An overview of current thermal challenges in transport electrification is introduced in order to underpin the research developments and trends of recent thermal management techniques. Currently, explorations of intelligent thermal management and control strategies prevail among car manufacturers in the context of climate change and global warming impacts. Therefore, major cutting-edge systematic approaches in electrified powertrain are summarized in the first place. In particular, the important role of heating, ventilation and air-condition system (HVAC) is emphasised. The trends in developing efficient HVAC system for future electrified powertrain are analysed. Then electric machine efficiency is under spotlight which could be improved by introducing new thermal management techniques and strengthening the efforts of driveline integrations. The demanded integration efforts are expected to provide better value per volume, or more power output/torque per unit with smaller form factor. Driven by demands, major thermal issues of high-power density machines are raised including the comprehensive understanding of thermal path, and multiphysics challenges are addressed whilst embedding power electronic semiconductors, non-isotropic electromagnetic materials and thermal insulation materials. Last but not least, the present review has listed several typical cooling techniques such as liquid cooling jacket, impingement/spray cooling and immersion cooling that could be applied to facilitate the development of integrated electric machine, and a mechanic-electric-thermal holistic approach is suggested at early design phase. Conclusively, a brief summary of the emerging new cooling techniques is presented and the keys to a successful integration are concluded.

The thermal management of battery systems is critical for maintaining the energy storage capacity, life span, and thermal safety of batteries used in electric vehicles, because the operating temperature is a key factor affecting battery performance. Excessive temperature rises and large temperature differences accelerate the degradation rate of such batteries. Currently, the increasing demand for fast charging and special on-vehicle scenarios has increased the heat dissipation requirements of battery thermal management systems. To address this demand, this work proposes a novel micro heat pipe array (MHPA) for thermal management under a broadened research scope, including high heat generation rates, large tilt angles, mild vibration, and distributed heat generation conditions. The experimental results indicate that the temperature difference is maintained 3.44 °C at a large heat generation of 50 W for a limited range of tilt angles. Furthermore, a mild vehicle vibration condition was found to improve temperature uniformity by 3.3 °C at a heat generation of 10 W. However, the use of distributed heat sources results in a temperature variation of 3.88 °C, suggesting that the heat generation distribution needs to be considered in thermal analyses. Understanding the effects of these special battery-operating conditions on the MHPA could significantly contribute to the enhancement of heat transfer capability and temperature uniformity improvement of battery thermal management systems based on heat pipe technologies. This would facilitate the realization of meeting the higher requirements of future battery systems.

Insulated gate bipolar transistor (IGBT) power module is used for power switching transistor devices in the power supply and motor control circuits in both hybrid electric vehicles and electric vehicles. The target of heat flux of IGBT is continuously increasing due to the demand for power rating improvements and miniaturisation. Without suitable efficient cooling technologies, excessively high temperature and uneven temperature distribution can cause high thermal stress, eventually leading to severe module failures. Therefore, highly efficient cooling solutions are highly required. Vapour chamber with phase change can provide quick heat transfer and low temperature gradient. This study proposes a new IGBT structure integrated with vapour chamber. The tests and simulation results indicate that the thermal and thermo-mechanical performances of IGBT integrated with vapour chamber are better than those of the IGBT with copper baseplate module. The thermal resistance between the junction and heat sink is reduced from 0.25 to 0.14 °C/W, and the temperature uniformity is greatly improved due to the phase change in the vapour chamber. The simulation also investigates the thermal stress distribution, deformation and thermal fatigue lifespan of IGBT power electronics module. A reduction of 21.8% in thermal stress and an increase of 9% in lifespan of Sn–3.5Ag solder are achieved.

Temperature uniformity of lithium-ion batteries and maintaining the temperature within the range for efficient operation are addressed. First, Liquid cold plates are placed on the sides of a prismatic battery, and fins made of aluminum alloy or graphite sheets are applied between battery cells to improve the heat transfer performance. Then a simulation model is built with 70 battery cells and 6 liquid cold plates, and the performance is analyzed according to the flow rate, liquid temperature, and discharge rate. Finally, the results show that temperature differences are mainly caused by the liquid cold plates. The fin surface determines the equivalent thermal conductivity of the battery. The graphite sheets have heterogeneous thermal conductivity, which help improve temperature uniformity and reduce the temperature gradient. With lower density than the aluminum alloy, they offer a lower gravimetric power density for the same heat transfer capacity. In addition to the equivalent thermal conductivity, the temperature difference between the cooling liquid and battery surface is an important parameter for temperature uniformity. Optimizing the fin thickness is found to be an effective way to reduce the temperature difference between the liquid and battery during cooling and improve the temperature uniformity.

Thermal management system is a crucial part in electric vehicles to ensure battery safety and driving comfort. A refrigerant-based thermal management system of electric vehicles with two evaporators connected in series (series system) or in parallel (parallel system) is established. The performances of the two systems are investigated and compared. The results reveal that the optimal refrigerant charge is approximately 600 g. Additionally, there is no correlation between the optimal refrigerant charge, and in the arrangement of heat sinks or the heat loads. Under the optimal refrigerant charge, the coefficient of performance of the series system ranges from 3.47 to 4.71. The coefficient of performance of the parallel system ranges from 3.40 to 4.59, which is lower than that of the series system. Furthermore, the series system has higher exergy efficiency and better cooling performance. The heat source (cabin) with a small thermal mass placed in the rear evaporator of the series system can weaken the lag of its cooling effect. The additional serial evaporator is an alternative solution to the dual-evaporator thermal management system of electric vehicles.

A micro gas turbine (MGT) can potentially be an alternative power source to the conventional internal combustion engine as a range extender in hybrid electric vehicles. The integration of the MGT into a hybrid vehicle needs a new approach for technical validation requirements compared to the testing of an internal combustion engine. Several attributes of the MGT are predicted to cause concerns for vehicle sub-system requirements such as high ambient temperature and start-stop behaviour. This paper describes the results from specially developed experimental techniques for testing the MGT in a typical automotive environment. A black box MGT was used in this study for performance investigation during hot and cold starts. The MGT was instrumented and fitted with automotive standard components to replicate typical vehicle operational conditions. The intake air temperature was varied between 10 and 24 °C. A significant reduction in the power output of the MGT was observed as the intake temperature was increased. The proposed case scenario caused a reduction in nitrogen oxide emissions in the range of 0.02?0.04 g/km because of the lower combustion temperature at high intake temperature. However, hydrocarbon and carbon monoxide emissions have not shown a noticeable reduction during the power output degradation. The experimental results have highlighted the potential issues of using the MGT at higher intake temperatures and suggest design change to take the effect of higher engine bay temperature into account.

Jet ignition is an efficient way to achieve lean burn of the engine and a promising strategy to meet the stringent emission regulations in the future. This paper presents a distributed gas ignition (DGI) combustion concept and realizes a DGI combustion mode using a newly designed DGI igniter. The igniter integrates a fuel injector and a spark plug to achieve minimum volume and easy installation. As the mixture preparation within the jet chamber is essential for the performance of the igniter, different jet chamber injection strategies were tested with varying excess air–fuel ratio ranging from 1.4 to 2.0. By addressing the dual injection strategy, the ignition delay and combustion duration were improved evidently. Compared with the single injection strategy, dual injection strategy improves the flexibility when preparing the mixture inside the jet chamber and therefore retains more fuel. The increased energy density of the jet chamber helps to generate more energetic jets under dual injection strategy, resulting in the improvement of ignition and combustion performance with lean burn. A higher thermal efficiency and a leaner limit of the engine are attained with dual injection than that with single injection. Dual injection exhibits its potential in reducing CO and THC emissions to an acceptable level with leaner mixture. Based on dual injection strategy, the maximum indicated thermal efficiency of 45% is achieved.

Road intersection is one of the most complex and accident-prone traffic scenarios, so it’s challenging for autonomous vehicles (AVs) to make safe and efficient decisions at the intersections. Most of the related studies focus on the solution to a single scenario or only guarantee safety without considering driving efficiency. To address these problems, this study proposed a deep reinforcement learning enabled decision-making framework for AVs to drive through intersections automatically, safely and efficiently. The mapping relationship between traffic images and vehicle operations was obtained by an end-to-end decision-making framework established by convolutional neural networks. Traffic images collected at two timesteps were used to calculate the relative velocity between vehicles. Markov decision process was employed to model the interaction between AVs and other vehicles, and the deep Q-network algorithm was utilized to obtain the optimal driving policy regarding safety and efficiency. To verify the effectiveness of the proposed decision-making framework, the top three accident-prone crossing path crash scenarios at intersections were simulated, when different initial vehicle states were adopted for better generalization capability. The results showed that the developed method could make AVs drive safely and efficiently through intersections in all of the tested scenarios.

Model predictive control (MPC) algorithm is established based on a mathematical model of a plant to forecast the system behavior and optimize the current control move, thus producing the best future performance. Hence, models are core to every form of MPC. An MPC-based controller for path tracking is implemented using a lower-fidelity vehicle model to control a higher-fidelity vehicle model. The vehicle models include a bicycle model, an 8-DOF model, and a 14-DOF model, and the reference paths include a straight line and a circle. In the MPC-based controller, the model is linearized and discretized for state prediction; the tracking is conducted to obtain the heading angle and the lateral position of the vehicle center of mass in inertial coordinates. The output responses are discussed and compared between the developed vehicle dynamics models and the CarSim model with three different steering input signals. The simulation results exhibit good path-tracking performance of the proposed MPC-based controller for different complexity vehicle models, and the controller with high-fidelity model performs better than that with low-fidelity model during trajectory tracking.