Battery Sizing for Mild P2 HEVs Considering the Battery Pack Thermal Limitations

Small capacity and passively cooled battery packs are widely used in mild hybrid electric vehicles (MHEV). In this regard, continuous usage of electric traction could cause thermal runaway of the battery, reducing its life and increasing the risk of fire incidence. Hence, thermal limitations on the battery could be implemented in a supervisory controller to avoid such risks. A vast literature on the topic shows that the problem of battery thermal runaway is solved by applying active cooling or by implementing penalty factors on electric energy utilization for large capacity battery packs. However, they do not address the problem in the case of passive cooled, small capacity battery packs. In this paper, an experimentally validated electro-thermal model of the battery pack is integrated with the hybrid electric vehicle simulator. A supervisory controller using the equivalent consumption minimization strategy with, and without, consideration of thermal limitations are discussed. The results of a simulation of an MHEV with a 0.9 kWh battery pack showed that the thermal limitations of the battery pack caused a 2–3% fuel consumption increase compared to the case without such limitations; however, the limitations led to battery temperatures as high as 180 ◦C. The same simulation showed that the adoption of a 1.8 kWh battery pack led to a fuel consumption reduction of 8–13% without thermal implications

Study of the Impact of E-Machine in Hybrid Dual Clutch Transmission Powertrain

Recent studies show that hybrid powertrains with dual clutch transmission are becoming more common. This is mainly influenced by the fact that they have higher efficiency, allow power-on shifting, and are more compact. However, the electric motor attached to the primary shaft of the transmission might represent some critical issues in statics and dynamics due to additional torque, inertia, and working irregularities. This paper aims to investigate the influence of the electric motor integration in the transmission on the reliability of the overall system. The focus is on the investigation of potential over stresses of the ICE bearings due to the bending of the gearbox primary shaft. To achieve the aim, the static and the rotor dynamic analysis of the inner and outer primary shafts is performed. The numerical analyses show the potential critical issues that can arise from the excessive manufacturing and assembling tolerances, the interaction of the e-machine torque irregularities and inertia with the bending dynamics of the primary shaft

Adaptive Model Predictive Control Including Battery Thermal Limitations for Fuel Consumption Reduction in P2 Hybrid Electric Vehicles

The primary objective of a hybrid electric vehicle (HEV) is to optimize the energy consumption of the automotive powertrain. This optimization has to be applied while respecting the operating conditions of the battery. Otherwise, there is a risk of compromising the battery life and thermal runaway that may result from excessive power transfer across the battery. Such considerations are critical if factoring in the low battery capacity and the passive battery cooling technology that is commonly associated with HEVs. The literature has proposed many solutions to HEV energy optimization. However, only a few of the solutions have addressed this optimization in the presence of thermal constraints. In this paper, a strategy for energy optimization in the presence of thermal constraints is developed for P2 HEVs based on battery sizing and the application of model predictive control (MPC) strategy. To analyse this approach, an electro-thermal battery pack model is integrated with an off-axis P2 HEV powertrain. The battery pack is properly sized to prevent thermal runaway while improving the energy consumption. The power splitting, thermal enhancement and energy optimization of the complex and nonlinear system are handled in this work with an adaptive MPC operated within a moving finite prediction horizon. The simulation results of the HEV SUV demonstrate that, by applying thermal constraints, energy consumption for a 0.9 kWh battery capacity can be reduced by 11.3% relative to the conventional vehicle. This corresponds to about a 1.5% energy increase when there is no thermal constraint. However, by increasing the battery capacity to 1.5 kWh (14s10p), it is possible to reduce the energy consumption by 15.7%. Additional benefits associated with the predictive capability of MPC are reported in terms of energy minimization and thermal improvement

Development of Optimization Based Control Strategy for P2 Hybrid Electric Vehicle including Transient Characteristics of Engine

Models based on steady-state maps estimate fuel consumption to be 2–8% lower than real experimental measured values. This is due to the fact that during transient phases, the engine consumes more fuel than in steady phases. Some literature has addressed the conventional vehicle engine model that improves fuel consumption estimation’s accuracy during the transient state. However, the characteristics of the engine in the scope of hybrid electric vehicles (HEVs) with an integrated control strategy is yet to be covered. The controller is designed to minimize engine operation in the transient phase to enhance energy savings. In this paper, the correlation between fuel enrichment in transient and steady-state fuel estimation is established as transient correction factor (TCF). Its explanatory variable was the engine torque change rate. This paper describes the influence of engine transient characteristics on the fuel consumption of a mild HEV. The work attempts to improve the fuel economy of the HEV by introducing a penalty factor in the controller to optimize the use of the engine in transient regimes. A backward vehicle model was developed for a production vehicle with a conventional powertrain and validated experimentally using data available online. The corresponding hybrid vehicle model was developed by integrating the electric motor and battery components with the conventional vehicle model. A P2 off-axis configuration was chosen to this end as the HEV architecture. A conventional equivalent consumption minimization strategy (ECMS) was used to split the torque request between the engine and the electric motor. This control strategy was modified with TCF to penalize the engine torque change rate. The results of the simulation show that due to less transient operation of the engine, the fuel consumption was reduced from 923 g to 918 g under the US06 driving cycle. The fuel economy of the model has been simulated for UDDS and HW drive cycles too, and fuel consumption improved by 4.4 g and 3.2 g, respectively. It has been verified that by increasing the battery capacity twice (14s24p), the limitations imposed by the battery capacity can be minimized and the fuel usage can be reduced by 9 g in the UDDS cycle

Intelligent Belt Drive Systems in Hybrid Powertrains: a Multipurpose Test Rig

In traditional engine setups Belt Drive Systems (BDS) are in charge of power transmission from the crankshaft to the accessories. They are complex and critical dynamic mechanisms, involving contact mechanics and vibration phenomena. The hybridization of vehicles has increased the severity of the operating conditions of these systems that have become even more critical. The traditional alternator was substituted by a Belt-Starter Generator (BSG), an electric machine that can power the BDS in particular operating conditions to improve the Internal Combustion Engine (ICE) performance or to allow regenerative braking. The aim of the present work is to describe the design and the main characteristic of a test rig conceived to investigate in laboratory environment on the behaviour of belt drive systems in dynamic conditions. Two permanent magnet electric motors are used to replicate the dynamic behavior of crankshaft and BSG in a realistic, though controlled and repaetable, manner

Modeling and Validation of Rolling Rotor Switched Reluctance Motors for Automotive Applications

Electric machines are widely used in modern automotive technologies. Generally, automotive applications require robust and low cost electric motors for the reason of their mass production and operation in different environments. Permanent magnet motors have been used in automotive applications for their high power density when compared to other existing types of motors. Recent years, the price of permanent magnets is sharply increasing and this trend is expected to continue in future. Moreover, brittle nature of permanent magnets make this type of motor less reliable in high vibration applications. Therefore, interest in switched reluctance motors (SRM) for automotive applications are increasing. These machines have number of advantages like: windings are placed only in stator and hence brushes can be excluded, permanent magnets are replaced with electromagnets. All these leads to lower cost in production and higher robustness of the motor. For high torque, low speed applications SRM must be used together with speed reduction mechanisms, resulting in larger dimensions. Even though high efficiency of the speed reduction system is a main design goal in many application, for some applications irreversibility of the speed reducer might be necessary. Rolling rotor switched reluctance motors (RRSRM) comprise all advantages of switched reluctance motors and due to rolling motion of the motor covers also the function of speed reduction mechanism. Wide range of analyzed literature on RRSRM studies, showed that there is no generalized method which allows dimensioning of this type of motor to achieve required specifications. To fill this gap the analytical model based on magnetic circuit analysis and numerical model based on finite element nonlinear analysis to study the performance of motor have been developed. The validation of the developed models was performed on a prototype of rolling rotor motor that was designed and built within the scope of the present study. Furthermore, main parameters to achieve the system irreversibility are defined by considering toothed wheels of RRSRM as an one stage cycloidal speed reduce

Modeling, Simulation and Control Strategy Optimization of Fuel Cell Hybrid Electric Vehicle

This work represents the development of a Fuel Cell Hybrid Electric Vehicle (FCHEV) model, its validation, and the comparison of different control strategies based on the Toyota Mirai (1st generation) vehicle and its subsystems. The main investigated parameters are hydrogen consumption, and the variation of the state of charge, current, and voltage of the battery. The FCHEV model, which is made up of multiple subsystems, is developed and simulated in MATLAB® Simulink environment using a rule-based control strategy derived from the real system. The results of the model were validated using the experimental data obtained from the open-source Argonne National Laboratory (ANL) database. In the second part, the equivalent consumption minimization strategy is implemented into the controller logic to optimize the existing control strategy and investigate the difference in hydrogen consumption. It was found that the ECMS control strategy outperforms the rule-based one in all drive cycles by 0.4–15.6%. On the other hand, when compared to the real controller, ECMS performs worse for certain considered driving cycles and outperforms others

Sensitivity Analysis of Electric Energy Consumption in Battery Electric Vehicles with Different Electric Motors

In the last decade, a number of research works in electrified vehicles have been devoted to the analysis of the electric consumption of battery electric vehicles and the evaluation of the main influencing factors. The literature analysis reveals that the electric motor size, efficiency, and driving condition substantially affect the electric energy stored in the vehicle battery. This paper studies the degree of sensitivity of energy consumption to electric motor size and to its efficiency map characteristics. In order to accomplish this task, three electric motors whose parameters are re-scaled to fit the maximum power torque and speed with different efficiency maps are simulated by installing them on two commercially available battery electric vehicles. This allows for isolating the influence of the efficiency map on electricity consumption. The original characteristics of the motors are then used to evaluate the influence on the electricity consumption of both the size and the efficiency characteristics. The results of the simulation revealed that the influences of the efficiency map and the electric motor size can be around 8–10% and 2–11%, respectively. When both factors are taken into account, the overall difference in electricity consumption can be around 10–21%

Adaptive Model Predictive Control Including Battery Thermal Limitations for Fuel Consumption Reduction in P2 Hybrid Electric Vehicles

The primary objective of a hybrid electric vehicle (HEV) is to optimize the energy consumption of the automotive powertrain. This optimization has to be applied while respecting the operating conditions of the battery. Otherwise, there is a risk of compromising the battery life and thermal runaway that may result from excessive power transfer across the battery. Such considerations are critical if factoring in the low battery capacity and the passive battery cooling technology that is commonly associated with HEVs. The literature has proposed many solutions to HEV energy optimization. However, only a few of the solutions have addressed this optimization in the presence of thermal constraints. In this paper, a strategy for energy optimization in the presence of thermal constraints is developed for P2 HEVs based on battery sizing and the application of model predictive control (MPC) strategy. To analyse this approach, an electro-thermal battery pack model is integrated with an off-axis P2 HEV powertrain. The battery pack is properly sized to prevent thermal runaway while improving the energy consumption. The power splitting, thermal enhancement and energy optimization of the complex and nonlinear system are handled in this work with an adaptive MPC operated within a moving finite prediction horizon. The simulation results of the HEV SUV demonstrate that, by applying thermal constraints, energy consumption for a 0.9 kWh battery capacity can be reduced by 11.3% relative to the conventional vehicle. This corresponds to about a 1.5% energy increase when there is no thermal constraint. However, by increasing the battery capacity to 1.5 kWh (14s10p), it is possible to reduce the energy consumption by 15.7%. Additional benefits associated with the predictive capability of MPC are reported in terms of energy minimization and thermal improvement