The aim of this project is to develop a family of generic heat pumps for on-board reversible air conditioning systems to replace heating systems using electrical resistance. In that perspective, it is necessary to design and/or adapt architectures and components allowing the realization of on-board reversible heat pumps (providing heating and cooling), with high energy efficiency, and using an electrical compressor. Barriers to be overcome are as follows: • To use a refrigerant with GWP lower than 150 and presenting high energy efficiency in heating mode for outdoor temperature of -30°C as well as in cooling mode for outdoor temperature of +40°C • To design fully-brazed aluminum heat-exchangers with new optimized fin designs, so as to achieve improved management of frosting/defrosting cycles, which is a major stake for robust and durable use of heat pumps in transports • To design new defrosting strategies that do not reverse the cycle and do not impact the cabin comfort • To develop systems diffusing heating and cooling as close as possible of passengers in order to improve the ratio of useful energy to produced energy. Once those barriers will be overcome and technical solutions will be proven at the laboratory level, two demonstrators will be designed, realized, and tested; one pre-existing demonstrator of heat pump for electric vehicle will be modified to integrate the new heat exchangers, modify the defrosting mode, and modify the overall system control. It will be necessary to perform dynamic simulation of heating and cooling needs as well as the associated overall energy management, which is specific to plug-in hybrid vehicles, electric vehicles, trains, and tramways. Pre-conditioning strategies will be designed and implemented. The two plus one demonstrators of reversible heat pumps will be designed in parallel and require dedicated developments for: • Plug-in hybrid vehicles • Electric vehicles • Car tramway The three prototypes will be realized during this project and will be tested during one year integrating the four seasons. This will allow tests in heating and cooling modes. Prototypes will operate as of the beginning of the third year of the program and measurements will be carried out over one year.

As technology increases and performance requirements continually tighten, the cost and the required precision of assemblies increase as well. Due to the variations associated with manufacturing process, it is not possible to attain the theoretical dimensions in a repetitive manner. It causes a degradation of functional characteristics of the product. In order to ensure the desired behavior and the functional requirements of the system in spite of variations, the component features are assigned a tolerance zone within which the value of the feature i.e. situation and intrinsic lie. Therefore, tolerance analysis is a key element in industry for improving product quality and decreasing the manufacturing cost. In addition, it participates to an eco-aware attitude since it allows industrials to manage and reduce scrap in production. Tolerance analysis concerns the verification of the value of functional requirements after tolerance has been specified on each component. The main objective of the AHTOLA proposal is to develop hybrid approaches for a large scope of product behavior models. Those approaches have to be based on: - worst case analysis approaches like Solution Space Exploration based on Interval Reduction Methods (Numerical Quantified Constraint Satisfaction Problem - Box consistency, …), Solution Space Exploration based on Evolutionary Methods (Genetic algorithm, …), and … to assess the worst gap configurations regarding to the assemblability and the functional requirements ; - probabilistic approaches like Simulation based method (Monte Carlo Simulation …), Most probable point based methods (FORM-SORM), Meta-modeling based method (Kriging …), to estimate the probability of system conformity based on the process capabilities or statistical distributions of component deviations.

Recent advances in simulation (hardware and software) make its use more accessible, and engineering departments have changed from scarce and costly expert simulation, to more accessible engineering calculations carried out daily. Paradoxically, the proliferation of data and results dramatically increases the task of those who must use them and optimize them: the complexity is shifted from mastery of the simulation process to the optimization methodology for complete systems. The questions that now arise to an engineer are related to the factors in its study. Are the selected parameters relevant, does he have to consider interactions, or are the ranges large enough? Is the model accurate and reliable? Ultimately, how far does he have the means to take optimization? The PEPITO project aims to experiment with a drastic approach using multi-physics and highly intensive computations, parameterized geometries and simulations, and design of experiments with a large number of factors. It also aims to seek for optima in a large dimension domain. This contribution to the development of sciences that treat and fully exploit the big data stream from intensive simulations will provide tools for the evaluation of parametric effects, for the exploration of large domains of solutions and for dealing with robustness and / or reliability. The optimization process will concern turbomachinery cases proposed by industrial partners. It will rely on the construction of response surfaces (with uncertainty assessments) and on multi-objective research techniques, with or without constraints, in very large domains (up to 60 parameters). Innovative methods are required for design of experiments, sensitivity analysis, dimension reduction, meta-modeling by kriging, co-kriging and neural networks, and in general terms for numerical experiments when they are costly, time consuming (in months) and require the use of high-performance computers. Developments will be made in the field of (multiphysics) performance prediction for rotating machines. The problem of accuracy and reliability for simulations should be carefully studied, especially for irregular geometries based a set of independent parameters. CFD results will be post-processed for acoustic analytical models developed to assess source intensities. Finally, advances are expected in the calculation of eigenmodes in rotating domains, and fluid interaction will be taken into account for mechanics and vibro-acoustics. Intensive simulation strategies will be explored by using fully automated processes and by seeking the optimum linking mesh, solver, parallelization and machine architecture (2.000.000 CPU hours on 125 processors for 2 years). Innovative techniques using parameterized simulations will be studied, and cost reductions will be assessed during the construction of databases with derivatives that contain added information. Implementation of results from the previous fields of research are intended to demonstrate their complementarily for multiphysics optimization in large dimension domains for turbomachines. A summary of academic work and feedback between statisticians and physicists will be proposed at the end of the project, and the industrial added value methods of simulation and optimization will also be evaluated in terms of cost, quality and time.