuel economy standards for automobiles have become much tighter in many countries in the past decades. Hybrid electric vehicles (HEVs), as one of the most promising solutions to take on these challenging standards, have been successful in the US market. In the last few years, an observed trend is to use multiple planetary gears with multiple operating modes to further improve vehicle fuel economy and driving performance. Most work in existing literature on HEV design and optimization has been based on specific configurations, rather than exhaustively searching through all possible configurations. This limitation arises from the large size of the design space–millions to trillions of possible topological candidates. In this dissertation, a systematic design methodology is presented, which enables the exhaustive search of multi-mode powertrain systems. As a first step, a systematic analysis has been performed for all 12 single PG configurations with multiple operating modes enabled by clutch operation. The Dynamic Programming (DP) technique is used to solve the optimal energy management problems for each design candidate. For multi-mode HEVs with multiple PGs, an automated modeling and mode classification methodology is developed, which makes it possible to exhaustively search all possible designs. General mode shift mechanisms are studied, while mode shift cost is evaluated using Dijkstra’s algorithm, which identifies the optimal mode shift path. For each candidate, the optimal control problem needs to be solved so that all designs can be compared based on their best possible execution. A fast and near-optimal energy management strategy is proposed. The comparison results show that it is up to 10,000 times faster than DP while achieving similar performance. To ensure acceptable launching performance of the design candidates, a fast and optimal acceleration performance test procedure is developed, which can be used to determine optimal control inputs and mode shift schedule. Combining all proposed methodologies produces a systematic and optimal design procedure. Optimization results show that the exhaustive search design method is able to identify dozens of better designs than the production hybrid vehicle models available in today’s market.PhDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/116659/1/xiaowuz_1.pd

Design methodology for a PM electrical variable transmission used in HEV

Designing a permanent magnet electrical variable transmission is a cumbersome task, regardless of the considered application. The main reason for this is the iterative design process using a computationally intensive finite element model calculations that is necessary to model its behaviour. This makes it difficult to study or visualize the impact of design changes on, for example, the fuel consumption or cost of a hybrid electrical vehicle. To solve this, electromagnetic scaling laws are used to set up a performance map of the entire system. This map is able to present the performance (i.e. fuel consumption, cost, maximum acceleration, etc.) as a function of an axial and radial scaling factor. The map thus displays the performance of a series of designs which enable the reader to select the optimal one in a graphical way. Furthermore, feasibility constraints such as maximum weight, are added. These constraints allow to reject designs but make it also possible to study the performance as a function of weight or material cost. This is particularly useful for manufacturers as it gives an idea of how their investment is translated into a reduction in fuel consumption

Improving Computational Efficiency for Energy Management Systems in Plug-in Hybrid Electric Vehicles Using Dynamic Programming Based Controllers

Reducing computational time has become a critical issue in recent years, particularly in the transportation field, where the complexity of scenarios demands lightweight controllers to run large simulations and gather results to study different behaviors. This study proposes two novel formulations of the Optimal Control Problem (OCP) for the Energy Management System of a Plug-in Hybrid Electric Vehicle (PHEV) and compares their performance with a benchmark found in the literature. Dynamic Programming was chosen as the optimization algorithm to solve the OCP in a Matlab environment, using the DynaProg toolbox. The objective is to address the optimality of the fuel economy solution and computational time. In order to improve the computational efficiency of the algorithm, an existing formulation from the literature was modified, which originally utilized three control inputs. The approach involves leveraging the unique equations that describe the Input-Split Hybrid powertrain, resulting in a reduction of control inputs firstly to two and finally to one in the proposed solutions. The aforementioned formulations are referred to as 2-Controls and a 1-Control. Virtual tests were conducted to evaluate the performance of the two formulations. The simulations were carried out in various scenarios, including urban and highway driving, to ensure the versatility of the controllers. The results demonstrate that both proposed formulations achieve a reduction in computational time compared to the benchmark. The 2-Controls formulation achieved a reduction in computational time of approximately 40 times, while the 1-Control formulation achieved a remarkable reduction of approximately 850 times. These reductions in computational time were achieved while obtaining a maximum difference in fuel economy of approximately 1.5% for the 1-Control formulation with respect to the benchmark solution. Overall, this study provides valuable insights into the development of efficient and optimal controllers for PHEVs, which can be applied to various transportation scenarios. The proposed formulations reduce computational time without sacrificing the optimality of the fuel economy solution, making them a promising approach for future research in this area

Rapid assessment of the fuel economy capability of parallel and series-parallel hybrid electric vehicles

Efficiently solving the off-line control problem represents a crucial step to predict the fuel economy capability of hybrid electric vehicles (HEVs). Optimal HEV control approaches implemented in literature usually prove to be either computationally inefficient or sub-optimal. Moreover, they often neglect drivability and comfort associated to the generated control actions over time. This paper therefore aims at introducing a rapid near-optimal approach to solve the off-line control problem for parallel and series-parallel HEV powertrains while accounting for drivability criteria such as the frequency of gear shifts and the number of activations of the thermal engine. The performance of the introduced slope-weighted energy-based rapid control analysis (SERCA) algorithm is compared with the global optimal benchmark provided by dynamic programming (DP) for both the parallel and the series-parallel HEV layouts over different driving missions. Results demonstrate how the SERCA algorithm can produce comparable control results with respect to DP by limiting the increase in the estimated fuel consumption within 2.2%. The corresponding computational time can be simultaneously reduced by around 99.5% while ensuring a limited number of gear shifts and engine activations over time. Engineers could therefore potentially implement the proposed SERCA algorithm in design and calibration procedures of parallel and series-parallel HEVs to accelerate the overall vehicle development process

Torque analysis on a double rotor electrical variable transmission with hybrid excitation

An electrical variable transmission (EVT) can be used as a power splitting device in hybrid electrical vehicles. The EVT analyzed in this paper is a rotating field electrical machine having two concentric rotors. On the outer rotor, permanent magnets (PMs) are combined with a dc-field winding, being the first implementation of its kind. The magnetic field in the machine as well as the electromagnetic torque on both rotors are a function of the q- and d-axis currents of the stator and inner rotor, as well as the dc-field current. To describe and fully understand this multiple-input multiple-output machine, this paper gives an overview of the influence of the different current inputs on the flux linkage and torque on both rotors. Focus is given to the hybrid excitation in the d-axis by combining the dc-field current and the alternating currents. This has the advantage compared to other EVT topologies that unwanted stator torque can be avoided without stator d-axis current flux weakening. Results of the analysis are presented by means of the torque to current characteristics of a double rotor PM-assisted EVT, as well as the torque to current ratios. The machine characteristics are finally experimentally verified on a prototype machine

Performance comparison between SiC and Si inverter modules in an electrical variable transmission application

This paper evaluates the performance of Silicon Carbide MOSFET and Silicon IGBT modules in a threephase inverter for Electrical Variable Transmission systems. For this purpose, two practical inverter setups were developed and compared. An increase of several percentage points is visible over the entire operating range for the Silicon Carbide prototype. The total energy efficiency increased by 3.7% for the rotor and by 11.2% for the stator, for the same test conditions

Energy management strategy for oscillating drivetrains equipped with an electric variable transmission

In this study the dynamic capability of the Electric Variable Transmission (EVT) is presented based on the tracking of a highly dynamic oscillating load. The targeted applications are 3-phase grid connected machines with periodic motions at high frequencies (> 5) Hz, which result in a high alternating to average power ratio (> 5). The overall consumed grid energy is minimized by a high-level non-parametric cascaded control to recuperate the oscillating load energy in a mechanical energy storage component. Here in this paper, this oscillating energy is stored in the inner rotor of the EVT, thereby making EVT an energy storing device in itself. The drivetrain containing an EVT is also shown to have a good load speed tracking performance with the maximum error of +/-1%